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ICML
2009
IEEE
15 years 10 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
ICML
1999
IEEE
15 years 10 months ago
Implicit Imitation in Multiagent Reinforcement Learning
Imitation is actively being studied as an effective means of learning in multi-agent environments. It allows an agent to learn how to act well (perhaps optimally) by passively obs...
Bob Price, Craig Boutilier
AAAI
1994
14 years 11 months ago
Learning to Coordinate without Sharing Information
Researchers in the eld of Distributed Arti cial Intelligence (DAI) have been developing e cient mechanisms to coordinate the activities of multiple autonomous agents. The need for...
Sandip Sen, Mahendra Sekaran, John Hale
UAI
1996
14 years 11 months ago
Learning Bayesian Networks with Local Structure
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
Nir Friedman, Moisés Goldszmidt
IIE
2007
63views more  IIE 2007»
14 years 9 months ago
Investigation of Q-Learning in the Context of a Virtual Learning Environment
We investigate the possibility to apply a known machine learning algorithm of Q-learning in the domain of a Virtual Learning Environment (VLE). It is important in this problem doma...
Dalia Baziukaite