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» Algorithm Selection using Reinforcement Learning
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ICPR
2006
IEEE
16 years 3 months ago
Feature selection based on the training set manipulation
A novel filter feature selection technique is introduced. The method exploits the information conveyed by the evolution of the training samples weights similarly to the Adaboost a...
Pavel Krízek, Josef Kittler, Václav ...
106
Voted
IROS
2009
IEEE
150views Robotics» more  IROS 2009»
15 years 9 months ago
Learning locomotion over rough terrain using terrain templates
— We address the problem of foothold selection in robotic legged locomotion over very rough terrain. The difficulty of the problem we address here is comparable to that of human...
Mrinal Kalakrishnan, Jonas Buchli, Peter Pastor, S...
186
Voted
ACMICEC
2007
ACM
117views ECommerce» more  ACMICEC 2007»
15 years 6 months ago
Selectively acquiring ratings for product recommendation
Accurate prediction of customer preferences on products is the key to any recommender systems to realize its promised strategic values such as improved customer satisfaction and t...
Zan Huang
139
Voted
AIIDE
2007
15 years 5 months ago
Automatic Rule Ordering for Dynamic Scripting
The goal of adaptive game AI is to enhance computercontrolled game-playing agents with (1) the ability to selfcorrect mistakes, and (2) creativity in responding to new situations....
Timor Timuri, Pieter Spronck, H. Jaap van den Heri...
118
Voted
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 8 months ago
Is negative selection appropriate for anomaly detection?
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...