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GECCO
2008
Springer
170views Optimization» more  GECCO 2008»
15 years 7 months ago
Evolving prediction weights using evolution strategy
The evolution strategy is one of the strongest evolutionary algorithms for optimizing real-value vectors. In this paper, we study how to use it for the evolution of prediction wei...
Trung Hau Tran, Cédric Sanza, Yves Duthen
IEICET
2007
114views more  IEICET 2007»
15 years 6 months ago
Analytic Optimization of Adaptive Ridge Parameters Based on Regularized Subspace Information Criterion
In order to obtain better learning results in supervised learning, it is important to choose model parameters appropriately. Model selection is usually carried out by preparing a ...
Shun Gokita, Masashi Sugiyama, Keisuke Sakurai
JAIR
2000
94views more  JAIR 2000»
15 years 6 months ago
Planning Graph as a (Dynamic) CSP: Exploiting EBL, DDB and other CSP Search Techniques in Graphplan
This paper reviews the connections between Graphplan's planning-graph and the dynamic constraint satisfaction problem and motivates the need for adapting CSP search technique...
Subbarao Kambhampati
ML
2002
ACM
145views Machine Learning» more  ML 2002»
15 years 6 months ago
Boosting Methods for Regression
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
Nigel Duffy, David P. Helmbold
NN
2007
Springer
105views Neural Networks» more  NN 2007»
15 years 6 months ago
Guiding exploration by pre-existing knowledge without modifying reward
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
Kary Främling