Hariharan, B. ; Vishwanathan, S.V.N. ; Varma, M. (2012) Efficient Max-Margin Multi-Label Classification with Applications to Zero-Shot Learning Machine Learning, 88 (1). pp. 127-155. ISSN 0885-6125
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Official URL: https://www.springer.com/journal/10994
Abstract
The goal in multi-label classification is to tag a data point with the subset of relevant labels from a pre-specified set. Given a set of L labels, a data point can be tagged with any of the 2L possible subsets. The main challenge therefore lies in optimising over this exponentially large label space subject to label correlations.
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Springer Verlag. |
| Keywords: | Multi-Label Classification; Zero-shot Learning; Max-Margin Methods; SMO Optimization; 1-vs-all Classification. |
| ID Code: | 119693 |
| Deposited On: | 16 Jun 2021 09:06 |
| Last Modified: | 16 Jun 2021 09:06 |
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