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http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7209| Title: | A Formulation for Active Learning with Applications to Object Detection |
| Keywords: | active learning optimal experiment design object detection example selection |
| Issue Date: | 9-Oct-2013 |
| Description: | We discuss a formulation for active example selection for function learning problems. This formulation is obtained by adapting Fedorov's optimal experiment design to the learning problem. We specifically show how to analytically derive example selection algorithms for certain well defined function classes. We then explore the behavior and sample complexity of such active learning algorithms. Finally, we view object detection as a special case of function learning and show how our formulation reduces to a useful heuristic to choose examples to reduce the generalization error. |
| URI: | http://koha.mediu.edu.my:8181/xmlui/handle/1721 |
| Other Identifiers: | AIM-1438 CBCL-116 http://hdl.handle.net/1721.1/7209 |
| Appears in Collections: | MIT Items |
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