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ICML
2009
IEEE
16 years 7 months ago
Near-Bayesian exploration in polynomial time
We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to this problem, by considering...
J. Zico Kolter, Andrew Y. Ng
ICML
2009
IEEE
16 years 7 months ago
Sparse Gaussian graphical models with unknown block structure
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...
Benjamin M. Marlin, Kevin P. Murphy
ICML
2009
IEEE
16 years 7 months ago
Efficient Euclidean projections in linear time
We consider the problem of computing the Euclidean projection of a vector of length n onto a closed convex set including the 1 ball and the specialized polyhedra employed in (Shal...
Jun Liu, Jieping Ye
ICML
2009
IEEE
16 years 7 months ago
Matrix updates for perceptron training of continuous density hidden Markov models
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
ICML
2007
IEEE
16 years 7 months ago
Dynamic hierarchical Markov random fields and their application to web data extraction
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen