Active Search with Complex Actions and Rewards
Active search studies algorithms that can find all positive examples in an unknown environment by collecting and learning from labels that are costly to obtain. They start with a pool of unlabeled data, act to design queries, and get rewarded by the number of positive examples found in a long-term h...
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| Format: | Others |
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Research Showcase @ CMU
2017
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| Online Access: | http://repository.cmu.edu/dissertations/1115 http://repository.cmu.edu/cgi/viewcontent.cgi?article=2154&context=dissertations |