Efficient coordinate descent for ranking with domination loss
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2011
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| Online Access: | http://hdl.handle.net/1721.1/61592 |
| _version_ | 1811071962195165184 |
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| author | Stevens, Mark A., M. Eng. Massachusetts Institute of Technology |
| author2 | Yoram Singer and Michael Collins. |
| author_facet | Yoram Singer and Michael Collins. Stevens, Mark A., M. Eng. Massachusetts Institute of Technology |
| author_sort | Stevens, Mark A., M. Eng. Massachusetts Institute of Technology |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. |
| first_indexed | 2024-09-23T08:58:42Z |
| format | Thesis |
| id | mit-1721.1/61592 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T08:58:42Z |
| publishDate | 2011 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/615922019-04-10T18:00:21Z Efficient coordinate descent for ranking with domination loss Stevens, Mark A., M. Eng. Massachusetts Institute of Technology Yoram Singer and Michael Collins. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 37-38). We define a new batch coordinate-descent ranking algorithm based on a domination loss, which is designed to rank a small number of positive examples above all negatives, with a large penalty on false positives. Its objective is to learn a linear ranking function for a query with labeled training examples in order to rank documents. The derived single-coordinate updates scale linearly with respect to the number of examples. We investigate a number of modifications to the basic algorithm, including regularization, layers of examples, and feature induction. The algorithm is tested on multiple datasets and problem settings, including Microsoft's LETOR dataset, the Corel image dataset, a Google image dataset, and Reuters RCV1. Specific results vary by problem and dataset, but the algorithm generally performed similarly to existing algorithms when rated by average precision and precision at top k. It does not train as quickly as online algorithms, but offers extensions to multiple layers, and perhaps most importantly, can be used to produce extremely sparse weight vectors. When trained with feature induction, it achieves similarly competitive performance but with much more compact models. by Mark A. Stevens. M.Eng. 2011-03-07T15:20:08Z 2011-03-07T15:20:08Z 2010 2010 Thesis http://hdl.handle.net/1721.1/61592 704290978 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 38 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Stevens, Mark A., M. Eng. Massachusetts Institute of Technology Efficient coordinate descent for ranking with domination loss |
| title | Efficient coordinate descent for ranking with domination loss |
| title_full | Efficient coordinate descent for ranking with domination loss |
| title_fullStr | Efficient coordinate descent for ranking with domination loss |
| title_full_unstemmed | Efficient coordinate descent for ranking with domination loss |
| title_short | Efficient coordinate descent for ranking with domination loss |
| title_sort | efficient coordinate descent for ranking with domination loss |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/61592 |
| work_keys_str_mv | AT stevensmarkamengmassachusettsinstituteoftechnology efficientcoordinatedescentforrankingwithdominationloss |