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» Termination Analysis with Algorithmic Learning
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130
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JMLR
2006
131views more  JMLR 2006»
15 years 3 months ago
Incremental Support Vector Learning: Analysis, Implementation and Applications
Incremental Support Vector Machines (SVM) are instrumental in practical applications of online learning. This work focuses on the design and analysis of efficient incremental SVM ...
Pavel Laskov, Christian Gehl, Stefan Krüger, ...
ICML
2009
IEEE
16 years 4 months ago
Model-free reinforcement learning as mixture learning
We cast model-free reinforcement learning as the problem of maximizing the likelihood of a probabilistic mixture model via sampling, addressing both the infinite and finite horizo...
Nikos Vlassis, Marc Toussaint
CIMCA
2005
IEEE
15 years 9 months ago
An Accelerating Learning Algorithm for Block-Diagonal Recurrent Neural Networks
An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to...
Paris A. Mastorocostas, Dimitris N. Varsamis, Cons...
137
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PAMI
2010
276views more  PAMI 2010»
15 years 1 months ago
Local-Learning-Based Feature Selection for High-Dimensional Data Analysis
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
Yijun Sun, Sinisa Todorovic, Steve Goodison
ICML
1995
IEEE
16 years 4 months ago
Residual Algorithms: Reinforcement Learning with Function Approximation
A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that ...
Leemon C. Baird III