We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
This paper presents an evolutionary algorithm for modeling the arrival dates in time-stamped data sequences such as newscasts, e-mails, IRC conversations, scientific journal artic...
A new method for object tracking in video sequences is presented. This method exploits the benefits of particle filters to tackle the multimodal distributions emerging from clutte...
Alexandros Makris, Dimitrios I. Kosmopoulos, Stavr...
We formulate and study a new variant of the k-armed bandit problem, motivated by e-commerce applications. In our model, arms have (stochastic) lifetime after which they expire. In...
Deepayan Chakrabarti, Ravi Kumar, Filip Radlinski,...
In this paper we consider gossip-based Peer-to-Peer streaming applications where multiple sources exist and they work serially. More specifically, we tackle the problem of fast s...