3694 search results - page 359 / 739 » Stochastic complexity in learning |
184
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ECML
2006
Springer
15 years 10 months ago
2006
Springer
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
146
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GECCO
2006
Springer
15 years 10 months ago
2006
Springer
Learning goal-scoring behaviour from scratch for simulated robot soccer is considered to be a very difficult problem, and is often achieved by endowing players with an innate set ...
184
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NIPS
2008
15 years 8 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
153
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UAI
2003
15 years 8 months ago
2003
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
192
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ATAL
2010
Springer
15 years 7 months ago
2010
Springer
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...