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» Sparse Optimization for Second Order Kernel Methods
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JMLR
2006
156views more  JMLR 2006»
13 years 7 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
PKDD
2009
Springer
147views Data Mining» more  PKDD 2009»
14 years 1 months ago
Kernel Polytope Faces Pursuit
Abstract. Polytope Faces Pursuit (PFP) is a greedy algorithm that approximates the sparse solutions recovered by 1 regularised least-squares (Lasso) [4,10] in a similar vein to (Or...
Tom Diethe, Zakria Hussain
JMLR
2006
89views more  JMLR 2006»
13 years 7 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel
ICDM
2009
IEEE
149views Data Mining» more  ICDM 2009»
14 years 2 months ago
Accelerated Gradient Method for Multi-task Sparse Learning Problem
—Many real world learning problems can be recast as multi-task learning problems which utilize correlations among different tasks to obtain better generalization performance than...
Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbon...
MOC
2010
13 years 2 months ago
Convergence analysis of the Jacobi spectral-collocation methods for Volterra integral equations with a weakly singular kernel
In this paper, a Jacobi-collocation spectral method is developed for Volterra integral equations of the second kind with a weakly singular kernel. We use some function transformati...
Yanping Chen, Tao Tang