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» Multiagent learning using a variable learning rate
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CP
2005
Springer
15 years 4 months ago
Evolving Variable-Ordering Heuristics for Constrained Optimisation
In this paper we present and evaluate an evolutionary approach for learning new constraint satisfaction algorithms, specifically for MAX-SAT optimisation problems. Our approach of...
Stuart Bain, John Thornton, Abdul Sattar
ML
1998
ACM
101views Machine Learning» more  ML 1998»
15 years 2 months ago
Elevator Group Control Using Multiple Reinforcement Learning Agents
Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithmshave appeared that approximatedynamic programming on an ...
Robert H. Crites, Andrew G. Barto
ICML
2008
IEEE
16 years 3 months ago
Bolasso: model consistent Lasso estimation through the bootstrap
We consider the least-square linear regression problem with regularization by the 1-norm, a problem usually referred to as the Lasso. In this paper, we present a detailed asymptot...
Francis R. Bach
JMLR
2010
132views more  JMLR 2010»
14 years 9 months ago
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mu...
IADIS
2004
15 years 3 months ago
Conceptualizing Student Learning Theory
The focus of this paper is on student learning theory. Use is made of an "analytic discovery tool" called Quantitative CyberQuest (QCQ) to help conceptualize the many go...
John Dickey, Richard Larkin