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» A New Way to Introduce Knowledge into Reinforcement Learning
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AAAI
2004
15 years 1 months ago
Conservative Belief Revision
A standard intuition underlying traditional accounts of belief change is the principle of minimal change. In this paper we introduce a novel account of belief change in which the ...
James P. Delgrande, Abhaya C. Nayak, Maurice Pagnu...
BMCBI
2008
132views more  BMCBI 2008»
14 years 12 months ago
Clustering ionic flow blockade toggles with a Mixture of HMMs
Background: Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties with potential implications f...
Alexander G. Churbanov, Stephen Winters-Hilt
ECCV
2002
Springer
16 years 1 months ago
Probabilistic Search for Object Segmentation and Recognition
Abstract. The problem of searching for a model-based scene interpretation is analyzed within a probabilistic framework. Object models are formulated as generative models for range ...
Ulrich Hillenbrand, Gerd Hirzinger
INFORMATICASI
1998
122views more  INFORMATICASI 1998»
14 years 11 months ago
Experimental Evaluation of Three Partition Selection Criteria for Decision Table Decomposition
Decision table decomposition is a machine learning approach that decomposes a given decision table into an equivalent hierarchy of decision tables. The approach aims to discover d...
Blaz Zupan, Marko Bohanec
CORR
2011
Springer
127views Education» more  CORR 2011»
14 years 3 months ago
Generalized Boosting Algorithms for Convex Optimization
Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks,...
Alexander Grubb, J. Andrew Bagnell