title: ON THE USE OF CONVOLUTIONAL AUTO-ENCODER FOR INCREMENTAL CLASSIFIER LEARNING IN CONTEXT AWARE ADVERTISEMENT
abstract: Context Aware Advertisement (CAA) is a type of advertisement
  appearing on websites or mobile apps. The advertisement is targeted
  on specific group of users and/or the content displayed on the
  websites or apps. This paper focuses on classifying images displayed
  on the websites by incremental learning classifier with Deep
  Convolutional Neural Network (DCNN) especially for Context Aware
  Advertisement (CAA) framework. Incrementally learning new knowledge
  with DCNN leads to catastrophic forgetting as previously stored
  information is replaced with new information. To prevent
  catastrophic forgetting, part of previously learned knowledge should
  be stored for the life time of incremental classifier. Storing
  information for life time involves privacy and legal concerns
  especially in context aware advertising framework. Here, we propose
  an incremental classifier learning method which addresses privacy
  and legal concerns while taking care of catastrophic forgetting
  problem. We conduct experiments on different datasets including
  CIFAR-100. Experimental results show that proposed system achieves
  relatively high performance compared to the state-of-the-art
  incremental learning methods.
authors: Tin Lay Nwe Shudong Xie Balaji Nataraj Yiqun Li Joo-Hwee Lim
hIndex: Joo-Hwee Lim 30