3250 search results - page 266 / 650 » Parameterized Learning Complexity |
178
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CIKM
2009
Springer
16 years 26 days ago
2009
Springer
Features in many real world applications such as Cheminformatics, Bioinformatics and Information Retrieval have complex internal structure. For example, frequent patterns mined fr...
165
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EUROCAST
2007
Springer
16 years 13 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...
150
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AGENTS
1999
Springer
15 years 10 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...
141
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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 ...
191
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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...