Abstract. While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations.

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This paper focuses on several regularized MSVMs and extends the alternating direction method of multiplier (ADMM) to these MSVMs. Using a splitting technique, ...

Abstract. While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations.

Experimental results are presented that show that the proposed novel dual formulation of the QCQP as a second-order cone programming problem is ...

The lp-. MKL dual is shown to be differentiable and thereby amenable to co-ordinate ascent. Placing the p-norm squared regulariser in the objective lets us ...

years, multiple kernel learning (MKL) methods have been proposed, where we use multiple kernels ... Multiple kernel learning, conic duality, and the SMO algorithm ...

Our objective is to trainp-norm Multiple Kernel Learning (MKL) and, more generally, linear MKL regularised by the Bregman divergence, using the Sequential ...

Missing: conic | Show results with:conic

We have proposed a simple, yet efficient algorithm to solve the multiple kernel learning ... Multiple kernel learning, conic duality, and the SMO algorithm. In ...