-
1
-
-
84860608998
-
-
arXiv preprint arXiv:1108. 0775
-
F. Bach, R. Jenatton, J. Mairal, and G. Obozinski, "Optimization with sparsity-inducing penalties," arXiv preprint arXiv:1108. 0775, 2011.
-
(2011)
Optimization with Sparsity-inducing Penalties
-
-
Bach, F.1
Jenatton, R.2
Mairal, J.3
Obozinski, G.4
-
2
-
-
84886524110
-
-
arXiv preprint arXiv:1105. 5379
-
J. K. Bradley, A. Kyrola, D. Bickson, and C. Guestrin, "Parallel coordinate descent for l1-regularized loss minimization," arXiv preprint arXiv:1105. 5379, 2011.
-
(2011)
Parallel Coordinate Descent for l1-regularized Loss Minimization
-
-
Bradley, J.K.1
Kyrola, A.2
Bickson, D.3
Guestrin, C.4
-
6
-
-
84874622647
-
Efficient parallel coordinate descent algorithm for convex optimization problems with separable constraints: Application to distributed MPC
-
I. Necoara and D. Clipici, "Efficient parallel coordinate descent algorithm for convex optimization problems with separable constraints: application to distributed MPC," Journal of Process Control, vol. 23, no. 3, pp. 243-253, 2013.
-
(2013)
Journal of Process Control
, vol.23
, Issue.3
, pp. 243-253
-
-
Necoara, I.1
Clipici, D.2
-
7
-
-
85057290169
-
Gradient methods for minimizing composite functions
-
Y. Nesterov, "Gradient methods for minimizing composite functions," Mathematical Programming, pp. 1-37, 2012.
-
(2012)
Mathematical Programming
, pp. 1-37
-
-
Nesterov, Y.1
-
8
-
-
84865692149
-
Efficiency of coordinate descent methods on hugescale optimization problems
-
-, "Efficiency of coordinate descent methods on hugescale optimization problems," SIAM Journal on Optimization, vol. 22, no. 2, pp. 341-362, 2012.
-
(2012)
SIAM Journal on Optimization
, vol.22
, Issue.2
, pp. 341-362
-
-
Nesterov, Y.1
-
9
-
-
84890453771
-
Efficient blockcoordinate descent algorithms for the group lasso
-
Z. Qin, K. Scheinberg, and D. Goldfarb, "Efficient blockcoordinate descent algorithms for the group lasso," Mathematical Programming Computation, pp. 1-27, 2010.
-
(2010)
Mathematical Programming Computation
, pp. 1-27
-
-
Qin, Z.1
Scheinberg, K.2
Goldfarb, D.3
-
10
-
-
79952039898
-
Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms
-
A. Rakotomamonjy, "Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms," Signal processing, vol. 91, no. 7, pp. 1505-1526, 2011.
-
(2011)
Signal Processing
, vol.91
, Issue.7
, pp. 1505-1526
-
-
Rakotomamonjy, A.1
-
11
-
-
84880570485
-
A unified convergence analysis of block successive minimization methods for nonsmooth optimization
-
M. Razaviyayn, M. Hong, and Z.-Q. Luo, "A unified convergence analysis of block successive minimization methods for nonsmooth optimization," SIAM Journal on Optimization, vol. 23, no. 2, pp. 1126-1153, 2013.
-
(2013)
SIAM Journal on Optimization
, vol.23
, Issue.2
, pp. 1126-1153
-
-
Razaviyayn, M.1
Hong, M.2
Luo, Z.-Q.3
-
12
-
-
84897116612
-
Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
-
P. Richtárik and M. Takáč, "Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function," Mathematical Programming, pp. 1-38, 2012.
-
(2012)
Mathematical Programming
, pp. 1-38
-
-
Richtárik, P.1
Takáč, M.2
-
14
-
-
84864687560
-
-
Cambridge, Massachusetts: The MIT Press, Sept.
-
S. Sra, S. Nowozin, and S. J. Wright, Eds., Optimization for Machine Learning, ser. Neural Information Processing. Cambridge, Massachusetts: The MIT Press, Sept. 2011.
-
(2011)
Optimization for Machine Learning, Ser. Neural Information Processing
-
-
Sra, S.1
Nowozin, S.2
Wright, S.J.3
-
15
-
-
46749146509
-
A coordinate gradient descent method for nonsmooth separable minimization
-
P. Tseng and S. Yun, "A coordinate gradient descent method for nonsmooth separable minimization," Mathematical Programming, vol. 117, no. 1-2, pp. 387-423, 2009.
-
(2009)
Mathematical Programming
, vol.117
, Issue.1-2
, pp. 387-423
-
-
Tseng, P.1
Yun, S.2
-
18
-
-
79551500651
-
A comparison of optimization methods and software for large-scale l1-regularized linear classification
-
G.-X. Yuan, K.-W. Chang, C.-J. Hsieh, and C.-J. Lin, "A comparison of optimization methods and software for large-scale l1-regularized linear classification," The Journal of Machine Learning Research, vol. 9999, pp. 3183-3234, 2010.
