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» Speeding Up Evolution through Learning: LEM
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IUI
2000
ACM
14 years 2 months ago
Expression constraints in multimodal human-computer interaction
Thanks to recent scientific advances, it is now possible to design multimodal interfaces allowing the use of speech and pointing out gestures on a touchscreen. However, present sp...
Sandrine Robbe-Reiter, Noelle Carbonell, Pierre Da...
ICMLA
2003
13 years 11 months ago
Reinforcement Learning Task Clustering
This work represents the first step towards a task library system in the reinforcement learning domain. Task libraries could be useful in speeding up the learning of new tasks th...
James L. Carroll, Todd S. Peterson, Kevin D. Seppi
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
14 years 3 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
ECAI
2010
Springer
13 years 10 months ago
Learning When to Use Lazy Learning in Constraint Solving
Abstract. Learning in the context of constraint solving is a technique by which previously unknown constraints are uncovered during search and used to speed up subsequent search. R...
Ian P. Gent, Christopher Jefferson, Lars Kotthoff,...
WWW
2008
ACM
14 years 10 months ago
Floatcascade learning for fast imbalanced web mining
This paper is concerned with the problem of Imbalanced Classification (IC) in web mining, which often arises on the web due to the "Matthew Effect". As web IC applicatio...
Xiaoxun Zhang, Xueying Wang, Honglei Guo, Zhili Gu...