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ICPR
2008
IEEE
14 years 1 months ago
Transductive optimal component analysis
We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
Yuhua Zhu, Yiming Wu, Xiuwen Liu, Washington Mio
ICML
1995
IEEE
14 years 7 months ago
Residual Algorithms: Reinforcement Learning with Function Approximation
A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that ...
Leemon C. Baird III
ML
2007
ACM
104views Machine Learning» more  ML 2007»
13 years 6 months ago
A general criterion and an algorithmic framework for learning in multi-agent systems
We offer a new formal criterion for agent-centric learning in multi-agent systems, that is, learning that maximizes one’s rewards in the presence of other agents who might also...
Rob Powers, Yoav Shoham, Thuc Vu
FLAIRS
1998
13 years 8 months ago
Optimizing Production Manufacturing Using Reinforcement Learning
Manyindustrial processes involve makingparts with an assemblyof machines, where each machinecarries out an operation on a part, and the finished product requires a wholeseries of ...
Sridhar Mahadevan, Georgios Theocharous
ILP
1997
Springer
13 years 11 months ago
A Logical Framework for Graph Theoretical Decision Tree Learning
Abstract. We present a logical approach to graph theoretical learning that is based on using alphabetic substitutions for modelling graph morphisms. A classi ed graph is represente...
Peter Geibel, Fritz Wysotzki