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» A Spectral Algorithm for Learning Hidden Markov Models
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TOIS
2010
128views more  TOIS 2010»
13 years 6 months ago
Learning author-topic models from text corpora
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...
INFOCOM
2012
IEEE
11 years 10 months ago
Approximately optimal adaptive learning in opportunistic spectrum access
—In this paper we develop an adaptive learning algorithm which is approximately optimal for an opportunistic spectrum access (OSA) problem with polynomial complexity. In this OSA...
Cem Tekin, Mingyan Liu
ACCV
2006
Springer
14 years 1 months ago
Tracking Targets Via Particle Based Belief Propagation
We first formulate multiple targets tracking problem in a dynamic Markov network(DMN)which is derived from a MRFs for joint target state and a binary process for occlusion of dual...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
WSC
2008
13 years 10 months ago
On step sizes, stochastic shortest paths, and survival probabilities in Reinforcement Learning
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
Abhijit Gosavi
BMCBI
2007
98views more  BMCBI 2007»
13 years 7 months ago
Duration learning for analysis of nanopore ionic current blockades
Background: Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties, with potential implications ...
Alexander G. Churbanov, Carl Baribault, Stephen Wi...