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Computationally efficient algorithms for statistical image processing: Implementation in R
Langovoy, M., Wittich, O.
(2010-053), EURANDOM, Technische Universiteit Eindhoven, December 2010 (techreport)
In the series of our earlier papers on the subject, we proposed a novel statistical hy- pothesis testing method for detection of objects in noisy images. The method uses results from percolation theory and random graph theory. We developed algorithms that allowed to detect objects of unknown shapes in the presence of nonparametric noise of unknown level and of un- known distribution. No boundary shape constraints were imposed on the objects, only a weak bulk condition for the object's interior was required. Our algorithms have linear complexity and exponential accuracy. In the present paper, we describe an implementation of our nonparametric hypothesis testing method. We provide a program that can be used for statistical experiments in image processing. This program is written in the statistical programming language R.
ei Langovoy, M., Wittich, O. Computationally efficient algorithms for statistical image processing: Implementation in R (2010-053), EURANDOM, Technische Universiteit Eindhoven, December 2010 (techreport)
Similarities in resting state and feature-driven activity: Non-parametric evaluation of human fMRI
Shelton, J., Blaschko, M., Gretton, A., Müller, J., Fischer, E., Bartels, A.
NIPS Workshop on Learning and Planning from Batch Time Series Data, December 2010 (poster)
ei Shelton, J., Blaschko, M., Gretton, A., Müller, J., Fischer, E., Bartels, A. Similarities in resting state and feature-driven activity: Non-parametric evaluation of human fMRI NIPS Workshop on Learning and Planning from Batch Time Series Data, December 2010 (poster)
Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference
Seeger, M., Nickisch, H.
Max Planck Institute for Biological Cybernetics, December 2010 (techreport)
We propose a novel algorithm to solve the expectation propagation relaxation of Bayesian inference for continuous-variable graphical models. In contrast to most previous algorithms, our method is provably convergent. By marrying convergent EP ideas from (Opper&Winther 05) with covariance decoupling techniques (Wipf&Nagarajan 08, Nickisch&Seeger 09), it runs at least an order of magnitude faster than the most commonly used EP solver.
ei Seeger, M., Nickisch, H. Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference Max Planck Institute for Biological Cybernetics, December 2010 (techreport)
Augmentation of fMRI Data Analysis using Resting State Activity and Semi-supervised Canonical Correlation Analysis
Shelton, JA., Blaschko, MB., Bartels, A.
NIPS Women in Machine Learning Workshop (WiML), December 2010 (poster)
Resting state activity is brain activation that arises in the absence of any task, and is usually measured in awake subjects during prolonged fMRI scanning sessions where the only instruction given is to close the eyes and do nothing. It has been recognized in recent years that resting state activity is implicated in a wide variety of brain function. While certain networks of brain areas have different levels of activation at rest and during a task, there is nevertheless significant similarity between activations in the two cases. This suggests that recordings of resting state activity can be used as a source of unlabeled data to augment kernel canonical correlation analysis (KCCA) in a semisupervised setting. We evaluate this setting empirically yielding three main results: (i) KCCA tends to be improved by the use of Laplacian regularization even when no additional unlabeled data are available, (ii) resting state data seem to have a similar marginal distribution to that recorded during the execution of a visual processing task implying largely similar types of activation, and (iii) this source of information can be broadly exploited to improve the robustness of empirical inference in fMRI studies, an inherently data poor domain.
ei Shelton, JA., Blaschko, MB., Bartels, A. Augmentation of fMRI Data Analysis using Resting State Activity and Semi-supervised Canonical Correlation Analysis NIPS Women in Machine Learning Workshop (WiML), December 2010 (poster)
High frequency phase-spike synchronization of extracellular signals modulates causal interactions in monkey primary visual cortex
Besserve, M., Murayama, Y., Schölkopf, B., Logothetis, N., Panzeri, S.
40(616.2), 40th Annual Meeting of the Society for Neuroscience (Neuroscience), November 2010 (poster)
Functional correlates of Rhythms in the gamma band (30-100Hz) are observed in the mammalian brain with a large variety of functional correlates. Nevertheless, their functional role is still debated. One way to disentangle this issue is to go beyond usual correlation analysis and apply causality measures that quantify the directed interactions between the gamma rhythms and other aspects of neural activity. These measures can be further compared with other aspects of neurophysicological signals to find markers of neural interactions. In a recent study, we analyzed extracellular recordings in the primary visual cortex of 4 anesthetized macaques during the presentation of movie stimuli using a causality measure named Transfer Entropy. We found causal interactions between high frequency gamma rhythms (60-100Hz) recorded in different electrodes, involving in particular their phase, and between the gamma phase and spiking activity quantified by the instantaneous envelope of the MUA band (1-3kHz). Here, we further investigate in the same dataset the meaning of these phase-MUA and phase-phase causal interactions by studying the distribution of phases at multiple recording sites at lags around the occurrence of spiking events. First, we found a sharpening of the gamma phase distribution in one electrode when spikes are occurring in other recording site. This phenomena appeared as a form of phase-spike synchronization and was quantified by an information theoretic measure. We found this measure correlates significantly with phase-MUA causal interactions. Additionally, we quantified in a similar way the interplay between spiking and the phase difference between two recording sites (reflecting the well-know concept of phase synchronization). We found that, depending on the couple of recording site, spiking can correlate either with a phase synchronization or with a desynchronization with respect to the baseline. This effect correlates very well with the phase-phase causality measure. These results provide evidence for high frequency phase-spike synchronization to reflect communication between distant neural populations in V1. Conversely, both phase synchronization or desynchronization may favor neural communication between recording sites. This new result, which contrasts with current hypothesis on the role of phase synchronization, could be interpreted as the presence of inhibitory interactions that are suppressed by desynchronization. Finally, our findings give new insights into the role of gamma rhythms in regulating local computation in the visual cortex.
ei Besserve, M., Murayama, Y., Schölkopf, B., Logothetis, N., Panzeri, S. High frequency phase-spike synchronization of extracellular signals modulates causal interactions in monkey primary visual cortex 40(616.2), 40th Annual Meeting of the Society for Neuroscience (Neuroscience), November 2010 (poster)
Attenuation Correction for Whole Body PET/MR: Quantitative Evaluation and Lung Attenuation Estimation with Consistency Information
Bezrukov, I., Hofmann, M., Aschoff, P., Beyer, T., Mantlik, F., Pichler, B., Schölkopf, B.
2010(M13-122), 2010 Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC), November 2010 (poster)
ei Bezrukov, I., Hofmann, M., Aschoff, P., Beyer, T., Mantlik, F., Pichler, B., Schölkopf, B. Attenuation Correction for Whole Body PET/MR: Quantitative Evaluation and Lung Attenuation Estimation with Consistency Information 2010(M13-122), 2010 Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC), November 2010 (poster)
PET/MRI: Observation of Non-Isotropic Positron Distribution in High Magnetic Fields and Its Diagnostic Impact
Kolb, A., Hofmann, M., Sauter, A., Liu, C., Schölkopf, B., Pichler, B.
2010 Nuclear Science Symposium and Medical Imaging Conference, 2010(M18-119):1, November 2010 (poster)
ei Kolb, A., Hofmann, M., Sauter, A., Liu, C., Schölkopf, B., Pichler, B. PET/MRI: Observation of Non-Isotropic Positron Distribution in High Magnetic Fields and Its Diagnostic Impact 2010 Nuclear Science Symposium and Medical Imaging Conference, 2010(M18-119):1, November 2010 (poster)
Probabilistic Assignment of Chemical Shift Data for Semi-Automatic Amino Acid Recognition
Hooge, J.
11(10):30, 11th Conference of Junior Neuroscientists of T{\"u}bingen (NeNa), October 2010 (poster)
manner. First the backbone resonances are assigned. This is usually achieved from sequential information provided by three chemical shifts: CA, CB and C'. Once the sequence is solved, the second assignment step takes place. For this purpose, the CA-CB and HA chemical shifts are used as a start point for assignment of the side chain resonances, thus connecting the backbone resonances to their respective side chains. This strategy is unfortunately limited by the size of the protein due to increasing signal overlap and missing signals. Therefore, amino acid recognition is in many cases not possible as the CA-CB chemical shift pattern is not sufficient to discriminate between the 20 amino acids. As a result, the first step of the strategy described above remains tedious and time consuming. The combination of modern NMR techniques with new spectrometers now provide information that was not always accessible in the past, due to sensitivity problems. These experiments can be applied efficiently to measure a protein size up to 45 kDa and furthermore provide a unique combination of sequential carbon spin system information. The assignment process can thus benefit from a maximum knowledge input, containing âallâ backbone and side chain chemical shifts as well as an immediate amino acid recognition from the side chain spin system. We propose to extend the software PASTA (Protein ASsignment by Threshold Accepting) to achieve a general sequential assignment of backbone and side-chain resonances in a semi- to fullautomatic per-residue approach. PASTA will offer the possibility to achieve the sequential assignment using any kind of chemical shifts (carbons and/or protons) that can provide sequential information combined with an amino acid recognition feature based on carbon spin system analysis.
ei Hooge, J. Probabilistic Assignment of Chemical Shift Data for Semi-Automatic Amino Acid Recognition 11(10):30, 11th Conference of Junior Neuroscientists of T{\"u}bingen (NeNa), October 2010 (poster)
Generalizing Demonstrated Actions in Manipulation Tasks
Kroemer, O., Detry, R., Piater, J., Peters, J.
IROS 2010 Workshop on Grasp Planning and Task Learning by Imitation, 2010, pages: 1, October 2010 (poster)
Programming-by-demonstration promises to significantly reduce the burden of coding robots to perform new tasks. However, service robots will be presented with a variety of different situations that were not specifically demonstrated to it. In such cases, the robot must autonomously generalize its learned motions to these new situations. We propose a system that can generalize movements to new target locations and even new objects. The former is achieved by using a task-specific coordinate system together with dynamical systems motor primitives. Generalizing actions to new objects is a more complex problem, which we solve by treating it as a continuum-armed bandits problem. Using the bandits framework, we can efficiently optimize the learned action for a specific object. The proposed method was implemented on a real robot and succesfully adapted the grasping action to three different objects. Although we focus on grasping as an example of a task, the proposed methods are much more widely applicable to robot manipulation tasks.
ei Kroemer, O., Detry, R., Piater, J., Peters, J. Generalizing Demonstrated Actions in Manipulation Tasks IROS 2010 Workshop on Grasp Planning and Task Learning by Imitation, 2010, pages: 1, October 2010 (poster)
Inhomogeneous Positron Range Effects in High Magnetic Fields might Cause Severe Artefacts in PET/MRI
Kolb, A., Hofmann, M., Sauter, A., Liu, C., Eriksson, L., Pichler, B.
(0305B), 2010 World Molecular Imaging Congress (WMIC), September 2010 (poster)
The combination of PET and MRI is an emerging field of current research. It is known that the positron range is shortened in high magnetic fields (MF), leading to an improved resolution in PET images. Interestingly, only the fraction of positron range (PR) orthogonal to the MF is reduced and the fraction along the MF is not affected and yields to a non-isotropic count distribution. We measured the PR effect with PET isotopes like F-18, Cu-64, C-11, N-13 and Ga-68. A piece of paper (1 cm2) was soaked with each isotope and placed in the cFOV of a clinical 3T BrainPET/MR scanner. A polyethylene board (PE) was placed as a positron (β+) stopper with an axial distance of 3 cm from the soaked paper. The area under the peaks of one pixel wide profiles along the z-axis in coronal images was compared. Based on these measurements we confirmed our data in organic tissue. A larynx/trachea and lung of a butchered swine were injected with a mixture of NiSO4 for T1 MRI signals and Ga-68, simulating tumor lesions in the respiratory tract. The trachea/larynx were aligned in 35° to the MF lines and a small mass lesion was inserted to imitate a primary tracheal tumor whereas the larynx was injected submucosally in the lower medial part of the epiglottis. Reconstructed PET data show that the annihilated ratio of β+ at the origin position and in the PE depends on the isotope energy and the direction of the MF. The annihilation ratios of the source and PE are 52.4/47.6 (F-18), 57.5/42.5 (Cu-64), 43.7/56.7 (C-11), 31.1/68.9 (N-13) and 14.9/85.1 (Ga-68). In the swine larynx measurement, an artefact with approximately 39% of the lesion activity formed along MF lines 3cm away from the original injected position (fig.1). The data of the trachea showed two shine artefacts with a symmetric alignment along the MF lines. About 58% of the positrons annihilated at the lesion and 21% formed each artefact. The PR effects areminor in tissue of higher or equal density to water (0.096 cm-1). However, the effect is severe in low density tissue or air and might lead to misinterpretation of clinical data.
ei Kolb, A., Hofmann, M., Sauter, A., Liu, C., Eriksson, L., Pichler, B. Inhomogeneous Positron Range Effects in High Magnetic Fields might Cause Severe Artefacts in PET/MRI (0305B), 2010 World Molecular Imaging Congress (WMIC), September 2010 (poster)
A PAC-Bayesian Analysis of Graph Clustering and Pairwise Clustering
