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Sparsity-inducing penalties are useful tools to design multiclass support vector machines (SVMs).
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Convex Optimization
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“A speech recognizer based on multiclass SVMs with HMM-guided segmentation,”
D. Martín-Iglesias, J. Bernal-Chaves, C. Peláez-Moreno, A. Gallardo-Antolín, and F. Díaz-de María, · 2005
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“Sparse multinomial logistic regression: Fast algorithms and generalization bounds,”
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M. Yuan and Y. Lin, · 2006
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Y. Liu, H. Helen Zhang, C. Park, and J. Ahn, · 2007
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Y. Liu and Y. Wu, · 2007
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“On l 1 l_{1} -norm multi-class support vector machines: methodology and theory,”
L. Wang and X. Shen, · 2007
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I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld, · 2008
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H. Zou and M. Yuan, · 2008
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“Optimization with sparsity-inducing penalties,”
F. Bach, R. Jenatton, J. Mairal, and G. Obozinski, · 2012
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L. Rosasco, S. Villa, S. Mosci, M. Santoro, and A. Verri, · 2013
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“Enhancing sparsity by reweighted ℓ 1 \ell_{1} minimization,”
E. J. Candés, M. B. Wakin, and S. Boyd, · 2008
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“The group Lasso for logistic regression,”
L. Meier, S. Van De Geer, and P. Bühlmann, · 2008
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“Variable selection for multicategory SVM via sup-norm regularization,”
H.H. Zhang, Y. Liu, Y. Wu, and J. Zhu, · 2008
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“Probing the Pareto frontier for basis pursuit solutions,”
E. Van Den Berg and M. P. Friedlander, · 2008
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“Cutting-plane training of structural SVMs,”
T. Joachims, T. Finley, and C.-N. J. Yu, · 2009
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“Boosting with structural sparsity,”
J. Duchi and Y. Singer, · 2009
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L. Condat, · 2013
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“Block coordinate descent algorithms for large-scale sparse multiclass classification,”
M. Blondel, K. Seki, and K. Uehara, · 2013
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“Invariant scattering convolution networks,”
J. Bruna and S. Mallat, · 2013
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“Large-scale multiclass support vector machine training via euclidean projection onto the simplex,”
M. Blondel, A. Fujino, and N. Ueda, · 2014
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“Automatic feature learning for spatio-spectral image classification with sparse SVM,”
D. Tuia, M. Volpi, M. Dalla Mura, A. Rakotomamonjy, and R. Flamary, · 2014
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“Proximal methods for the latent group lasso penalty,”
S. Villa, L. Rosasco, S. Mosci, and A. Verri, · 2014
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“Epigraphical projection and proximal tools for solving constrained convex optimization problems,”
G. Chierchia, N. Pustelnik, J.-C. Pesquet, and B. Pesquet-Popescu, · 2014
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“Epigraphical proximal projection for sparse multiclass SVM,”
G. Chierchia, N. Pustelnik, J.-C. Pesquet, and B. Pesquet-Popescu, · 2014
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“Non-convex regularizations for feature selection in ranking with sparse SVM,”
L. Laporte, R. Flamary, S. Canu, S. Déjean, and J. Mothe, · 2014
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“Proximal algorithms,”
N. Parikh and S. Boyd, · 2014
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“Playing with duality: An overview of recent primal-dual approaches for solving large-scale optimization problems,”
N. Komodakis and J.-C. Pesquet, · 2014
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“A forward-backward view of some primal-dual optimization methods in image recovery,”
P. L. Combettes, L. Condat, J.-C. Pesquet, and B. C. Vũ, · 2014
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“Variable metric forward-backward splitting with applications to monotone inclusions in duality,”
P. L. Combettes and B. C. Vũ, · 2014
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“Fast projection onto the simplex and the l1 ball,”
L. Condat, · 2014
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