Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can b...
General dissimilarity-based learning approaches have been proposed for dissimilarity data sets [11, 10]. They arise in problems in which direct comparisons of objects are made, e....
Background: Hidden Markov Models (HMMs) provide an excellent means for structure identification and feature extraction on stochastic sequential data. An HMM-with-Duration (HMMwD) ...
The goal of this paper is to describe a new approach to a content creation and delivery mechanism for a programming course. This approach is based on the concept of creating a lar...
Recovering the pose of a person from single images is a challenging problem. This paper discusses a bottom-up approach that uses local image features to estimate human upper body p...