995 search results - page 59 / 199 » Learning Useful Horn Approximations |
134
Voted
ICML
2002
IEEE
16 years 4 months ago
2002
IEEE
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
147
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KDD
2008
ACM
16 years 4 months ago
2008
ACM
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. It has been applied successfully to capture highord...
140
Voted
NIPS
2004
15 years 5 months ago
2004
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
131
Voted
ML
2008
ACM
15 years 3 months ago
2008
ACM
Abstract. We consider a large volume principle for transductive learning that prioritizes the transductive equivalence classes according to the volume they occupy in hypothesis spa...
172
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ML
2012
ACM
13 years 11 months ago
2012
ACM
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...