Max Planck Institute for Biological Cybernetics, Tübingen, Germany, September 2010 (techreport)
We formulate weighted graph clustering as a prediction problem: given a subset of edge weights we analyze the ability of graph clustering to predict the remaining edge weights. This formulation enables practical and theoretical comparison of different approaches to graph clustering as well as comparison of graph clustering with other possible ways to model the graph. We adapt the PAC-Bayesian analysis of co-clustering (Seldin and Tishby, 2008; Seldin, 2009) to derive a PAC-Bayesian generalization bound for graph clustering. The bound shows that graph clustering should optimize a trade-off between empirical data fit and the mutual information that clusters preserve on the graph nodes. A similar trade-off derived from information-theoretic considerations was already shown to produce state-of-the-art results in practice (Slonim et al., 2005; Yom-Tov and Slonim, 2009). This paper supports the empirical evidence by providing a better theoretical foundation, suggesting formal generalization guarantees, and offering a more accurate way to deal with finite sample issues. We derive a bound minimization algorithm and show that it provides good results in real-life problems and that the derived PAC-Bayesian bound is reasonably tight.
ei Seldin, Y. A PAC-Bayesian Analysis of Graph Clustering and Pairwise Clustering Max Planck Institute for Biological Cybernetics, Tübingen, Germany, September 2010 (techreport)
Sparse nonnegative matrix approximation: new formulations and algorithms
Tandon, R., Sra, S.
(193), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, September 2010 (techreport)
We introduce several new formulations for sparse nonnegative matrix approximation. Subsequently, we solve these formulations by developing generic algorithms. Further, to help selecting a particular sparse formulation, we briefly discuss the interpretation of each formulation. Finally, preliminary experiments are presented to illustrate the behavior of our formulations and algorithms.
ei Tandon, R., Sra, S. Sparse nonnegative matrix approximation: new formulations and algorithms (193), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, September 2010 (techreport)
Robust nonparametric detection of objects in noisy images
(2010-049), EURANDOM, Technische Universiteit Eindhoven, September 2010 (techreport)
We propose a novel statistical hypothesis testing method for detection of objects in noisy images. The method uses results from percolation theory and random graph theory. We present an algorithm that allows to detect objects of unknown shapes in the presence of nonparametric noise of unknown level and of unknown distribution. No boundary shape constraints are imposed on the object, only a weak bulk condition for the object's interior is required. The algorithm has linear complexity and exponential accuracy and is appropriate for real-time systems. In this paper, we develop further the mathematical formalism of our method and explore im- portant connections to the mathematical theory of percolation and statistical physics. We prove results on consistency and algorithmic complexity of our testing procedure. In addition, we address not only an asymptotic behavior of the method, but also a nite sample performance of our test.
ei Langovoy, M., Wittich, O. Robust nonparametric detection of objects in noisy images (2010-049), EURANDOM, Technische Universiteit Eindhoven, September 2010 (techreport)
Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models
Max Planck Institute for Biological Cybernetics, August 2010 (techreport)
Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or super-resolution, can be addressed by maximizing the posterior distribution of a sparse linear model (SLM). We show how higher-order Bayesian decision-making problems, such as optimizing image acquisition in magnetic resonance scanners, can be addressed by querying the SLM posterior covariance, unrelated to the density's mode. We propose a scalable algorithmic framework, with which SLM posteriors over full, high-resolution images can be approximated for the first time, solving a variational optimization problem which is convex iff posterior mode finding is convex. These methods successfully drive the optimization of sampling trajectories for real-world magnetic resonance imaging through Bayesian experimental design, which has not been attempted before. Our methodology provides new insight into similarities and differences between sparse reconstruction and approximate Bayesian inference, and has important implications for compressive sensing of real-world images.
ei Seeger, M., Nickisch, H. Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models Max Planck Institute for Biological Cybernetics, August 2010 (techreport)
Cooperative Cuts for Image Segmentation
Jegelka, S., Bilmes, J.
(UWEETR-1020-0003), University of Washington, Washington DC, USA, August 2010 (techreport)
We propose a novel framework for graph-based cooperative regularization that uses submodular costs on graph edges. We introduce an efficient iterative algorithm to solve the resulting hard discrete optimization problem, and show that it has a guaranteed approximation factor. The edge-submodular formulation is amenable to the same extensions as standard graph cut approaches, and applicable to a range of problems. We apply this method to the image segmentation problem. Specifically, Here, we apply it to introduce a discount for homogeneous boundaries in binary image segmentation on very difficult images, precisely, long thin objects and color and grayscale images with a shading gradient. The experiments show that significant portions of previously truncated objects are now preserved.
ei Jegelka, S., Bilmes, J. Cooperative Cuts for Image Segmentation (UWEETR-1020-0003), University of Washington, Washington DC, USA, August 2010 (techreport)
Fast algorithms for total-variationbased optimization
Barbero, A., Sra, S.
(194), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, August 2010 (techreport)
We derive a number of methods to solve efficiently simple optimization problems subject to a totalvariation (TV) regularization, under different norms of the TV operator and both for the case of 1-dimensional and 2-dimensional data. In spite of the non-smooth, non-separable nature of the TV terms considered, we show that a dual formulation with strong structure can be derived. Taking advantage of this structure we develop adaptions of existing algorithms from the optimization literature, resulting in efficient methods for the problem at hand. Experimental results show that for 1-dimensional data the proposed methods achieve convergence within good accuracy levels in practically linear time, both for L1 and L2 norms. For the more challenging 2-dimensional case a performance of order O(N2 log2 N) for N x N inputs is achieved when using the L2 norm. A final section suggests possible extensions and lines of further work.
ei Barbero, A., Sra, S. Fast algorithms for total-variationbased optimization (194), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, August 2010 (techreport)
Reinforcement Learning by Relative Entropy Policy Search
Peters, J., Mülling, K., Altun, Y.
30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2010), 30, pages: 69, July 2010 (poster)
Policy search is a successful approach to reinforcement learning. However, policy improvements often result in the loss of information. Hence, it has been marred by premature convergence and implausible solutions. As first suggested in the context of covariant policy gradients, many of these problems may be addressed by constraining the information loss. In this book chapter, we continue this path of reasoning and suggest the Relative Entropy Policy Search (REPS) method. The resulting method differs significantly from previous policy gradient approaches and yields an exact update step. It works well on typical reinforcement learning benchmark problems. We will also present a real-world applications where a robot employs REPS to learn how to return balls in a game of table tennis.
ei Peters, J., Mülling, K., Altun, Y. Reinforcement Learning by Relative Entropy Policy Search 30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2010), 30, pages: 69, July 2010 (poster)
A Maximum Entropy Approach to Semi-supervised Learning
Erkan, A., Altun, Y.
Maximum entropy (MaxEnt) framework has been studied extensively in supervised learning. Here, the goal is to find a distribution p that maximizes an entropy function while enforcing data constraints so that the expected values of some (pre-defined) features with respect to p match their empirical counterparts approximately. Using different entropy measures, different model spaces for p and different approximation criteria for the data constraints yields a family of discriminative supervised learning methods (e.g., logistic regression, conditional random fields, least squares and boosting). This framework is known as the generalized maximum entropy framework. Semi-supervised learning (SSL) has emerged in the last decade as a promising field that combines unlabeled data along with labeled data so as to increase the accuracy and robustness of inference algorithms. However, most SSL algorithms to date have had trade-offs, e.g., in terms of scalability or applicability to multi-categorical data. We extend the generalized MaxEnt framework to develop a family of novel SSL algorithms. Extensive empirical evaluation on benchmark data sets that are widely used in the literature demonstrates the validity and competitiveness of the proposed algorithms.
ei Erkan, A., Altun, Y. A Maximum Entropy Approach to Semi-supervised Learning 30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2010), 30, pages: 80, July 2010 (poster)
The effect of positioning aids on PET quantification following MR-based attenuation correction (AC) in PET/MR imaging
Mantlik, F., Hofmann, M., Kupferschläger, J., Werner, M., Pichler, B., Beyer, T.
Journal of Nuclear Medicine, 51(Supplement 2):1418 , June 2010 (poster)
Objectives: We study the quantitative effect of not accounting for the attenuation of patient positioning aids in combined PET/MR imaging. Methods: Positioning aids cannot be detected with conventional MR sequences. We mimic this effect using PET/CT data (Biograph HiRez16) with the foams removed from CT images prior to using them for CT-AC. PET/CT data were acquired using standard parameters (phantoms/patients): 120/140 kVp, 30/250 mAs, 5 mm slices, OSEM (4i, 8s, 5 mm filter) following CT-AC. First, a uniform 68Ge-cylinder was positioned centrally in the PET/CT and fixed with a vacuum mattress (10 cm thick). Second, the same cylinder was placed in 3 positioning aids from the PET/MR (BrainPET-3T). Third, 5 head/neck patients who were fixed in a vacuum mattress were selected. In all 3 studies PET recon post CT-AC based on measured CT images was used as the reference (mCT-AC). The PET/MR set-up was mimicked by segmenting the foam inserts from the measured CT images and setting their voxel values to -1000 HU (air). PET images were reconstructed using CT-AC with the segmented CT images (sCT-AC). PET images with mCT- and sCT-AC were compared. Results: sCT-AC underestimated PET voxel values in the phantom by 6.7% on average compared to mCT-AC with the vacuum mattress in place. 5% of the PET voxels were underestimated by >=10%. Not accounting for MR positioning aids during AC led to an underestimation of 2.8% following sCT-AC, with 5% of the PET voxels being underestimated by >=7% wrt mCT-AC. Preliminary evaluation of the patient data indicates a slightly higher bias from not accounting for patient positioning aids (mean: -9.1%, 5% percentile: -11.2%). Conclusions: A considerable and regionally variable underestimation of the PET activity following AC is observed when positioning aids are not accounted for. This bias may become relevant in neurological activation or dementia studies with PET/MR
ei Mantlik, F., Hofmann, M., Kupferschläger, J., Werner, M., Pichler, B., Beyer, T. The effect of positioning aids on PET quantification following MR-based attenuation correction (AC) in PET/MR imaging Journal of Nuclear Medicine, 51(Supplement 2):1418 , June 2010 (poster)
Multi-task Learning for Zero Training Brain-Computer Interfaces
Alamgir, M., Grosse-Wentrup, M., Altun, Y.
4th International BCI Meeting, June 2010 (poster)
Brain-computer interfaces (BCIs) are limited in their applicability in everyday settings by the current necessity to record subject-specific calibration data prior to actual use of the BCI for communication. In this work, we utilize the framework of multitask learning to construct a BCI that can be used without any subject-specific calibration process, i.e., with zero training data. In BCIs based on EEG or MEG, the predictive function of a subject's intention is commonly modeled as a linear combination of some features derived from spatial and spectral recordings. The coefficients of this combination correspond to the importance of the features for predicting the intention of the subject. These coefficients are usually learned separately for each subject due to inter-subject variability. Principle feature characteristics, however, are known to remain invariant across subject. For example, it is well known that in motor imagery paradigms spectral power in the mu- and beta frequency ranges (roughly 8-14 Hz and 20-30 Hz, respectively) over sensorimotor areas provides most information on a subject's intention. Based on this assumption, we define the intention prediction function as a combination of subject-invariant and subject-specific models, and propose a machine learning method that infers these models jointly using data from multiple subjects. This framework leads to an out-of-the-box intention predictor, where the subject-invariant model can be employed immediately for a subject with no prior data. We present a computationally efficient method to further improve this BCI to incorporate subject-specific variations as such data becomes available. To overcome the problem of high dimensional feature spaces in this context, we further present a new method for finding the relevance of different recording channels according to actions performed by subjects. Usually, the BCI feature representation is a concatenation of spectral features extracted from different channels. This representation, however, is redundant, as recording channels at different spatial locations typically measure overlapping sources within the brain due to volume conduction. We address this problem by assuming that the relevance of different spectral bands is invariant across channels, while learning different weights for each recording electrode. This framework allows us to significantly reduce the feature space dimensionality without discarding potentially useful information. Furthermore, the resulting out-of-the-box BCI can be adapted to different experimental setups, for example EEG caps with different numbers of channels, as long as there exists a mapping across channels in different setups. We demonstrate the feasibility of our approach on a set of experimental EEG data recorded during a standard two-class motor imagery paradigm from a total of ten healthy subjects. Specifically, we show that satisfactory classification results can be achieved with zero training data, and that combining prior recordings with subject-specific calibration data substantially outperforms using subject-specific data only.
