Learning dimensionality-reduced classifiers for information fusion
The fusion of multimodal sensor information often requires learning decision rules from samples of high-dimensional data. Each data dimension may only be weakly informative for the detection problem of interest. Also, it is not known a priori which components combine to form a lower-dimensional feat...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2012
|
| Online Access: | http://hdl.handle.net/1721.1/74147 https://orcid.org/0000-0003-0149-5888 |
| _version_ | 1826197008843538432 |
|---|---|
| author | Varshney, Kush R. Willsky, Alan S. |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Varshney, Kush R. Willsky, Alan S. |
| author_sort | Varshney, Kush R. |
| collection | MIT |
| description | The fusion of multimodal sensor information often requires learning decision rules from samples of high-dimensional data. Each data dimension may only be weakly informative for the detection problem of interest. Also, it is not known a priori which components combine to form a lower-dimensional feature space that is most informative. To learn both the combination of dimensions and the decision rule specified in the reduced-dimensional space together, we jointly optimize the linear dimensionality reduction and margin-based supervised classification problems, representing dimensionality reduction by matrices on the Stiefel manifold. We describe how the learning procedure and resulting decision rule can be implemented in parallel, serial, and tree-structured fusion networks. |
| first_indexed | 2024-09-23T10:41:00Z |
| format | Article |
| id | mit-1721.1/74147 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:41:00Z |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/741472022-09-27T14:13:41Z Learning dimensionality-reduced classifiers for information fusion Varshney, Kush R. Willsky, Alan S. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Laboratory for Information and Decision Systems Varshney, Kush R. Willsky, Alan S. The fusion of multimodal sensor information often requires learning decision rules from samples of high-dimensional data. Each data dimension may only be weakly informative for the detection problem of interest. Also, it is not known a priori which components combine to form a lower-dimensional feature space that is most informative. To learn both the combination of dimensions and the decision rule specified in the reduced-dimensional space together, we jointly optimize the linear dimensionality reduction and margin-based supervised classification problems, representing dimensionality reduction by matrices on the Stiefel manifold. We describe how the learning procedure and resulting decision rule can be implemented in parallel, serial, and tree-structured fusion networks. United States. Army Research Office. Multidisciplinary University Research Initiative (Grant W911NF-06-1-0076) United States. Air Force Office of Scientific Research. Multidisciplinary University Research Initiative (Grant FA9550-06-1-0324) 2012-10-19T14:25:14Z 2012-10-19T14:25:14Z 2009-08 2009-07 Article http://purl.org/eprint/type/ConferencePaper 978-0-9824-4380-4 http://hdl.handle.net/1721.1/74147 Kush R. Varshney and Alan S. Willsky. "Learning dimensionality-reduced classifiers for information fusion." 12th International Conference on Information Fusion, 2009. FUSION '09. © 2009 ISIF https://orcid.org/0000-0003-0149-5888 en_US http://ieeexplore.ieee.org/xpls/abs_all.jsp?tp=&arnumber=5203616&tag=1 Proceedings of the 12th International Conference on Information Fusion, 2009. FUSION '09 Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Institute of Electrical and Electronics Engineers (IEEE) IEEE |
| spellingShingle | Varshney, Kush R. Willsky, Alan S. Learning dimensionality-reduced classifiers for information fusion |
| title | Learning dimensionality-reduced classifiers for information fusion |
| title_full | Learning dimensionality-reduced classifiers for information fusion |
| title_fullStr | Learning dimensionality-reduced classifiers for information fusion |
| title_full_unstemmed | Learning dimensionality-reduced classifiers for information fusion |
| title_short | Learning dimensionality-reduced classifiers for information fusion |
| title_sort | learning dimensionality reduced classifiers for information fusion |
| url | http://hdl.handle.net/1721.1/74147 https://orcid.org/0000-0003-0149-5888 |
| work_keys_str_mv | AT varshneykushr learningdimensionalityreducedclassifiersforinformationfusion AT willskyalans learningdimensionalityreducedclassifiersforinformationfusion |