We investigate incremental word learning with few training examples in a Hidden Markov Model (HMM) framework suitable for an interactive learning scenario with little prior knowle...
Discriminative learning techniques for sequential data have proven to be more effective than generative models for named entity recognition, information extraction, and other task...
Abstract. We describe a Markov chain Monte Carlo based particle filter that effectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or be...
We develop a general framework to automatically match electronic slides to the videos of corresponding presentations. Applications include supporting indexing and browsing of educ...
—Accurate and timely detection of infectious disease outbreaks provides valuable information which can enable public health officials to respond to major public health threats in...