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» Learning Markov Network Structure with Decision Trees
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DAWAK
2006
Springer
15 years 1 months ago
Mixed Decision Trees: An Evolutionary Approach
In the paper, a new evolutionary algorithm (EA) for mixed tree learning is proposed. In non-terminal nodes of a mixed decision tree different types of tests can be placed, ranging ...
Marek Kretowski, Marek Grzes
IJCAI
1993
14 years 10 months ago
Learning Decision Lists over Tree Patterns and Its Application
This paper introduces a new concept, a decision tree (or list) over tree patterns, which is a natural extension of a decision tree (or decision list), for dealing with tree struct...
Satoshi Kobayashi, Koichi Hori, Setsuo Ohsuga
ICML
2007
IEEE
15 years 10 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney
83
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COLT
2001
Springer
15 years 2 months ago
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we ...
Peter L. Bartlett, Shahar Mendelson
IJCAI
2007
14 years 11 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup