Jawanpuria, P. ; Varma, M. ; Nath, J.S. (2014) On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection In: Proceedings of the 31 st International Conference on Machine Learning, 2014, Beijing, China.
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Abstract
Our objective is to develop formulations and algorithms for efficiently computing the feature selection path - i.e. the variation in classification accuracy as the fraction of selected features is varied from null to unity. Multiple Kernel Learning subject to lp≥1 regularization (lp-MKL) has been demonstrated to be one of the most effective techniques for non-linear feature selection. However, state-of-the-art lp-MKL algorithms are too computationally expensive to be invoked thousands of times to determine the entire path.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Source: | Copyright of this article belongs to International Conference on Machine Learning. |
| ID Code: | 119689 |
| Deposited On: | 16 Jun 2021 08:39 |
| Last Modified: | 16 Jun 2021 08:39 |
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