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» On Kernel Methods for Relational Learning
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129
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ML
1998
ACM
136views Machine Learning» more  ML 1998»
15 years 3 months ago
Co-Evolution in the Successful Learning of Backgammon Strategy
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
Jordan B. Pollack, Alan D. Blair
173
Voted

Publication
154views
14 years 6 months ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis
109
Voted
ICIP
2005
IEEE
16 years 5 months ago
Custom color enhancements by statistical learning
We consider the problem of automatically learning color enhancements from a small set of sample color pairs, and describing the enhancement by a three-dimensional look-uptable tha...
Maya R. Gupta
150
Voted
CISST
2004
164views Hardware» more  CISST 2004»
15 years 5 months ago
Probabilistic Region Relevance Learning for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Iker Gondra, Douglas R. Heisterkamp
109
Voted
ICPR
2010
IEEE
15 years 8 months ago
Lattice-Based Anomaly Rectification for Sport Video Annotation
Anomaly detection has received much attention within the literature as a means of determining, in an unsupervised manner, whether a learning domain has changed in a fundamental way...
Aftab Khan, David Windridge, Teofilo De Campos