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Regularization Strategies and Empirical Bayesian Learning for MKL
v1v2 (latest)

Regularization Strategies and Empirical Bayesian Learning for MKL

13 November 2010
Ryota Tomioka
Taiji Suzuki
ArXiv (abs)PDFHTML

Papers citing "Regularization Strategies and Empirical Bayesian Learning for MKL"

4 / 4 papers shown
Title
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear
  Multivariate Regression and Granger Causality
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality
Vikas Sindhwani
H. Q. Minh
A. Lozano
133
59
0
09 Aug 2014
Regularization for Multiple Kernel Learning via Sum-Product Networks
Regularization for Multiple Kernel Learning via Sum-Product Networks
Ziming Zhang
51
0
0
13 Feb 2014
Regularizers for Structured Sparsity
Regularizers for Structured Sparsity
C. Micchelli
Jean Morales
Massimiliano Pontil
149
80
0
04 Oct 2010
Super-Linear Convergence of Dual Augmented-Lagrangian Algorithm for
  Sparsity Regularized Estimation
Super-Linear Convergence of Dual Augmented-Lagrangian Algorithm for Sparsity Regularized Estimation
Ryota Tomioka
Taiji Suzuki
Masashi Sugiyama
217
84
0
20 Nov 2009
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