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ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
ATAL
2009
Springer
13 years 5 months ago
2009
Springer
Today's society is largely connected and many real life applications lend themselves to be modeled as multi-agent systems. Although such systems as well as their models are d...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
UAI
2008
13 years 9 months ago
2008
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...