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» Reinforcement Learning with Time
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ICML
2008
IEEE
16 years 7 months ago
Modeling interleaved hidden processes
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Niels Landwehr
ICML
2006
IEEE
16 years 7 months ago
Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution
The Dirichlet compound multinomial (DCM) distribution, also called the multivariate Polya distribution, is a model for text documents that takes into account burstiness: the fact ...
Charles Elkan
199
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ICML
2006
IEEE
16 years 7 months ago
Fast direct policy evaluation using multiscale analysis of Markov diffusion processes
Policy evaluation is a critical step in the approximate solution of large Markov decision processes (MDPs), typically requiring O(|S|3 ) to directly solve the Bellman system of |S...
Mauro Maggioni, Sridhar Mahadevan
ICML
2006
IEEE
16 years 7 months ago
Efficient inference on sequence segmentation models
Sequence segmentation is a flexible and highly accurate mechanism for modeling several applications. Inference on segmentation models involves dynamic programming computations tha...
Sunita Sarawagi
ICML
2004
IEEE
16 years 7 months ago
A maximum entropy approach to species distribution modeling
We study the problem of modeling species geographic distributions, a critical problem in conservation biology. We propose the use of maximum-entropy techniques for this problem, s...
Miroslav Dudík, Robert E. Schapire, Steven ...