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We introduce a proximal version of dual coordinate ascent method.
Mirror descent and nonlinear projected subgradient methods for convex optimization
A. Beck and M. Teboulle · 2003
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Exponentiated gradient algorithms for conditional random fields and max-margin markov networks
M. Collins, A. Globerson, T. Koo, X. Carreras, and P. Bartlett · 2008
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A fast iterative shrinkage-thresholding algorithm for linear inverse problems
A. Beck and M. Teboulle · 2009
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Efficient online and batch learning using forward backward splitting
J. Duchi and Y. Singer · 2009
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Sparse online learning via truncated gradient
J. Langford, L. Li, and T. Zhang · 2009
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Composite objective mirror descent
John Duchi, Shai Shalev-Shwartz, Yoram Singer, and Ambuj Tewari · 2010
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Dual averaging method for regularized stochastic learning and online optimization
Lin Xiao · 2010
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Online learning and online convex optimization
S. Shalev-Shwartz · 2011
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Stochastic methods for l 1-regularized loss minimization
S. Shalev-Shwartz and A. Tewari · 2011
Cited alongside, same era.
Regularization techniques for learning with matrices
S. Kakade, S. Shalev-Shwartz, and A. Tewari · 2012
Cited alongside, same era.
Stochastic block-coordinate frank-wolfe optimization for structural svms
S. Lacoste-Julien, M. Jaggi, M. Schmidt, and P. Pletscher · 2012
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Nicolas Le Roux, Mark Schmidt, and Francis Bach · 2012
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Efficiency of coordinate descent methods on huge-scale optimization problems
Y. Nesterov · 2012
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Stochastic dual coordinate ascent methods for regularized loss minimization
Shai Shalev-Shwartz and Tong Zhang · 2012
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