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Title: | Active Learning with Statistical Models |
Keywords: | AI MIT Artificial Intelligence active learning queries locally weighted regression LOESS mixtures of gaussians exploration robotics |
Issue Date: | 9-Oct-2013 |
Description: | For many types of learners one can compute the statistically 'optimal' way to select data. We review how these techniques have been used with feedforward neural networks. We then show how the same principles may be used to select data for two alternative, statistically-based learning architectures: mixtures of Gaussians and locally weighted regression. While the techniques for neural networks are expensive and approximate, the techniques for mixtures of Gaussians and locally weighted regression are both efficient and accurate. |
URI: | http://koha.mediu.edu.my:8181/xmlui/handle/1721 |
Other Identifiers: | AIM-1522 CBCL-110 http://hdl.handle.net/1721.1/7192 |
Appears in Collections: | MIT Items |
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