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» The Moving Target Function Problem in Multi-Agent Learning
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AAAI
2012
11 years 10 months ago
Transfer Learning with Graph Co-Regularization
Transfer learning proves to be effective for leveraging labeled data in the source domain to build an accurate classifier in the target domain. The basic assumption behind transf...
Mingsheng Long, Jianmin Wang 0001, Guiguang Ding, ...
AROBOTS
2002
130views more  AROBOTS 2002»
13 years 7 months ago
Dynamic Motion Planning for Mobile Robots Using Potential Field Method
The potential field method is widely used for autonomous mobile robot path planning due to its elegant mathematical analysis and simplicity. However, most researches have been focu...
Shuzhi Sam Ge, Youjing Cui
ALT
2006
Springer
14 years 4 months ago
Active Learning in the Non-realizable Case
Most of the existing active learning algorithms are based on the realizability assumption: The learner’s hypothesis class is assumed to contain a target function that perfectly c...
Matti Kääriäinen
SBRN
2008
IEEE
14 years 2 months ago
Imitation Learning of an Intelligent Navigation System for Mobile Robots Using Reservoir Computing
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which mus...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...
IJCAI
2007
13 years 9 months ago
Concept Sampling: Towards Systematic Selection in Large-Scale Mixed Concepts in Machine Learning
This paper addresses the problem of concept sampling. In many real-world applications, a large collection of mixed concepts is available for decision making. However, the collecti...
Yi Zhang 0010, Xiaoming Jin