3694 search results - page 330 / 739 » Stochastic complexity in learning |
169
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EUROCAST
2007
Springer
16 years 25 days ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
159
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AGENTS
1999
Springer
15 years 11 months ago
1999
Springer
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
145
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ALT
2003
Springer
15 years 10 months ago
2003
Springer
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
200
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JMLR
2008
15 years 6 months ago
2008
The computational complexities arising in motor control can be ameliorated through the use of a library of motor synergies. We present a new model, referred to as the Greedy Addit...
208
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ECCV
2010
Springer
15 years 12 months ago
2010
Springer
The range space of dynamic textures spans spatiotemporal phenomena that vary along three fundamental dimensions: spatial texture, spatial texture layout, and dynamics. By describin...