ei Alamgir, M., Grosse-Wentrup, M., Altun, Y. Multi-task Learning for Zero Training Brain-Computer Interfaces 4th International BCI Meeting, June 2010 (poster)
Causal Influence of Gamma Oscillations on Performance in Brain-Computer Interfaces
Grosse-Wentrup, M., Hill, J., Schölkopf, B.
4th International BCI Meeting0, June 2010 (poster)
Background and Objective: While machine learning approaches have led to tremendous advances in brain-computer interfaces (BCIs) in recent years (cf. [1]), there still exists a large variation in performance across subjects. Furthermore, a significant proportion of subjects appears incapable of achieving above chance-level classification accuracy [2], which to date includes all subjects in a completely locked-in state that have been trained in BCI control. Understanding the reasons for this variation in performance arguably constitutes one of the most fundamental open questions in research on BCIs. Methods & Results Using a machine learning approach, we derive a trial-wise measure of how well EEG recordings can be classified as either left- or right-hand motor imagery. Specifically, we train a support vector machine (SVM) on log-bandpower features (7-40 Hz) derived from EEG channels after spatial filtering with a surface Laplacian, and then compute the trial-wise distance of the output of the SVM from the separating hyperplane using a cross-validation procedure. We then correlate this trial-wise performance measure, computed on EEG recordings of ten healthy subjects, with log-bandpower in the gamma frequency range (55-85 Hz), and demonstrate that it is positively correlated with frontal- and occipital gamma-power and negatively correlated with centro-parietal gamma-power. This correlation is shown to be highly significant on the group level as well as in six out of ten subjects on the single-subject level. We then utilize the framework for causal inference developed by Pearl, Spirtes and others [3,4] to present evidence that gamma-power is not only correlated with BCI performance but does indeed exert a causal influence on it. Discussion and Conclusions Our results indicate that successful execution of motor imagery, and hence reliable communication by means of a BCI based on motor imagery, requires a volitional shift of gamma-power from centro-parietal to frontal and occipital regions. As such, our results provide the first non-trivial explanation for the variation in BCI performance across and within subjects. As this topographical alteration in gamma-power is likely to correspond to a specific attentional shift, we propose to provide subjects with feedback on their topographical distribution of gamma-power in order to establish the attentional state required for successful execution of motor imagery.
ei Grosse-Wentrup, M., Hill, J., Schölkopf, B. Causal Influence of Gamma Oscillations on Performance in Brain-Computer Interfaces 4th International BCI Meeting0, June 2010 (poster)
Solving large-scale nonnegative least-squares
Sra, S.
16th Conference of the International Linear Algebra Society (ILAS 2010), 16, pages: 19, June 2010, based on Joint work with Dongmin Kim and Inderjit Dhillon (poster)
We study the fundamental problem of nonnegative least squares. This problem was apparently introduced by Lawson and Hanson [1] under the name NNLS. As is evident from its name, NNLS seeks least-squares solutions that are also nonnegative. Owing to its wide-applicability numerous algorithms have been derived for NNLS, beginning from the active-set approach of Lawson and Hanson [1] leading up to the sophisticated interior-point method of Bellavia et al. [2]. We present a new algorithm for NNLS that combines projected subgradients with the non-monotonic gradient descent idea of Barzilai and Borwein [3]. Our resulting algorithm is called BBSG, and we guarantee its convergence by exploiting properties of NNLS in conjunction with projected subgradients. BBSG is surprisingly simple and scales well to large problems. We substantiate our claims by empirically evaluating BBSG and comparing it with established convex solvers and specialized NNLS algorithms. The numerical results suggest that BBSG is a practical method for solving large-scale NNLS problems.
ei Sra, S. Solving large-scale nonnegative least-squares 16th Conference of the International Linear Algebra Society (ILAS 2010), 16, pages: 19, June 2010, based on Joint work with Dongmin Kim and Inderjit Dhillon (poster)
Simultaneous PET/MRI for the evaluation of hemato-oncological diseases with lower extremity manifestations
Sauter, A., Horger, M., Boss, A., Kolb, A., Mantlik, F., Kanz, L., Pfannenberg, C., Stegger, L., Claussen, C., Pichler, B.
Objectives: The study purpose is the evaluation of patients, suffering from hemato-oncological disease with complications at the lower extremities, using simultaneous PET/MRI. Methods: Until now two patients (chronic active graft-versus-host-disease [GvHD], B-non Hodgkin lymphoma [B-NHL]) before and after therapy were examined in a 3-Tesla-BrainPET/MRI hybrid system following F-18-FDG-PET/CT. Simultaneous static PET (1200 sec.) and MRI scans (T1WI, T2WI, post-CA) were acquired. Results: Initial results show the feasibility of using hybrid PET/MRI-technology for musculoskeletal imaging of the lower extremities. Simultaneous PET and MRI could be acquired in diagnostic quality. Before treatment our patient with GvHD had a high fascia and muscle FDG uptake, possibly due to muscle encasement. T2WI and post gadolinium T1WI revealed a fascial thickening and signs of inflammation. After therapy with steroids followed by imatinib the patient's symptoms improved while, the muscular FDG uptake droped whereas the MRI signal remained unchanged. We assume that fascial elasticity improved during therapy despite persistance of fascial thickening. The examination of the second patient with B-NHL manifestation in the tibia showed a significant signal and uptake decrease in the bone marrow and surrounding lesions in both, MRI and PET after therapy with rituximab. The lack of residual FDG-uptake proved superior to MRI information alone helping for exclusion of vital tumor. Conclusions: Combined PET/MRI is a powerful tool to monitor diseases requiring high soft tissue contrast along with molecular information from the FDG uptake.
ei Sauter, A., Horger, M., Boss, A., Kolb, A., Mantlik, F., Kanz, L., Pfannenberg, C., Stegger, L., Claussen, C., Pichler, B. Simultaneous PET/MRI for the evaluation of hemato-oncological diseases with lower extremity manifestations Journal of Nuclear Medicine, 51(Supplement 2):1001 , June 2010 (poster)
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Nickisch, H., Rasmussen, C.
Max Planck Institute for Biological Cybernetics, June 2010 (techreport)
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristics of the data. Recently, the Gaussian Process Latent Variable Model (GPLVM) has successfully been used to find low dimensional manifolds in a variety of complex data. The GPLVM consists of a set of points in a low dimensional latent space, and a stochastic map to the observed space. We show how it can be interpreted as a density model in the observed space. However, the GPLVM is not trained as a density model and therefore yields bad density estimates. We propose a new training strategy and obtain improved generalisation performance and better density estimates in comparative evaluations on several benchmark data sets.
ei Nickisch, H., Rasmussen, C. Gaussian Mixture Modeling with Gaussian Process Latent Variable Models Max Planck Institute for Biological Cybernetics, June 2010 (techreport)
Generalized Proximity and Projection with Norms and Mixed-norms
(192), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, May 2010 (techreport)
We discuss generalized proximity operators (GPO) and their associated generalized projection problems. On inputs of size n, we show how to efficiently apply GPOs and generalized projections for separable norms and distance-like functions to accuracy e in O(n log(1/e)) time. We also derive projection algorithms that run theoretically in O(n log n log(1/e)) time but can for suitable parameter ranges empirically outperform the O(n log(1/e)) projection method. The proximity and projection tasks are either separable, and solved directly, or are reduced to a single root-finding step. We highlight that as a byproduct, our analysis also yields an O(n log(1/e)) (weakly linear-time) procedure for Euclidean projections onto the l1;1-norm ball; previously only an O(n log n) method was known. We provide empirical evaluation to illustrate the performance of our methods, noting that for the l1;1-norm projection, our implementation is more than two orders of magnitude faster than the previously known method.
ei Sra, S. Generalized Proximity and Projection with Norms and Mixed-norms (192), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, May 2010 (techreport)
Solving large-scale nonnegative least squares using an adaptive non-monotonic method
Sra, S., Kim, D., Dhillon, I.
24th European Conference on Operational Research (EURO 2010), 24, pages: 223, April 2010 (poster)
We present an efficient algorithm for large-scale non-negative least-squares (NNLS). We solve NNLS by extending the unconstrained quadratic optimization method of Barzilai and Borwein (BB) to handle nonnegativity constraints. Our approach is simple yet efficient. It differs from other constrained BB variants as: (i) it uses a specific subset of variables for computing BB steps; and (ii) it scales these steps adaptively to ensure convergence. We compare our method with both established convex solvers and specialized NNLS methods, and observe highly competitive empirical performance.
ei Sra, S., Kim, D., Dhillon, I. Solving large-scale nonnegative least squares using an adaptive non-monotonic method 24th European Conference on Operational Research (EURO 2010), 24, pages: 223, April 2010 (poster)
Sparse regression via a trust-region proximal method
Kim, D., Sra, S., Dhillon, I.
We present a method for sparse regression problems. Our method is based on the nonsmooth trust-region framework that minimizes a sum of smooth convex functions and a nonsmooth convex regularizer. By employing a separable quadratic approximation to the smooth part, the method enables the use of proximity operators, which in turn allow tackling the nonsmooth part efficiently. We illustrate our method by implementing it for three important sparse regression problems. In experiments with synthetic and real-world large-scale data, our method is seen to be competitive, robust, and scalable.
ei Kim, D., Sra, S., Dhillon, I. Sparse regression via a trust-region proximal method 24th European Conference on Operational Research (EURO 2010), 24, pages: 278, April 2010 (poster)
Cooperative Cuts: Graph Cuts with Submodular Edge Weights
(189), Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, March 2010 (techreport)
We introduce a problem we call Cooperative cut, where the goal is to find a minimum-cost graph cut but where a submodular function is used to define the cost of a subsets of edges. That means, the cost of an edge that is added to the current cut set C depends on the edges in C. This generalization of the cost in the standard min-cut problem to a submodular cost function immediately makes the problem harder. Not only do we prove NP hardness even for nonnegative submodular costs, but also show a lower bound of Omega(|V|^(1/3)) on the approximation factor for the problem. On the positive side, we propose and compare four approximation algorithms with an overall approximation factor of min { |V|/2, |C*|, O( sqrt(|E|) log |V|), |P_max|}, where C* is the optimal solution, and P_max is the longest s, t path across the cut between given s, t. We also introduce additional heuristics for the problem which have attractive properties from the perspective of practical applications and implementations in that existing fast min-cut libraries may be used as subroutines. Both our approximation algorithms, and our heuristics, appear to do well in practice.
ei Jegelka, S., Bilmes, J. Cooperative Cuts: Graph Cuts with Submodular Edge Weights (189), Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, March 2010 (techreport)
PAC-Bayesian Bounds for Discrete Density Estimation and Co-clustering Analysis
Seldin, Y., Tishby, N.
Workshop "Foundations and New Trends of PAC Bayesian Learning", 2010, March 2010 (poster)
We applied PAC-Bayesian framework to derive gen- eralization bounds for co-clustering1. The analysis yielded regularization terms that were absent in the preceding formulations of this task. The bounds sug- gested that co-clustering should optimize a trade-off between its empirical performance and the mutual in- formation that the cluster variables preserve on row and column indices. Proper regularization enabled us to achieve state-of-the-art results in prediction of the missing ratings in the MovieLens collaborative filtering dataset. In addition a PAC-Bayesian bound for discrete den- sity estimation was derived. We have shown that the PAC-Bayesian bound for classification is a spe- cial case of the PAC-Bayesian bound for discrete den- sity estimation. We further introduced combinatorial priors to PAC-Bayesian analysis. The combinatorial priors are more appropriate for discrete domains, as opposed to Gaussian priors, the latter of which are suitable for continuous domains. It was shown that combinatorial priors lead to regularization terms in the form of mutual information.
ei Seldin, Y., Tishby, N. PAC-Bayesian Bounds for Discrete Density Estimation and Co-clustering Analysis Workshop "Foundations and New Trends of PAC Bayesian Learning", 2010, March 2010 (poster)
Learning the Reward Model of Dialogue POMDPs
Boularias, A., Chinaei, H., Chaib-Draa, B.
NIPS Workshop on Machine Learning for Assistive Technology (MLAT-2010), 2010 (poster)
ei Boularias, A., Chinaei, H., Chaib-Draa, B. Learning the Reward Model of Dialogue POMDPs NIPS Workshop on Machine Learning for Assistive Technology (MLAT-2010), 2010 (poster)
Information-theoretic inference of common ancestors
Steudel, B., Ay, N.
Computing Research Repository (CoRR), abs/1010.5720, pages: 18, 2010 (techreport)
ei Steudel, B., Ay, N. Information-theoretic inference of common ancestors Computing Research Repository (CoRR), abs/1010.5720, pages: 18, 2010 (techreport)
Erste Erfahrungen bei der Beurteilung hämato-onkologischer Krankheitsmanifestationen an den Extremitäten mit einem PET/MRT-Hybridsystem.