-
(2010)
The Journal of Machine Learning Research
, vol.9999
, pp. 3183-3234
-
-
Yuan, G.-X.1
Chang, K.-W.2
Hsieh, C.-J.3
Lin, C.-J.4
-
19
-
-
84861594597
-
Accelerated block-coordinate relaxation for regularized optimization
-
S. J. Wright, "Accelerated block-coordinate relaxation for regularized optimization," SIAM Journal on Optimization, vol. 22, no. 1, pp. 159-186, 2012.
-
(2012)
SIAM Journal on Optimization
, vol.22
, Issue.1
, pp. 159-186
-
-
Wright, S.J.1
-
20
-
-
84890457443
-
Decomposition by partial linearization in multiuser systems
-
May 4-9
-
G. Scutari, F. Facchinei, P. Song, D. P. Palomar, and J.-S. Pang, "Decomposition by partial linearization in multiuser systems," in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), May 4-9 2013, pp. 4424-4428.
-
(2013)
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)
, pp. 4424-4428
-
-
Scutari, G.1
Facchinei, F.2
Song, P.3
Palomar, D.P.4
Pang, J.-S.5
-
21
-
-
84893409470
-
Decomposition by partial linearization: Parallel optimization of multi-agent systems
-
Feb
-
G. Scutari, F. Facchinei, P. Song, D. Palomar, and J.-S. Pang, "Decomposition by Partial linearization: Parallel optimization of multi-agent systems," IEEE Trans. Signal Process., vol. 62, pp. 641-656, Feb. 2014.
-
(2014)
IEEE Trans. Signal Process.
, vol.62
, pp. 641-656
-
-
Scutari, G.1
Facchinei, F.2
Song, P.3
Palomar, D.4
Pang, J.-S.5
-
23
-
-
33645035051
-
Model selection and estimation in regression with grouped variables
-
M. Yuan and Y. Lin, "Model selection and estimation in regression with grouped variables," Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 68, no. 1, pp. 49-67, 2006.
-
(2006)
Journal of the Royal Statistical Society: Series B (Statistical Methodology)
, vol.68
, Issue.1
, pp. 49-67
-
-
Yuan, M.1
Lin, Y.2
-
24
-
-
0345327592
-
A simple and efficient algorithm for gene selection using sparse logistic regression
-
S. K. Shevade and S. S. Keerthi, "A simple and efficient algorithm for gene selection using sparse logistic regression," Bioinformatics, vol. 19, no. 17, pp. 2246-2253, 2003.
-
(2003)
Bioinformatics
, vol.19
, Issue.17
, pp. 2246-2253
-
-
Shevade, S.K.1
Keerthi, S.S.2
-
25
-
-
37849035696
-
The group lasso for logistic regression
-
L. Meier, S. Van De Geer, and P. Bühlmann, "The group lasso for logistic regression," Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 70, no. 1, pp. 53-71, 2008.
-
(2008)
Journal of the Royal Statistical Society: Series B (Statistical Methodology)
, vol.70
, Issue.1
, pp. 53-71
-
-
Meier, L.1
Van De Geer, S.2
Bühlmann, P.3
-
26
-
-
84884671011
-
Fast alternating linearization methods for minimizing the sum of two convex functions
-
D. Goldfarb, S. Ma, and K. Scheinberg, "Fast alternating linearization methods for minimizing the sum of two convex functions," Mathematical Programming, pp. 1-34, 2012.
-
(2012)
Mathematical Programming
, pp. 1-34
-
-
Goldfarb, D.1
Ma, S.2
Scheinberg, K.3
-
30
-
-
85014561619
-
A fast iterative shrinkagethresholding algorithm for linear inverse problems
-
A. Beck and M. Teboulle, "A fast iterative shrinkagethresholding algorithm for linear inverse problems," SIAM Journal on Imaging Sciences, vol. 2, no. 1, pp. 183-202, 2009.
-
(2009)
SIAM Journal on Imaging Sciences
, vol.2
, Issue.1
, pp. 183-202
-
-
Beck, A.1
Teboulle, M.2
-
31
-
-
80051762104
-
Distributed optimization and statistical learning via the alternating direction method of multipliers
-
S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, "Distributed optimization and statistical learning via the alternating direction method of multipliers," Foundations and Trends-R in Machine Learning, vol. 3, no. 1, pp. 1-122, 2011.
-
(2011)
Foundations and Trends-R in Machine Learning
, vol.3
, Issue.1
, pp. 1-122
-
-
Boyd, S.1
Parikh, N.2
Chu, E.3
Peleato, B.4
Eckstein, J.5
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