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» On a theory of learning with similarity functions
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PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
15 years 6 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
JCHE
2007
81views more  JCHE 2007»
14 years 11 months ago
Supporting Self-Organized Learning with Personal WebPublishing Technologies and Practices
I N THIS PAPER, we suggest that self-organized learning can be supported through emergent and informal Web technologies and propose that these technologies can be used to encourag...
Priya Sharma, Sebastian Fiedler
ICMCS
2006
IEEE
155views Multimedia» more  ICMCS 2006»
15 years 5 months ago
Region-Based Image Retrieval using Radial Basis Function Network
This paper presents a new framework that integrates relevance feedback into region-based image retrieval (RBIR) systems based on radial basis function network (RBFN). A modified u...
Kui Wu, Kim-Hui Yap, Lap-Pui Chau
NIPS
1996
15 years 1 months ago
Why did TD-Gammon Work?
Although TD-Gammon is one of the major successes in machine learning, it has not led to similar impressive breakthroughs in temporal difference learning for other applications or ...
Jordan B. Pollack, Alan D. Blair
ATAL
2005
Springer
15 years 5 months ago
Behavior transfer for value-function-based reinforcement learning
Temporal difference (TD) learning methods [22] have become popular reinforcement learning techniques in recent years. TD methods have had some experimental successes and have been...
Matthew E. Taylor, Peter Stone