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ICML
2007
IEEE
16 years 7 months ago
A kernel path algorithm for support vector machines
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky
GECCO
2009
Springer
16 years 22 days ago
On the scalability of XCS(F)
Many successful applications have proven the potential of Learning Classifier Systems and the XCS classifier system in particular in datamining, reinforcement learning, and func...
Patrick O. Stalph, Martin V. Butz, David E. Goldbe...
CVPR
2007
IEEE
16 years 8 months ago
An Exemplar Model for Learning Object Classes
We introduce an exemplar model that can learn and generate a region of interest around class instances in a training set, given only a set of images containing the visual class. T...
Ondrej Chum, Andrew Zisserman
AAAI
1998
15 years 7 months ago
Applying Online Search Techniques to Continuous-State Reinforcement Learning
In this paper, we describe methods for e ciently computing better solutions to control problems in continuous state spaces. We provide algorithms that exploit online search to boo...
Scott Davies, Andrew Y. Ng, Andrew W. Moore
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
15 years 4 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup