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UAI
2001
15 years 3 months ago
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning
There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
Lex Weaver, Nigel Tao
CVPR
2007
IEEE
16 years 3 months ago
Adaptive Distance Metric Learning for Clustering
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
Jieping Ye, Zheng Zhao, Huan Liu
COLT
2008
Springer
15 years 3 months ago
On the Power of Membership Queries in Agnostic Learning
We study the properties of the agnostic learning framework of Haussler [Hau92] and Kearns, Schapire and Sellie [KSS94]. In particular, we address the question: is there any situat...
Vitaly Feldman
JIRS
2000
133views more  JIRS 2000»
15 years 1 months ago
Managing Complexity in Large Learning Robotic Systems
Abstract. Autonomous learning systems of significant complexity often consist of several interacting modules or agents. These modules collaborate to produce a system which, when vi...
Kynan Eng, Alec P. Robertson, Deane R. Blackman
NECO
1998
168views more  NECO 1998»
15 years 1 months ago
Constructive Incremental Learning from Only Local Information
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, t...
Stefan Schaal, Christopher G. Atkeson