Accelerated Algorithms for Unconstrained Convex Optimization
暂无分享,去创建一个
[1] Huan Li,et al. On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent , 2018, J. Mach. Learn. Res..
[2] Yin Tat Lee,et al. Near-optimal method for highly smooth convex optimization , 2018, COLT.
[3] Xiaoming Yuan,et al. An alternating direction method of multipliers with a worst-case O(1/n2) convergence rate , 2018, Mathematics of Computation.
[4] Zhouchen Lin,et al. Accelerated Alternating Direction Method of Multipliers: An Optimal O(1 / K) Nonergodic Analysis , 2016, Journal of Scientific Computing.
[5] Ion Necoara,et al. Complexity of first-order inexact Lagrangian and penalty methods for conic convex programming , 2015, Optim. Methods Softw..
[6] Y. Nesterov,et al. Linear convergence of first order methods for non-strongly convex optimization , 2015, Math. Program..
[7] Yi Zhou,et al. An optimal randomized incremental gradient method , 2015, Mathematical Programming.
[8] Zaïd Harchaoui,et al. Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice , 2017, J. Mach. Learn. Res..
[9] Zhouchen Lin,et al. Convergence Rates Analysis of The Quadratic Penalty Method and Its Applications to Decentralized Distributed Optimization , 2017, 1711.10802.
[10] Yangyang Xu,et al. Accelerated First-Order Primal-Dual Proximal Methods for Linearly Constrained Composite Convex Programming , 2016, SIAM J. Optim..
[11] Stephen P. Boyd,et al. Linear Convergence and Metric Selection for Douglas-Rachford Splitting and ADMM , 2014, IEEE Transactions on Automatic Control.
[12] Zeyuan Allen Zhu,et al. Linear Coupling: An Ultimate Unification of Gradient and Mirror Descent , 2014, ITCS.
[13] Antonin Chambolle,et al. On the ergodic convergence rates of a first-order primal–dual algorithm , 2016, Math. Program..
[14] Zeyuan Allen Zhu,et al. Optimal Black-Box Reductions Between Optimization Objectives , 2016, NIPS.
[15] Andre Wibisono,et al. A variational perspective on accelerated methods in optimization , 2016, Proceedings of the National Academy of Sciences.
[16] Shuicheng Yan,et al. Fast Proximal Linearized Alternating Direction Method of Multiplier with Parallel Splitting , 2015, AAAI.
[17] Mikael Johansson,et al. Convergence Analysis of Approximate Primal Solutions in Dual First-Order Methods , 2015, SIAM J. Optim..
[18] Stephen P. Boyd,et al. A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights , 2014, J. Mach. Learn. Res..
[19] Ion Necoara,et al. Iteration complexity analysis of dual first-order methods for conic convex programming , 2014, Optim. Methods Softw..
[20] Benjamin Recht,et al. Analysis and Design of Optimization Algorithms via Integral Quadratic Constraints , 2014, SIAM J. Optim..
[21] Damek Davis,et al. Convergence Rate Analysis of Several Splitting Schemes , 2014, 1406.4834.
[22] Bingsheng He,et al. On non-ergodic convergence rate of Douglas–Rachford alternating direction method of multipliers , 2014, Numerische Mathematik.
[23] Francis R. Bach,et al. From Averaging to Acceleration, There is Only a Step-size , 2015, COLT.
[24] Elad Hazan,et al. Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets , 2014, ICML.
[25] Yunmei Chen,et al. An Accelerated Linearized Alternating Direction Method of Multipliers , 2014, SIAM J. Imaging Sci..
[26] Emmanuel J. Candès,et al. Adaptive Restart for Accelerated Gradient Schemes , 2012, Foundations of Computational Mathematics.
[27] Yurii Nesterov,et al. First-order methods of smooth convex optimization with inexact oracle , 2013, Mathematical Programming.
[28] Ion Necoara,et al. Rate Analysis of Inexact Dual First-Order Methods Application to Dual Decomposition , 2014, IEEE Transactions on Automatic Control.
[29] Marc Teboulle,et al. Rate of Convergence Analysis of Decomposition Methods Based on the Proximal Method of Multipliers for Convex Minimization , 2014, SIAM J. Optim..
[30] Zhixun Su,et al. Linearized alternating direction method with parallel splitting and adaptive penalty for separable convex programs in machine learning , 2013, Machine Learning.
[31] Yunmei Chen,et al. Optimal Primal-Dual Methods for a Class of Saddle Point Problems , 2013, SIAM J. Optim..
[32] Alberto Bemporad,et al. An Accelerated Dual Gradient-Projection Algorithm for Embedded Linear Model Predictive Control , 2014, IEEE Transactions on Automatic Control.
[33] Martin Jaggi,et al. Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization , 2013, ICML.
[34] Renato D. C. Monteiro,et al. Iteration-complexity of first-order penalty methods for convex programming , 2013, Math. Program..
[35] G. Sapiro,et al. A collaborative framework for 3D alignment and classification of heterogeneous subvolumes in cryo-electron tomography. , 2013, Journal of structural biology.
[36] Yurii Nesterov,et al. Gradient methods for minimizing composite functions , 2012, Mathematical Programming.
[37] Xiangfeng Wang,et al. The Linearized Alternating Direction Method of Multipliers for Dantzig Selector , 2012, SIAM J. Sci. Comput..
[38] Bingsheng He,et al. On the O(1/n) Convergence Rate of the Douglas-Rachford Alternating Direction Method , 2012, SIAM J. Numer. Anal..
[39] Mark W. Schmidt,et al. Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization , 2011, NIPS.
[40] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[41] Julien Mairal,et al. Convex optimization with sparsity-inducing norms , 2011 .
[42] Antonin Chambolle,et al. A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging , 2011, Journal of Mathematical Imaging and Vision.
[43] Tony F. Chan,et al. A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science , 2010, SIAM J. Imaging Sci..
[44] Martin Jaggi,et al. A Simple Algorithm for Nuclear Norm Regularized Problems , 2010, ICML.
[45] Xi Chen,et al. Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso , 2010, ArXiv.
[46] Mohamed-Jalal Fadili,et al. Total Variation Projection With First Order Schemes , 2011, IEEE Transactions on Image Processing.
[47] Daniel Cremers,et al. An algorithm for minimizing the Mumford-Shah functional , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[48] Jean-Philippe Vert,et al. Group lasso with overlap and graph lasso , 2009, ICML '09.
[49] M. Baes. Estimate sequence methods: extensions and approximations , 2009 .
[50] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[51] Yurii Nesterov,et al. Accelerating the cubic regularization of Newton’s method on convex problems , 2005, Math. Program..
[52] Yurii Nesterov,et al. Cubic regularization of Newton method and its global performance , 2006, Math. Program..
[53] Yurii Nesterov,et al. Smooth minimization of non-smooth functions , 2005, Math. Program..
[54] Yurii Nesterov,et al. Introductory Lectures on Convex Optimization - A Basic Course , 2014, Applied Optimization.
[55] Bingsheng He,et al. A new inexact alternating directions method for monotone variational inequalities , 2002, Math. Program..
[56] Convergence rate results for a penalty function method , 1978 .
[57] B. T. Polyak,et al. The convergence rate of the penalty function method , 1971 .
[58] D. Luenberger. Convergence rate of a penalty-function scheme , 1971 .
[59] Philip Wolfe,et al. An algorithm for quadratic programming , 1956 .