1989 search results - page 113 / 398 » Learning to Select Useful Landmarks |
183
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EMNLP
2008
15 years 7 months ago
2008
Active learning is well-suited to many problems in natural language processing, where unlabeled data may be abundant but annotation is slow and expensive. This paper aims to shed ...
186
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AAMAS
2002
Springer
15 years 6 months ago
2002
Springer
In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action in a given state of the environment, so that it maximizes the total amount of reward it ...
167
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JSA
2006
15 years 6 months ago
2006
It is often possible to greatly improve the performance of a hardware system via the use of predictive (speculative) techniques. For example, the performance of out-of-order micro...
165
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NIPS
2008
15 years 7 months ago
2008
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
204
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IJCAI
2001
15 years 7 months ago
2001
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...