We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
A few models have appeared in recent years that consider not only the way substitutions occur through evolutionary history at each site of a genome, but also the way the process c...
This paper proposes a method for detecting object classes that exhibit variable shape structure in heavily cluttered images. The term "variable shape structure" is used t...
Jingbin Wang, Vassilis Athitsos, Stan Sclaroff, Ma...
In this paper, we propose a general two-dimensional hidden Markov model (2D-HMM), where dependency of the state transition probability on any state is allowed as long as causality...
One of the major limitations of HMM-based models is the inability to cope with topology: When applied to a visible observation (VO) sequence, HMM-based techniques have difficulty ...