In this paper we present a new method, time-striding hidden Markov model (TSHMM), to learn from long-term motion for atomic behaviors and the statistical dependencies among them. T...
A new large margin classifier, named MaxiMin Margin Machine (M4 ) is proposed in this paper. This new classifier is constructed based on both a "local" and a "globa...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
Support Vector Machines (SVMs) have successfully shown efficiencies in many areas such as text categorization. Although recommendation systems share many similarities with text ca...
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scen...