Sauter, A., Boss, A., Kolb, A., Mantlik, F., Bethge, W., Kanz, L., Pfannenberg, C., Stegger, L., Pichler, B., Claussen, C., Horger, M.
Thieme Verlag, Stuttgart, Germany, 91. Deutscher R{\"o}ntgenkongress, 2010 (poster)
ei Sauter, A., Boss, A., Kolb, A., Mantlik, F., Bethge, W., Kanz, L., Pfannenberg, C., Stegger, L., Pichler, B., Claussen, C., Horger, M. Erste Erfahrungen bei der Beurteilung hämato-onkologischer Krankheitsmanifestationen an den Extremitäten mit einem PET/MRT-Hybridsystem. Thieme Verlag, Stuttgart, Germany, 91. Deutscher R{\"o}ntgenkongress, 2010 (poster)
Surface-slant-from-texture discrimination: Effects of slant level and texture type
Journal of Vision, 2(7):300, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)
The problem of surface-slant-from-texture was studied psychophysically by measuring the performances of five human subjects in a slant-discrimination task with a number of different types of textures: uniform lattices, randomly displaced lattices, polka dots, Voronoi tessellations, orthogonal sinusoidal plaid patterns, fractal or 1/f noise, "coherent" noise and a "diffusion-based" texture (leopard skin-like). The results show: (1) Improving performance with larger slants for all textures. (2) A "non-symmetrical" performance around a particular slant characterized by a psychometric function that is steeper in the direction of the more slanted orientation. (3) For sufficiently large slants (66 deg) there are no major differences in performance between any of the different textures. (4) For slants at 26, 37 and 53 degrees, however, there are marked differences between the different textures. (5) The observed differences in performance across textures for slants up to 53 degrees are systematic within subjects, and nearly so across them. This allows a rank-order of textures to be formed according to their "helpfulness" — that is, how easy the discrimination task is when a particular texture is mapped on the surface. Polka dots tended to allow the best slant discrimination performance, noise patterns the worst up to the large slant of 66 degrees at which performance was almost independent of the particular texture chosen. Finally, our large number of 2AFC trials (approximately 2800 trials per texture across subjects) and associated tight confidence intervals may enable us to find out about which statistical properties of the textures could be responsible for surface-slant-from-texture estimation, with the ultimate goal of being able to predict observer performance for any arbitrary texture.
ei Rosas, P., Wichmann, F., Wagemans, J. Surface-slant-from-texture discrimination: Effects of slant level and texture type Journal of Vision, 2(7):300, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)
Modelling Contrast Transfer in Spatial Vision
Wichmann, F.
Journal of Vision, 2(10):7, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)
Much of our information about spatial vision comes from detection experiments involving low-contrast stimuli. Contrast discrimination experiments provide one way to explore the visual system's response to stimuli of higher contrast, the results of which allow different models of contrast processing (e.g. energy versus gain-control models) to be critically assessed (Wichmann & Henning, 1999). Studies of detection and discrimination using pulse train stimuli in noise, on the other hand, make predictions about the number, position and properties of noise sources within the processing stream (Henning, Bird & Wichmann, 2002). Here I report modelling results combining data from both sinusoidal and pulse train experiments in and without noise to arrive at a more tightly constrained model of early spatial vision.
ei Wichmann, F. Modelling Contrast Transfer in Spatial Vision Journal of Vision, 2(10):7, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)
Pulse train detection and discrimination in pink noise
Henning, G., Wichmann, F., Bird, C.
Much of our information about spatial vision comes from detection experiments involving low-contrast stimuli. Contrast discrimination experiments provide one way to explore the visual system's response to stimuli of higher contrast. We explored both detection and contrast discrimination performance with sinusoidal and "pulse-train" (or line) gratings. Both types of grating had a fundamental spatial frequency of 2.09-c/deg but the pulse-train, ideally, contains, in addition to its fundamental component, all the harmonics of the fundamental. Although the 2.09-c/deg pulse-train produced on the display was measured and shown to contain at least 8 harmonics at equal contrast, it was no more detectable than its most detectable component; no benefit from having additional information at the harmonics was measurable. The addition of broadband "pink" noise, designed to equalize the detectability of the components of the pulse train, made it about a factor of four more detectable than any of its components. However, in contrast-discrimination experiments, with an in-phase pedestal or masking grating of the same form and phase as the signal and 15% contrast, the noise did not improve the discrimination performance of the pulse train relative to that of its sinusoidal components. In contrast, a 2.09-c/deg "super train," constructed to have 8 equally detectable harmonics, was a factor of five more detectable than any of its components. We discuss the implications of these observations for models of early vision in particular the implications for possible sources of internal noise.
ei Henning, G., Wichmann, F., Bird, C. Pulse train detection and discrimination in pink noise Journal of Vision, 2(7):229, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)
Kernel Dependency Estimation
Weston, J., Chapelle, O., Elisseeff, A., Schölkopf, B., Vapnik, V.
(98), Max Planck Institute for Biological Cybernetics, August 2002 (techreport)
We consider the learning problem of finding a dependency between a general class of objects and another, possibly different, general class of objects. The objects can be for example: vectors, images, strings, trees or graphs. Such a task is made possible by employing similarity measures in both input and output spaces using kernel functions, thus embedding the objects into vector spaces. Output kernels also make it possible to encode prior information and/or invariances in the loss function in an elegant way. We experimentally validate our approach on several tasks: mapping strings to strings, pattern recognition, and reconstruction from partial images.
ei Weston, J., Chapelle, O., Elisseeff, A., Schölkopf, B., Vapnik, V. Kernel Dependency Estimation (98), Max Planck Institute for Biological Cybernetics, August 2002 (techreport)
Phase information in the recognition of natural images
Braun, D., Wichmann, F., Gegenfurtner, K.
Perception, 31(ECVP Abstract Supplement):133, 25th European Conference on Visual Perception, August 2002 (poster)
Fourier phase plays an important role in determining global image structure. For example, when the phase spectrum of an image of a flower is swapped with that of a tank, we usually perceive a tank, even though the amplitude spectrum is still that of the flower. Similarly, when the phase spectrum of an image is randomly swapped across frequencies, that is its Fourier energy is randomly distributed over the image, the resulting image becomes impossible to recognise. Our goal was to evaluate the effect of phase manipulations in a quantitative manner. Subjects viewed two images of natural scenes, one of which contained an animal (the target) embedded in the background. The spectra of the images were manipulated by adding random phase noise at each frequency. The phase noise was the independent variable, uniformly distributed between 0° and ±180°. Subjects were remarkably resistant to phase noise. Even with ±120° noise, subjects were still 75% correct. The proportion of correct answers closely followed the correlation between original and noise-distorted images. Thus it appears as if it was not the global phase information per se that determines our percept of natural images, but rather the effect of phase on local image features.
ei Braun, D., Wichmann, F., Gegenfurtner, K. Phase information in the recognition of natural images Perception, 31(ECVP Abstract Supplement):133, 25th European Conference on Visual Perception, August 2002 (poster)
Detection and discrimination in pink noise
Wichmann, F., Henning, G.
5, pages: 100, 5. T{\"u}binger Wahrnehmungskonferenz (TWK), February 2002 (poster)
Much of our information about early spatial vision comes from detection experiments involving low-contrast stimuli, which are not, perhaps, particularly "natural" stimuli. Contrast discrimination experiments provide one way to explore the visual system's response to stimuli of higher contrast whilst keeping the number of unknown parameters comparatively small. We explored both detection and contrast discrimination performance with sinusoidal and "pulse-train" (or line) gratings. Both types of grating had a fundamental spatial frequency of 2.09-c/deg but the pulse-train, ideally, contains, in addition to its fundamental component, all the harmonics of the fundamental. Although the 2.09-c/deg pulse-train produced on our display was measured using a high-performance digital camera (Photometrics) and shown to contain at least 8 harmonics at equal contrast, it was no more detectable than its most detectable component; no benefit from having additional information at the harmonics was measurable. The addition of broadband 1-D "pink" noise made it about a factor of four more detectable than any of its components. However, in contrast-discrimination experiments, with an in-phase pedestal or masking grating of the same form and phase as the signal and 15% contrast, the noise did not improve the discrimination performance of the pulse train relative to that of its sinusoidal components. We discuss the implications of these observations for models of early vision in particular the implications for possible sources of internal noise.
ei Wichmann, F., Henning, G. Detection and discrimination in pink noise 5, pages: 100, 5. T{\"u}binger Wahrnehmungskonferenz (TWK), February 2002 (poster)
A compression approach to support vector model selection
von Luxburg, U., Bousquet, O., Schölkopf, B.
(101), Max Planck Institute for Biological Cybernetics, 2002, see more detailed JMLR version (techreport)
In this paper we investigate connections between statistical learning theory and data compression on the basis of support vector machine (SVM) model selection. Inspired by several generalization bounds we construct ``compression coefficients'' for SVMs, which measure the amount by which the training labels can be compressed by some classification hypothesis. The main idea is to relate the coding precision of this hypothesis to the width of the margin of the SVM. The compression coefficients connect well known quantities such as the radius-margin ratio R^2/rho^2, the eigenvalues of the kernel matrix and the number of support vectors. To test whether they are useful in practice we ran model selection experiments on several real world datasets. As a result we found that compression coefficients can fairly accurately predict the parameters for which the test error is minimized.
ei von Luxburg, U., Bousquet, O., Schölkopf, B. A compression approach to support vector model selection (101), Max Planck Institute for Biological Cybernetics, 2002, see more detailed JMLR version (techreport)
Application of Monte Carlo Methods to Psychometric Function Fitting
Proceedings of the 33rd European Conference on Mathematical Psychology, pages: 44, 2002 (poster)
The psychometric function relates an observer's performance to an independent variable, usually some physical quantity of a stimulus in a psychophysical task. Here I describe methods to (1) fitting psychometric functions, (2) assessing goodness-of-fit, and (3) providing confidence intervals for the function's parameters and other estimates derived from them. First I describe a constrained maximum-likelihood method for parameter estimation. Using Monte-Carlo simulations I demonstrate that it is important to have a fitting method that takes stimulus-independent errors (or "lapses") into account. Second, a number of goodness-of-fit tests are introduced. Because psychophysical data sets are usually rather small I advocate the use of Monte Carlo resampling techniques that do not rely on asymptotic theory for goodness-of-fit assessment. Third, a parametric bootstrap is employed to estimate the variability of fitted parameters and derived quantities such as thresholds and slopes. I describe how the bootstrap bridging assumption, on which the validity of the procedure depends, can be tested without incurring too high a cost in computation time. Finally I describe how the methods can be extended to test hypotheses concerning the form and shape of several psychometric functions. Software describing the methods is available (http://www.bootstrap-software.com/psignifit/), as well as articles describing the methods in detail (Wichmann&Hill, Perception&Psychophysics, 2001a,b).
ei Wichmann, F. Application of Monte Carlo Methods to Psychometric Function Fitting Proceedings of the 33rd European Conference on Mathematical Psychology, pages: 44, 2002 (poster)
Optimal linear estimation of self-motion - a real-world test of a model of fly tangential neurons
Franz, MO.
SAB 02 Workshop, Robotics as theoretical biology, 7th meeting of the International Society for Simulation of Adaptive Behaviour (SAB), (Editors: Prescott, T.; Webb, B.), 2002 (poster)
The tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during self-motion (see example in Fig.1). We examine whether a simplified linear model of these neurons can be used to estimate self-motion from the optic flow. We present a theory for the construction of an optimal linear estimator incorporating prior knowledge both about the distance distribution of the environment, and about the noise and self-motion statistics of the sensor. The optimal estimator is tested on a gantry carrying an omnidirectional vision sensor that can be moved along three translational and one rotational degree of freedom. The experiments indicate that the proposed approach yields accurate results for rotation estimates, independently of the current translation and scene layout. Translation estimates, however, turned out to be sensitive to simultaneous rotation and to the particular distance distribution of the scene. The gantry experiments confirm that the receptive field organization of the tangential neurons allows them, as an ensemble, to extract self-motion from the optic flow.
ei Franz, MO. Optimal linear estimation of self-motion - a real-world test of a model of fly tangential neurons SAB 02 Workshop, Robotics as theoretical biology, 7th meeting of the International Society for Simulation of Adaptive Behaviour (SAB), (Editors: Prescott, T.; Webb, B.), 2002 (poster)


