Varma, M. ; Babu, B.R. (2009) More Generality in Efficient Multiple Kernel Learning In: Proceedings of the International Conference on Machine Learning.
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Abstract
Recent Advances In Multiple Kernel Learning (mkl) Have Positioned It As An Attractive Tool For Tackling Many Supervised Learning Tasks. The Development Of Efficient Gradient Descent Based Optimization Schemes Has Made It Possible To Tackle Large Scale Problems. Simultaneously, Mkl Based Algorithms Have Achieved Very Good Results On Challenging Real World Applications. Yet, Despite Their Successes, Mkl Approaches Are Limited In That They Focus On Learning A Linear Combination Of Given Base Kernels.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Source: | Copyright of this article belongs to International Conference on Machine Learning. |
| ID Code: | 119701 |
| Deposited On: | 16 Jun 2021 09:40 |
| Last Modified: | 16 Jun 2021 09:40 |
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