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124
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NN
2010
Springer
125views Neural Networks» more  NN 2010»
15 years 1 months ago
Parameter-exploring policy gradients
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
Frank Sehnke, Christian Osendorfer, Thomas Rü...
119
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GECCO
2007
Springer
195views Optimization» more  GECCO 2007»
15 years 8 months ago
MILCS: a mutual information learning classifier system
This paper introduces a new variety of learning classifier system (LCS), called MILCS, which utilizes mutual information as fitness feedback. Unlike most LCSs, MILCS is specifical...
Robert Elliott Smith, Max Kun Jiang
136
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CIKM
2011
Springer
14 years 2 months ago
Content based social behavior prediction: a multi-task learning approach
The study of information flow analyzes the principles and mechanisms of social information distribution. It is becoming an extremely important research topic in social network re...
Hongliang Fei, Ruoyi Jiang, Yuhao Yang, Bo Luo, Ju...
97
Voted
CIKM
2000
Springer
15 years 7 months ago
Relevance and Reinforcement in Interactive Browsing
We consider the problem of browsing the top ranked portion of the documents returned by an information retrieval system. We describe an interactive relevance feedback agent that a...
Anton Leuski
114
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IJCNN
2006
IEEE
15 years 8 months ago
On derivation of stagewise second-order backpropagation by invariant imbedding for multi-stage neural-network learning
— We present a simple, intuitive argument based on “invariant imbedding” in the spirit of dynamic programming to derive a stagewise second-order backpropagation (BP) algorith...
Eiji Mizutani, Stuart Dreyfus