Install a toilet cake containing bleach that attaches to the toilet bowl. Avoid ones that are dropped into a tank, as the bleach may start to erode the plumbing on the toilet tank.
A pink or reddish slime or stain comes from an airborne bacterium, Serratia marcescens that is found naturally in soil, food and animals. The bacterium produces a red pigment as it grows and multiplies. The bacterium thrives on moisture, therefore it will grow on moist surfaces such as toilet bowls, showerheads, and even pet water bowls. Because the bacterium is found in soil, customers who live near construction sites may frequently notice this pink slim or stain. It is harmless to humans and pets, but can be a nuisance.
If you have a carbon filter, the bacteria growth will intensify because while chlorine will kill the bacteria, the carbon filter removes the chlorine from the water.
Treatment: Keep the affected area clean and wipe the surface with chlorine bleach.
This is often caused by a water main break or heavy water usage nearby, such as fighting fires, maintenance or construction. To determine the cause, e-mail us at info.water@warehamfirdistrict.org or call us at 508-295-0450. The discoloration should clear up in 4-8 hours. Check to make sure the discoloration has cleared by running you COLD water for a minute.
DO NOT use any hot water until the color discoloration has cleared up because the sediment will collect in the hot water tank. Also, DO NOT do any laundry until the discoloration has cleared. If you have done laundry and your clothing has become stained, do not dry the clothes and DO NOT use bleach. Bleach will cause the stain to set. Call the Wareham Water Department at 508-295-0450 and let us know what happened. We have a rust removal product at the office that you may be able to use to remove the stains.
The odor may indicate bacteria growth. This could be in your drain. Over time organic matter (such as hair, soap and food waste) accumulates on the walls of the drain. Bacteria grow on these deposits and emit gases with the odor. When you turn on your faucet, the force of the water going down the drain pushes these gases up into the air where you smell them. Disinfecting the drain with bleach should eliminate the problem. If this doesn't eliminate the problem, or if you notice the odor in more than one place in your home, the bacteria could be growing in you hot water heater. Turn the temperature of the hot water heater up very high for a short period of time. This will kill any bacteria growing in the hot water heater.
If your hot water heater has a magnesium rod to prevent corrosion of the heater, the odor could be caused by sulfur reacting with the magnesium. Contact the company that installed the hot water heater to inquire about either replacing the magnesium rod with an aluminum rod, or having the rod removed (note that removing the rod may void the water heater's warranty).
There are two possible causes for these particles. Try smearing some of the specks between your fingers. If the specks smear, it is a deterioration of the rubber gaskets. You should replace the gaskets in the area you're noticing the particles. If the specks do not smear, it could be due to carbon from a water filter. If you have a water filter, call the manufacturer to have the problem investigated.
If you notice a stronger chlorine smell than normal, our annual main flushing program could cause it. Call our office at 508-295-0450 to find out if we are currently flushing in your area. It should clear up in a couple of hours. If the problem persists, please contact us. If the taste bothers you, keeps an open container of water in your refrigerator. The chlorine will dissipate in an open container.
Temporary low water pressure could be due to heavy water usage in your area such as watering lawns, fighting fires, maintenance, or construction. Water pressure will return to normal after the activity is complete. If you a chronic problem with low water pressure it could be due to several things.


