Sarah A Moody, Jean J Cabell, Tyler N Livingston, Yueran Yang
Evidence-based suspicion and the prior probability of guilt in police interrogations
Law and human behavior
paper revisit bounded component analysis bca formulate geometric problem finding minimum volume enclosing parallelotope mvep set data points euclidean space parallelotope affine transformation standard box also known lnorm ball immediate benefit novel formulation bounds supports latent components arbitrary unlike existing bca works assume bounds symmetric around zero main contribution mvep solution exactly recovers latent components inherent inconsequential permutation shift scaling ambiguities groundtruth components satisfy socalled sufficiently scattered condition standard box great improvement existing result requires vertices box contained data set requires exponentially many data points ica essentially requires infinite amount data points guarantee exact recovery also present new learning algorithm solve nphard mvep problem based frankwolfe show numerically performance surprisingly effective