Multiclass learning with simplex coding
In this paper we discuss a novel framework for multiclass learning, defined by a suitable coding/decoding strategy, namely the simplex coding, that allows us to generalize to multiple classes a relaxation approach commonly used in binary classification. In this framework, we develop a relaxation err...
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Bibliographic Details
| Main Authors: |
Mroueh, Youssef
(Contributor),
Poggio, Tomaso A.
(Contributor),
Rosasco, Lorenzo Andrea
(Contributor),
Slotine, Jean-Jacques E.
(Contributor) |
|---|
| Other Authors: |
Massachusetts Institute of Technology. Center for Biological & Computational Learning
(Contributor),
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
(Contributor),
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
(Contributor),
Massachusetts Institute of Technology. Department of Mechanical Engineering
(Contributor),
McGovern Institute for Brain Research at MIT
(Contributor) |
|---|
| Format: | Article
|
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| Language: | English |
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| Published: |
Neural Information Processing Systems Foundation,
2014-12-16T15:43:57Z.
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| Subjects: | |
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| Online Access: | Get fulltext
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