text:
Peanut Centre Nursery is located on the corner of Highway 77 & Mersea Rd 6, just north of Leamington, Ontario, in what was formerly known as the hamlet of 'Peanut Centre'. The rich soil was prime for peanut growing and still is today for growing quality nursery stock.
For over 40 years, Peanut Centre Nursery has been providing quality plants to Windsor, Essex County, and surrounding areas. Established in 1973 by Ted & Josephine DeGoey, the farm changed from tomatoes to nursery stock, row by row. On the weekends, Ted would load up his wagon and truck and drive to the newly established subdivision that were popping up everywhere and sell his shrubs, even offering planting services. Often customers would refer Ted's services to a friend and from there Peanut Centre Nursery had begun. The nursery became a place were customers could come and dig their own shrubs and evergreens from the field at a reasonable price.
After his passing in March 1998, Ted's wife Josephine and their youngest son, Stephen, who was only 19 at the time, worked together for the spring season, planning to close the nursery for good. Stephen, who was attending Wilfrid Laurier University, made the decision to leave school and open the nursery as his full time career. Ownership changed hands later that year and Stephen set off to make Peanut Centre Nursery the garden centre and nursery that it is today.
Peanut Centre Nursery has evolved from a small coldframe greenhouse and 4 acres of field grown nursery stock to a full-service garden centre boasting a large perennial growing greenhouse and 8 acres of quality trees, shrubs, annuals, perennials, landscape boulders, mulches, soils & so much more.
Stephen continues to grow nursery stock and provide installation services, while his wife Katherine manages the retail garden centre.

