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» Gaussian Processes in Reinforcement Learning
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ML
2002
ACM
220views Machine Learning» more  ML 2002»
13 years 9 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
EOR
2007
165views more  EOR 2007»
13 years 9 months ago
Adaptive credit scoring with kernel learning methods
Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Yingxu Yang
WWW
2010
ACM
14 years 4 months ago
iRIN: image retrieval in image-rich information networks
In this demo, we present a system called iRIN designed for performing image retrieval in image-rich information networks. We first introduce MoK-SimRank to significantly improve...
Xin Jin, Jiebo Luo, Jie Yu, Gang Wang, Dhiraj Josh...
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
14 years 1 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
AAAI
2010
13 years 11 months ago
Towards Multiagent Meta-level Control
Embedded systems consisting of collaborating agents capable of interacting with their environment are becoming ubiquitous. It is crucial for these systems to be able to adapt to t...
Shanjun Cheng, Anita Raja, Victor R. Lesser