New insights on the power of active learning
Traditional supervised machine learning algorithms are expected to have access to a large corpus of labeled examples, but the massive amount of data available in the modern world has made unlabeled data much easier to acquire than accompanying labels. Active learning is an extension of the classical...
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| Format: | Others |
| Language: | en_US |
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Georgia Institute of Technology
2015
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| Online Access: | http://hdl.handle.net/1853/53948 |