redpajama_set_name: RedPajamaCommonCrawl


text:
Candnw Rr Depot
Redfield City and Surrounding Area Historical Facts
What is the OK Tire Store at 628 West 2nd Street in Redfield was known as the Norbeck and Nickolson Artesian Building when it was erected in 1908.
The building was built at a cost of $20,000 and it served as the office and supply department for the well drilling operations of Peter Norbeck and Charles Nickolson. The building has also been a foundry and was used as a creamery and cheese factory.
628 West 2nd Street
The Pheasant Capital of the World®
Redfield is the first recorded place in South Dakota to successfully introduce the Chinese Ringneck Pheasant. This lead to the first open season on October 30, 1919. From Spink County, pheasant hunting grew throughout the state. Hunters still flock to Redfield to bag their limit.


A long handle for hard to reach places. 2 inch polyester bent rad brush. Excellent for tight enclosures.
Thick Bent Rad Brush - 2 Inch A long handle for hard to reach places. 2 inch polyester bent rad brush. Excellent for tight enclosures.


text:
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Consolidation Remakes Chemicals
16 August 2018 By Andreas Gocke , Hubert Schönberger , Pranshu Rohatgi , and Philipp Jostarndt
Consolidation has driven M&A in the chemical industry for decades. Now, though, the pace is accelerating, transforming many chemical segments as companies look to focus their portfolios and further optimize their business models. To survive in this environment, companies need more than functional M&A capabilities—to identify specific opportunities, they need to understand the consolidation dynamics within the different specialty-chemical segments.
Adding to the M&A environment's complexity: stepped-up competition from ever-more-sophisticated private equity buyers (which benefit from fewer regulatory or antitrust concerns than strategic buyers), newly assertive competitors from Asia pursuing outbound deals across the globe, and the tricky balancing act many companies must manage as they diversify their offerings while consolidating their focus.
With these dynamics in mind, we have assessed the progress of consolidation in key chemical segments, examined several secondary drivers of M&A in the industry and the impact of private equity in chemicals, and identified a number of concrete steps that executives can take to establish and maintain a competitive edge in the pursuit of M&A deals going forward.
Consolidation on the March
There have always been multiple deal rationales in the chemical industry, but consolidation has consistently been the number-one reason. (See Exhibit 1.) We don't expect that to change; in fact, the pace of consolidation is likely to pick up. Our analysis of all deals announced in chemicals from 2012 through 2017 indicates that segment consolidation is the most popular deal rationale, accounting for almost 46% of all deal value. Portfolio diversification is the second most popular rationale at approximately 22%. M&A for geographic expansion contributes about 9%; technology acquisition accounts for just 1%.
The reasons for consolidation vary. Some companies, such as those in the agrochemical segment, are motivated to consolidate to gain scale and lower costs, which they can accomplish by acquiring related businesses and combining R&D, production, sales, and logistics activities. Others seek to strengthen a specialty, snapping up divisions or assets rather than entire companies. This rationale is particularly dominant among base-chemical players that want to go downstream into high-value and niche businesses such as compounding.
But the degree of consolidation in the different specialty segments varies greatly, and that creates some interesting dynamics and opportunities. In specialty segments where there are still many players—such as industrial cleaners and feed and food additives—we expect the volume of deals to remain strong. In segments that have already undergone significant consolidation—such as industrial gases, paints and coatings, agrochemicals, and flavors and fragrances—we expect fewer but higher-value deals for the simple reason that there are fewer but larger targets. (See Exhibit 2.)
However, to truly understand the opportunities you need to dig a bit deeper into each specific segment.
Industrial Gases. Consolidation is not new within industrial gases. But the latest deal in this area, the $82 billion merger between the Linde Group and Praxair Technology, is truly transformative—because it will leave only three other sizable global players in the industry. We expect that regulators will demand more divestures out of the Linde/Praxair deal, creating opportunities for smaller industrial gas players and PE firms. Already, Taiyo has agreed to buy $6 billion of Praxair assets in Europe that will help it compete head-on with industry leaders such as Linde and Air Liquide.
Agrochemicals and Crop Protection. Years of strong competition and dynamic M&A activity have left just five key players in the industry. The battle among industry giants such as Bayer, ChemChina, and BASF has been fierce, and given the already consolidated state of the industry, any further M&A activity involving the top five companies is likely to face significant regulatory hurdles.
Paints and Coatings. This industry is dominated by several large players including PPG Industries and The Sherwin-Williams Company, yet there are still several regional paint players such as Kansai Paint and Asian Paints. So, although the level of consolidation is already high, we believe there will be plenty of midsize M&A deals in the years to come.
Flavors and Fragrances. Although the top five players control almost 45% of the market, this space is quite fragmented, leaving room for consolidation. In particular, we believe that leading players in mature markets will look for targets among the many small regional players in emerging markets. This has already started to happen: International Flavors & Fragrances acquired Frutarom, and Givaudan scooped up Naturex (specifically targeting its natural-ingredient business).
Other M&A Drivers
Motivations apart from consolidation contribute to M&A activity and have a significant influence on market dynamics.
Diversification. This is the second most powerful M&A motivator, which makes sense given the importance of opening up new revenue streams and diluting concentration risk. Diversification is particularly attractive for multispecialty players that aim to gain by adding customers and end industries.
Over the years, players such as Dow Chemical, DuPont, BASF, DSM, and Solvay have pursued M&A deals to diversify their end industry exposure. But companies must carefully balance their diversification and consolidation goals. (See Exhibit 3.) However, by no means do portfolio diversification and market consolidation contradict each other. Portfolio diversification is intended to expand a company's exposure to new end industries or new customers whereas segment consolidation is deployed to increase market share within the select few segments in which the player sees the highest value.
Access to Feedstock. Another popular and sensible reason for M&A, gaining access to feedstock allows a company to protect a competitive position and prepare for possible shortages of critical raw materials. This rationale is prevalent in the base-chemical segment. A prime example is Ineos, which acquired multiple upstream oil and gas assets in the North Sea in order to integrate them into its downstream businesses.
PE Investment. Over the past 20 years, some PE players have developed a deep understanding of chemical assets. That insight, along with their appetite for deals, makes them a force to be reckoned with. Amid the financial crisis in 2009, only 2% of chemical M&A deals were led by PE firms. But much has changed since then. In 2017, 11% of all M&A deal volume in chemicals was led by PE firms, and we expect that momentum to carry forward with another strong year in 2018. By mid-2018, PE players accounted for about 20% of deals including the biggest of the year, Carlyle Group's $12.6 billion acquisition of AkzoNobel's specialty-chemical business. Some global PE players in chemicals (such as Carlyle, Arsenal Capital Partners, and Apollo Global Management) focus on the Americas, while others (such as Advent) focus on mainland Europe.
Historically, PE players have tended to shy away from emerging markets, preferring targets in mature markets.
However, strong growth in emerging markets, an improved regulatory environment, and a stable growth outlook are turning the tide. (See Exhibit 4.) PE players usually hunt for independent assets that are easier to value, manage, and, ultimately, sell. And because PE firms' participation generally raises few if any regulatory or antitrust concerns, they often enjoy a built-in advantage over strategic buyers.
Asian Competitors. These newly assertive firms are pursuing outbound deals to globalize their footprint and broaden their portfolios. From 2002 through 2006, outbound deals made up just 2% of total global activity; in the period from 2012 through 2017, that share jumped to nearly 7%.
Historically, Chinese firms have looked at players in China or Southeast Asia as acquisition targets. But this changed in the last ten years: Chinese chemical companies, including state-owned enterprises, are now approaching targets in Europe and the Americas to access key technologies and IP and to establish themselves as global players. ChemChina's emergence on a global scale with its acquisition of Syngenta and Sabic's investment in Clariant point to a trend that will heat up in the years ahead.
Roadblocks to M&A
The environment for chemical industry M&A activity is quite favorable. The global economy is chugging along, interest rates are still low, and many companies have cash on hand. Moreover, pursuing focus through acquisitions is a well-grounded strategy with a track record of positive returns for shareholders; in other words, it is a strategy that executives can explain clearly to stakeholders and pursue with confidence.
But companies must navigate some formidable roadblocks as they pursue the M&A strategy. Low interest rates are contributing to high valuations, making acquisitions quite expensive. Political tensions, most notably the trade situations involving the US, Europe, and China, must be considered. To varying degrees, import tariffs affect the ways in which chemical companies conduct business and thus their attractiveness as M&A targets.
Another challenge comes from the increased regulatory scrutiny of deals. The uptick in consolidation within certain chemical segments has made antitrust regulators cautious about approving large M&A deals for fear of monopolies that could hurt customers and consumers. As a result, several megadeals have been pending for almost two years. Indeed, almost all the most historically active acquirers—Bayer, Dow, Monsanto, Praxair, ChemChina, DuPont, Linde, and more—are bogged down in regulatory discussions.
This delay in approvals is getting more acute. In 2015, at the recent peak in M&A activity, 17% of deal volume announced during the year was left pending at year end. Pending volume jumped to 45% in 2016 and then 50% in 2017. With companies struggling to finalize deals, new activity has been subdued, especially the most ambitious megadeals (which are predominantly consolidation deals). No deal greater than $10 billion was announced in 2017 and just one appeared by midyear in 2018 (the Carlyle Group/AkzoNobel deal).
Be an Active Player
As consolidation continues to remake the chemical industry, companies need to hone their M&A capabilities, sharpen their outlook, and work through roadblocks to make certain they can be proactive and remain competitive in a very dynamic environment. To this end, we have defined six recommendations for active M&A players:
Set reasonable downstream goals. Executives need to realistically assess how many end industries their company should play in. Companies that get too broad run the risk of losing focus and not getting deep enough in terms of customer centricity in all the industries.
Continually pursue business "fit." Maintain a fresh, unsentimental perspective on the business. Regularly analyze business units and assets. Identify those areas of the business that are no longer a good fit (and perhaps never were) and that other players, including private equity, might like to acquire. It is also important for players to connect and follow competitor moves and assess their own business performance on a continual basis.
Scan for threats and opportunities. Proactively monitor trends and the competitive landscape to understand what is happening not only in adjacent markets but also in downstream markets to spot threats and opportunities from competitors. Be open to acquisitions to specialize operations and deepen capabilities. This will require institutionalizing processes to screen targets regularly.
Be opportunistic. Sometimes the best opportunities are the ones you aren't expecting, but if you can pivot quickly to consider them, especially at a time when regulators are likely to force a sale, you could score a good deal. For example, in April, BASF agreed to acquire seed and crop protection assets from Bayer valued at €1.7 billion as Bayer sought antitrust approval for its acquisition of Monsanto (which it finally won in May). BASF's purchase came after it had already agreed to purchase €5.9 billion in Bayer assets in October 2017. Similar opportunities are expected to arise from the Linde/Praxair deal.
Be flexible with M&A structures. The regulatory dynamic is likely to yield more complex agreements between regulators and acquirers—with carve-outs, asset sharing, asset swaps, and joint ventures—creating more M&A opportunities, albeit perhaps less conventional opportunities. Remain open to these deal structures to make full use of available opportunities. For example, both BASF (in 2017) and Clariant (in 2014) divested their leather chemical businesses to Stahl Holdings in exchange for cash plus a minority stake in the company—making Stahl the global market leader in leather chemicals. Meanwhile, the merger of Dow and DuPont required the divestment of crop protection businesses that resulted in an asset swap with FMC's health and nutrition business in 2017.
Don't break what you buy. Institutionalize your integration processes so that each acquisition is fairly assessed and integrated correctly. That doesn't mean each acquisition is integrated in an identical way. Sometimes it's best to keep the target's business model operating in parallel with the incumbent's business model. This is especially likely in downstream businesses where models are tailored to meet the demands of an end industry or segment. Trying to completely integrate a downstream business model could easily destroy value.
Put the Future in Focus
Chemical companies need an active M&A strategy that is tuned to sense new business opportunities around the globe. This has never been more important, as the trend toward consolidation and deeper specialization to serve fewer end industries and chemical segments gathers strength and as companies involved in megadeals will increasingly spin off assets to gain regulatory approval.
Companies that want to leverage these trends for their own advantage will need to compete not only with other industry players but with a very active and expert PE community. Though the competition will be intense—and regulatory and political issues will invariably make structuring deals complex—companies can position themselves for long-term success by institutionalizing an M&A strategy and honing their expertise.
Andreas Gocke
Managing Director & Senior Partner
Hubert Schönberger
Senior Knowledge Expert
Philipp Jostarndt
Managing Director & Partner
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text:
Sandra Friedli (born 25 October 1974) is a Swiss slalom canoeist who competed from the early 1990s to the early 2000s (decade).

