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CORR
2012
Springer
214views Education» more  CORR 2012»
12 years 6 months ago
Stochastic Low-Rank Kernel Learning for Regression
We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic ...
Pierre Machart, Thomas Peel, Liva Ralaivola, Sandr...
ICPR
2010
IEEE
13 years 8 months ago
Learning the Kernel Combination for Object Categorization
Although Support Vector Machines(SVM) succeed in classifying several image databases using image descriptors proposed in the literature, no single descriptor can be optimal for ge...
Deyuan Zhang, Xiaolong Wang, Bingquan Liu
ICML
2007
IEEE
14 years 11 months ago
More efficiency in multiple kernel learning
An efficient and general multiple kernel learning (MKL) algorithm has been recently proposed by Sonnenburg et al. (2006). This approach has opened new perspectives since it makes ...
Alain Rakotomamonjy, Francis Bach, Stéphane...
CORR
2010
Springer
124views Education» more  CORR 2010»
13 years 11 months ago
Online Learning of Noisy Data with Kernels
We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
CVPR
2010
IEEE
14 years 7 months ago
Online-Batch Strongly Convex Multi Kernel Learning
Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled approach to combine multiple cues, and to obtain state-of-theart perform...
Francesco Orabona, Jie Luo, Barbara Caputo