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UAI
2000
13 years 8 months ago
Tractable Bayesian Learning of Tree Belief Networks
In this paper we present decomposable priors, a family of priors over structure and parameters of tree belief nets for which Bayesian learning with complete observations is tracta...
Marina Meila, Tommi Jaakkola
ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 7 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
STOC
2010
ACM
193views Algorithms» more  STOC 2010»
14 years 8 days ago
Maintaining a large matching and a small vertex cover
We consider the problem of maintaining a large matching and a small vertex cover in a dynamically changing graph. Each update to the graph is either an edge deletion or an edge in...
Krzysztof Onak, Ronitt Rubinfeld
ISAAC
2009
Springer
169views Algorithms» more  ISAAC 2009»
14 years 2 months ago
The Complexity of Solving Stochastic Games on Graphs
We consider some well-known families of two-player zero-sum perfect-information stochastic games played on finite directed graphs. Generalizing and unifying results of Liggett and...
Daniel Andersson, Peter Bro Miltersen
ICML
2008
IEEE
14 years 8 months ago
Graph kernels between point clouds
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
Francis R. Bach