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» Learning Rules for Adaptive Planning
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NIPS
2001
13 years 10 months ago
Learning Spike-Based Correlations and Conditional Probabilities in Silicon
We have designed and fabricated a VLSI synapse that can learn a conditional probability or correlation between spike-based inputs and feedback signals. The synapse is low power, c...
Aaron P. Shon, David Hsu, Chris Diorio
JMLR
2008
124views more  JMLR 2008»
13 years 8 months ago
Learning Control Knowledge for Forward Search Planning
A number of today's state-of-the-art planners are based on forward state-space search. The impressive performance can be attributed to progress in computing domain independen...
Sung Wook Yoon, Alan Fern, Robert Givan
ICCBR
2001
Springer
14 years 1 months ago
A Fuzzy-Rough Approach for Case Base Maintenance
Abstract. This paper proposes a fuzzy-rough method of maintaining CaseBased Reasoning (CBR) systems. The methodology is mainly based on the idea that a large case library can be tr...
Guoqing Cao, Simon C. K. Shiu, Xizhao Wang
ROCAI
2004
Springer
14 years 2 months ago
Learning Mixtures of Localized Rules by Maximizing the Area Under the ROC Curve
We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
Tobias Sing, Niko Beerenwinkel, Thomas Lengauer
ICML
2010
IEEE
13 years 10 months ago
Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
Tobias Lang, Marc Toussaint