She won a bronze medal in the K1 event at the 1999 ICF Canoe Slalom World Championships in La Seu d'Urgell and also at the 1998 European Championships in Roudnice nad Labem.

Friedli also competed in two Summer Olympics, earning her best finish of ninth in the K1 event in Sydney in 2000.

World Cup individual podiums

References

Sports-reference.com profile

1974 births
Canoeists at the 1996 Summer Olympics
Canoeists at the 2000 Summer Olympics
Living people
Olympic canoeists of Switzerland
Swiss female canoeists
Medalists at the ICF Canoe Slalom World Championships

redpajama_set_name: RedPajamaWikipedia


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The technological world we live in helps make our lives easier. For example, companies can be run by a distributed workforce from all corners of America, meetings incorporate high definition video calls, and marketing software can automate a week's worth of messages with a few clicks.
In the past, crowdfunding has been used offline by politicians all the way to school bake sales. The goal was simple: raise capital for your cause, no matter what it is. Today, like many of our other processes, crowdfunding has adapted well to online use.
Beyond that, it's become a staple of success for modern fundraising strategies. However, you can't simply create a campaign page, set it, forget it, and expect donations to roll in. Like any fundraising campaign, there's a fair amount of work and strategy behind a successful crowdfunding campaign.
To help, we outline some tips and tactics below to ensure you get the most out of your next campaign. Keep these in mind as you work through your next crowdfunding initiative to build an engaging page and drive donations for your mission.
Who will we market this campaign to?
What does our average donor look like?
Who typically engages with our fundraising campaigns?
Do we have more success on certain channels, like email over social media?
Are there demographics we haven't appealed to before that might like this campaign?
It can be difficult to gather insights like this around your audience, especially if you've never segmented your supporters before, but the benefits are worth it. For example, if you identify a large group of supporters who frequently donate to your nonprofit, you know they care about your nonprofit.
You can consider soft-launching a crowdfunding campaign to this group of frequent donors, who are likely to make a gift. Not only does this targeted appeal resonate with them, it also establishes early momentum and social proof for your campaign before general release to the public.
It's important to drill down into your audience because blanketed mass appeals don't typically generate the same results as their hyper-targeted counterparts. That is, if you're blindly sending emails to a segment of your audience that responds to direct mail they may not donate at all because they're unaware of your campaign.
You shouldn't choose an online fundraising platform blindly because a platform alone won't drive traffic to your page. The place you choose to host your crowdfunding campaign should, without question, match the needs of your nonprofit.
Remember, a campaign's success is driven by your staff, powered by your supporters, and guided by your fundraising and marketing strategy. Focus on what your team needs and wants.
For example, if you have a limited staff you may need to consider a fundraising option that minimizes time in-product. Likewise, you might want establish that consistent branding, ways to showcase impact, and donor experience are important to your organization. Then, let that steer your ship.
It's better to go with a platform you and your staff trust can help you achieve your fundraising goals. From there, you can comfortably take the time to create great elements, stories, photos, and videos to populate the page and drive donations.
When it comes to empowering your donors, there are a few things you should remember. First and foremost, you need to guide people from discovery of the campaign, through exploration of your mission, to completion of a donation.
When someone donates to your crowdfunding campaign, they're saying that your cause is important to them. So, help your donors spread the word that they're making a difference.
Consider sending them special resources in follow up emails after their donation is complete. For example, you might include custom social media profile photos or an easy-to-digest version of your nonprofit's story.
What's important here is that you help them feel proud of their donation, so they can spread word of your nonprofit, mission, and campaign to their friends, family, coworkers, and beyond. This also goes a long way toward stewarding them to return for future campaigns.
A completed donation shouldn't be the end: look at it as the beginning of a long-term relationship. Seize the opportunity to interact with them, learn more about them, and keep them engaged with your work for years to come.
Peer-to-peer fundraising is a specific type of crowdfunding that your nonprofit can use which allows supporters to align with your cause in personalized ways. You still create a main campaign page, but individuals who land on your page can either donate or create a personal fundraising page.
Through this page, they can express a direct connection to your mission, promote it to their direct networks, and raise money on behalf of your organization. What's more, peer-to-peer fundraisers can raise more money for your nonprofit than they could donate out of their pockets.
On average, a typical one-time donor on Classy makes a gift of $120. Peer-to-peer fundraisers, however, raise an average of $559 through their personal fundraising pages: that's 365% higher.
In addition to the financial return, peer-to-peer fundraisers have the potential to bring in entirely new audiences of supporter due to their self-promotion of your mission. In fact, in a recent survey Classy conducted, we found that 46% of respondents choose to donate to a cause if a family member or friend asks them to.
After all this, it's important to understand that you may not reach your ultimate fundraising goal. However, that's not a bad thing: fail fast, fail forward, and carry your learnings into your next fundraising campaign with you.
Success doesn't happen overnight, and it could take your organization a while to build a crowdfunding engine that engages supporters, elicits donations, and stewards donors into future campaigns. Be patient, and before you know it you'll be a pro.
As you go through your crowdfunding campaign, take time with your team to plan, lay out a robust strategy, and create thoughtful content that speaks to your audience. If you'd like to dig into even more details around crowdfunding, make sure to download the guide below, The Anatomy of a Successful Crowdfunding Campaign.


I love the creative process of decorating a room, but find that I frequently fail at it before I finally succeed in getting the right look. Although it can be frustrating, I've found that the results are well worth the challenge because space that's livable is also lovable.
I've always been a fan of found objects and mixing old with new. I'm appreciative of color and design but I also tend to gravitate toward furnishings and details that have a well-loved and worn look and especially pieces that will lend character to an otherwise bland environment. I'm a huge fan of modular pieces that can be easily moved to change up the look of a room and I adore the use of natural objects and artwork used to create texture and evoke mood.
I may find a washed out blue trunk at a thrift or antique store that I want to use at the end of the bed for a table. I can put seashells or a hurricane lamp and choose white linens with accent pillows for a pop of color.
Prepare to hunt: If your budget is tight, think about where you are going to splurge and where you are going to skimp. Sometimes I will find a piece that makes the statement and blows the budget all at the same time. If this happens, it's not about forgoing the piece, but about getting creative with the rest of the room at thrift stores, yard sales, craigs list, or Ikea! Ikea is a great place to look for an element that achieves a look without breaking the bank.
Two Ikea Bunkbeds have been placed end to end to create this great look and take up very little floor space while maximizing the space for sleeping four.
Give yourself permission to get it right: We don't know till we try. If you have an idea or a vision in your head, then go with it. If you get it wrong the first few times, keep going till you get it right. When it comes to decorating a space there are no set rules, and we only gain experience when we make mistakes. It's ok if that piece you thought would work is a bust, maybe it will work somewhere else, maybe you resell it and begin again. Sometimes consignment stores will give you the opportunity to test a piece in your home to see if it works in the space. Obviously you will need to do your best by taking measurements and even "taping off" the amount of space each piece will take up in the room before actually going to the trouble to bring it home.
Make it: If you can't find that lamp or accent chair you are looking for... can you make it? Marshalls or TJ's are great places to look for the basics. Consider how many white lamps or tables you can find at either place. Can you decopage some tasteful seashell images on it's surface to achieve your look?
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