Learning communities from a graph is an important problem in many domains. Different types of communities can be generalized as link-pattern based communities. In this paper, we p...
Bo Long, Xiaoyun Xu, Zhongfei (Mark) Zhang, Philip...
Analyzing videos of human activities involves not only
recognizing actions (typically based on their appearances),
but also determining the story/plot of the video. The storyline...
Abhinav Gupta (University of Maryland), Praveen Sr...
This paper presents a novel framework for simultaneously learning representation and control in continuous Markov decision processes. Our approach builds on the framework of proto...
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
Abstract – In this paper, a variational message passing framework is proposed for Markov random fields. Analogous to the traditional belief propagation algorithm, variational mes...