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9
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High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning
– Francis Bach
- 2009
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2. Function space / normRegularizations
– Francis Bach, Special Thanks To R. Jenatton, J. Mairal, G. Obozinski Supervised Learning, Data Xi X, Yi Y, Function Space Norm
- 2009
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81
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Consistency of the group lasso and multiple kernel learning
– Francis R. Bach
- 2007
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Learning with Sparsity-Inducing Norms
– Francis Bach
- 2008
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4
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SimpleMKL
– Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet
- 2008
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Learning with Unlabeled Data
– Xu Zenglin
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Model-Consistent Sparse Estimation through the Bootstrap
– Francis Bach
- 2009
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– Groups of features / Multiple kernel learning
– Francis Bach, Function Space Norm
- 2010
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Abstract
– Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Pavel Laskov, Universität Tübingen, Klaus-robert Müller, Alexander Zien
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23
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Hiroshi Imai and Masao Iri. Polygonal approximations of a curve – formulations and algorithms
– Francis R. Bach
- 1988
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77
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An interior-point method for large-scale l1-regularized logistic regression
– Kwangmoo Koh, Seung-jean Kim, Stephen Boyd, Yi Lin
- 2007
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Positive Definite Kernels in Machine Learning
– Marco Cuturi
- 2009
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Learning to Integrate Data from Different Sources and Tasks
– Andreas Argyriou
- 2007
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2
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Building Sparse Multiple-Kernel SVM Classifiers
– Mingqing Hu, Yiqiang Chen, James Tin-yau Kwok
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11
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Multi-class Discriminant Kernel Learning via Convex Programming
– Jieping Ye, Shuiwang Ji, Jianhui Chen, Isabelle Guyon, Amir Saffari
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Class Prediction from Disparate Biological Data Sources using an Iterative Multi-kernel Algorithm
– Yiming Ying, Colin Campbell, Theodoros Damoulas, Mark Girolami
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19
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Bolasso: model consistent lasso estimation through the bootstrap
– Francis R. Bach
- 2008
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Contents lists available at ScienceDirect Pattern Recognition
– Mehmet Gönen, Ethem Alpaydın
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14
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On the Asymptotic Properties of The Group Lasso Estimator in Least Squares Problems
– Yuval Nardi, Alessandro Rinaldo
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