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» Approximation Methods for Supervised Learning
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103
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ATAL
2009
Springer
15 years 7 months ago
An empirical analysis of value function-based and policy search reinforcement learning
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
Shivaram Kalyanakrishnan, Peter Stone
JMLR
2006
153views more  JMLR 2006»
15 years 19 days ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis
90
Voted
ICML
2008
IEEE
16 years 1 months ago
An RKHS for multi-view learning and manifold co-regularization
Inspired by co-training, many multi-view semi-supervised kernel methods implement the following idea: find a function in each of multiple Reproducing Kernel Hilbert Spaces (RKHSs)...
Vikas Sindhwani, David S. Rosenberg
EKAW
2008
Springer
15 years 2 months ago
Learning Disjointness for Debugging Mappings between Lightweight Ontologies
Abstract. Dealing with heterogeneous ontologies by means of semantic mappings has become an important area of research and a number of systems for discovering mappings between onto...
Christian Meilicke, Johanna Völker, Heiner St...
118
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DLOG
2007
15 years 3 months ago
Speeding up Approximation with Nicer Concepts
Abstract. Concept approximation is an inference service for Description Logics that provides “translations” of concept descriptions from one DL to a less expressive DL. In [4] ...
Anni-Yasmin Turhan, Yusri Bong