A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems, SIAM Journal on Imaging Sciences, vol.2, issue.1, pp.183-202, 2009. ,
DOI : 10.1137/080716542
Smoothing and First Order Methods: A Unified Framework, SIAM Journal on Optimization, vol.22, issue.2, pp.557-580, 2012. ,
DOI : 10.1137/100818327
Numerical Optimization: Theoretical and Practical Aspects, 2006. ,
DOI : 10.1007/978-3-662-05078-1
On the superlinear convergence of the variable metric proximal point algorithm using Broyden and BFGS matrix secant updating, Mathematical Programming, pp.157-181, 2000. ,
DOI : 10.1007/PL00011373
A Stochastic Quasi-Newton Method for Large-Scale Optimization, SIAM Journal on Optimization, vol.26, issue.2, pp.1008-1031, 2016. ,
DOI : 10.1137/140954362
An inexact successive quadratic approximation method for L-1 regularized optimization, Mathematical Programming, pp.375-396, 2015. ,
DOI : 10.1007/s10107-015-0941-y
Global Convergence of a Cass of Quasi-Newton Methods on Convex Problems, SIAM Journal on Numerical Analysis, vol.24, issue.5, pp.1171-1190, 1987. ,
DOI : 10.1137/0724077
Proximal quasi-Newton methods for nondifferentiable convex optimization, Mathematical Programming, vol.85, issue.2, pp.313-334, 1999. ,
DOI : 10.1007/s101070050059
Saga: A fast incremental gradient method with support for non-strongly convex composite objectives, Advances in Neural Information Processing Systems, pp.1646-1654, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-01016843
Finito: A faster, permutable incremental gradient method for big data problems, Proceedings of the International Conferences on Machine Learning (ICML), 2014. ,
First-order methods of smooth convex optimization with inexact oracle, Mathematical Programming, vol.110, issue.3, pp.37-75, 2014. ,
DOI : 10.1007/s10107-013-0677-5
Randomized Smoothing for Stochastic Optimization, SIAM Journal on Optimization, vol.22, issue.2, pp.674-701, 2012. ,
DOI : 10.1137/110831659
Sparse and Redundant Representations, 2010. ,
DOI : 10.1007/978-1-4419-7011-4
URL : https://hal.archives-ouvertes.fr/inria-00568893
Hybrid Deterministic-Stochastic Methods for Data Fitting, SIAM Journal on Scientific Computing, vol.34, issue.3, pp.1380-1405, 2012. ,
DOI : 10.1137/110830629
URL : https://hal.archives-ouvertes.fr/inria-00626571
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization, Proceedings of the International Conferences on Machine Learning (ICML), 2015. ,
Descentwise inexact proximal algorithms for smooth optimization, Computational Optimization and Applications, vol.11, issue.1, pp.755-769, 2012. ,
DOI : 10.1007/s10589-012-9461-3
URL : https://hal.archives-ouvertes.fr/hal-00628777
A Globally and Superlinearly Convergent Algorithm for Nonsmooth Convex Minimization, SIAM Journal on Optimization, vol.6, issue.4, pp.1106-1120, 1996. ,
DOI : 10.1137/S1052623494278839
Stochastic block BFGS: Squeezing more curvature out of data, 2016. ,
New Proximal Point Algorithms for Convex Minimization, SIAM Journal on Optimization, vol.2, issue.4, pp.649-664, 1992. ,
DOI : 10.1137/0802032
Convex Analysis and Minimization Algorithms I, 1996. ,
DOI : 10.1007/978-3-662-02796-7
Convex analysis and minimization algorithms. II, 1996. ,
DOI : 10.1007/978-3-662-06409-2
Proximal Newton-type methods for convex optimization, Advances in Neural Information Processing Systems (NIPS), pp.836-844, 2012. ,
Practical Aspects of the Moreau--Yosida Regularization: Theoretical Preliminaries, SIAM Journal on Optimization, vol.7, issue.2, pp.367-385, 1997. ,
DOI : 10.1137/S1052623494267127
A universal catalyst for first-order optimization, Advances in Neural Information Processing Systems (NIPS), 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01160728
On the limited memory BFGS method for large scale optimization, Mathematical Programming, vol.32, issue.2, pp.503-528, 1989. ,
DOI : 10.1007/BF01589116
Sparse Modeling for Image and Vision Processing. Foundations and Trends in Computer Graphics and Vision, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-01081139
A quasi-second-order proximal bundle algorithm, Mathematical Programming, pp.51-72, 1996. ,
DOI : 10.1007/BF02592098
A linearly-convergent stochastic L-BFGS algorithm, 2015. ,
A method of solving a convex programming problem with convergence rate, Soviet Mathematics Doklady, vol.27, issue.1 22, pp.372-376, 1983. ,
Introductory Lectures on Convex Optimization: A Basic Course, 2004. ,
DOI : 10.1007/978-1-4419-8853-9
Smooth minimization of non-smooth functions, Mathematical Programming, vol.269, issue.1, pp.127-152, 2005. ,
DOI : 10.1007/s10107-004-0552-5
Gradient methods for minimizing composite functions, Mathematical Programming, pp.125-161, 2013. ,
DOI : 10.1007/s10107-012-0629-5
Numerical optimization, 2006. ,
DOI : 10.1007/b98874
A Unified Convergence Analysis of Block Successive Minimization Methods for Nonsmooth Optimization, SIAM Journal on Optimization, vol.23, issue.2, pp.1126-1153, 2013. ,
DOI : 10.1137/120891009
Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function, Mathematical Programming, pp.1-38, 2014. ,
DOI : 10.1007/s10107-012-0614-z
Monotone Operators and the Proximal Point Algorithm, SIAM Journal on Control and Optimization, vol.14, issue.5, pp.877-898, 1976. ,
DOI : 10.1137/0314056
Inexact and accelerated proximal point algorithms, Journal of Convex Analysis, vol.19, issue.4, pp.1167-1192, 2012. ,
Practical inexact proximal quasi-Newton method with global complexity analysis, Mathematical Programming, pp.1-35, 2014. ,
DOI : 10.1007/s10107-016-0997-3
Projected Newton-type methods in machine learning, pp.305-330, 2011. ,
Minimizing finite sums with the stochastic average gradient, Mathematical Programming, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-00860051
Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization, Mathematical Programming, 2015. ,
DOI : 10.1007/s10107-014-0839-0
A Proximal Stochastic Gradient Method with Progressive Variance Reduction, SIAM Journal on Optimization, vol.24, issue.4, pp.2057-2075, 2014. ,
DOI : 10.1137/140961791
A quasi-Newton approach to non-smooth convex optimization, Proceedings of the 25th international conference on Machine learning, ICML '08, 2008. ,
DOI : 10.1145/1390156.1390309
Regularization and variable selection via the elastic net, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.5, issue.2, pp.301-320, 2005. ,
DOI : 10.1073/pnas.201162998