3694 search results - page 254 / 739 » Stochastic complexity in learning |
152
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ECAL
2005
Springer
15 years 11 months ago
2005
Springer
The complexity, variation, and change of human languages makes evident the importance of representation and learning in the acquisition and evolution of language. For example, anal...
175
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FOCS
2008
IEEE
16 years 14 days ago
2008
IEEE
We study the learnability of sets in Rn under the Gaussian distribution, taking Gaussian surface area as the “complexity measure” of the sets being learned. Let CS denote the ...
165
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ICML
2008
IEEE
16 years 6 months ago
2008
IEEE
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
149
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ICML
2001
IEEE
16 years 6 months ago
2001
IEEE
In this paper, we discuss a technique for handling multi-class problems with binary classifiers, namely to learn one classifier for each pair of classes. Although this idea is kno...
162
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ICML
2001
IEEE
16 years 6 months ago
2001
IEEE
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...