3694 search results - page 160 / 739 » Stochastic complexity in learning |
168
Voted
CVPR
2009
IEEE
16 years 11 months ago
2009
IEEE
Graph-based methods form a main category of semisupervised
learning, offering flexibility and easy implementation
in many applications. However, the performance of
these methods...
133
Voted
ICML
2009
IEEE
16 years 4 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
123
Voted
ICASSP
2011
IEEE
14 years 7 months ago
2011
IEEE
We start by formulating the resource sharing in peer-to-peer (P2P) networks as a random-matching gift-giving game, where self-interested peers aim at maximizing their own long-ter...
117
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COLING
2008
15 years 5 months ago
2008
Recent years have witnessed a growing interest in analogical learning for NLP applications. If the principle of analogical learning is quite simple, it does involve complex steps ...
132
click to vote
CORR
2010
Springer
15 years 4 months ago
2010
Springer
The sample complexity of active learning under the realizability assumption has been well-studied. The realizability assumption, however, rarely holds in practice. In this paper, ...