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Stochastic gradient algorithms estimate the gradient based on only one or a few samples and enjoy low computational cost per iteration.
On the convergence of the coordinate descent method for convex differentiable minimization
Z.-Q. Luo and P. Tseng · 1992
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Error bounds and convergence analysis of feasible descent methods: a general approach
Z. Luo and P. Tseng · 1993
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Regression shrinkage and selection via the lasso
R. Tibshirani · 1996
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Nonlinear Programming
D. Bertsekas · 1999
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Solving large scale linear prediction problems using stochastic gradient descent algorithms
T. Zhang · 2004
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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
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Accelerated gradient methods for stochastic optimization and online learning
C. Hu, J. Kwok, and W. Pan · 2009
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An efficient projection for ℓ 1 , ∞ \ell_{1,\infty} regularization
A. Quattoni, X. Carreras, M. Collins, and T. Darrell · 2009
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A coordinate gradient descent method for nonsmooth separable minimization
P. Tseng and S. Yun · 2009
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Approximation accuracy, gradient methods, and error bound for structured convex optimization
P. Tseng · 2010
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Dual averaging methods for regularized stochastic learning and online optimization
L. Xiao · 2010
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Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization
E. Hazan and S. Kale · 2011
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Making gradient descent optimal for strongly convex stochastic optimization
A. Rakhlin, O. Shamir, and K. Sridharan · 2011
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On the linear convergence of the proximal gradient method for trace norm regularization
K. Hou, Z. Zhou, A. So, and Z. Luo · 2013
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Accelerating stochastic gradient descent using predictive variance reduction
R. Johnson and T. Zhang · 2013
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Semi-stochastic gradient descent methods
J. Konečnỳ and P. Richtárik · 2013
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Gradient methods for minimizing composite functions
Y. Nesterov · 2013
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Stochastic dual coordinate ascent methods for regularized loss
S. Shalev-Shwartz and T. Zhang · 2013
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Stochastic gradient descent for non-smooth optimization: Convergence results and optimal averaging schemes
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A. Agarwal, S. Negahban, and J. Wainwright · 2012
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An optimal method for stochastic composite optimization
G. Lan · 2012
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A stochastic gradient method with an exponential convergence rate for finite training sets
N. Le Roux, M. Schmidt, and F. Bach · 2012
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Proximal stochastic dual coordinate ascent
S. Shalev-Shwartz and T. Zhang · 2012
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O. Shamir and T. Zhang · 2013
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Linear convergence with condition number independent access of full gradients
L. Zhang, M. Mahdavi, and R. Jin · 2013
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Iteration complexity of feasible descent methods for convex optimization
P. Wang and C. Lin · 2014
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A proximal stochastic gradient method with progressive variance reduction
L. Xiao and T. Zhang · 2014
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