Extensions of ADMM for Separable Convex Optimization Problems with Linear Equality or Inequality Constraints
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Bingsheng He | Xiaoming Yuan | Shengjie Xu | Xiaoming Yuan | B. He | Shengjie Xu | X. Yuan
[1] Robert A. Lordo,et al. Learning from Data: Concepts, Theory, and Methods , 2001, Technometrics.
[2] Bingsheng He,et al. A new inexact alternating directions method for monotone variational inequalities , 2002, Math. Program..
[3] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[4] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[5] Jin Zhang,et al. Discerning the Linear Convergence of ADMM for Structured Convex Optimization through the Lens of Variational Analysis , 2020, J. Mach. Learn. Res..
[6] Georgios B. Giannakis,et al. Consensus-Based Distributed Support Vector Machines , 2010, J. Mach. Learn. Res..
[7] HeBingsheng,et al. On non-ergodic convergence rate of Douglas---Rachford alternating direction method of multipliers , 2015 .
[8] Bingsheng He,et al. Convergence Rate Analysis for the Alternating Direction Method of Multipliers with a Substitution Procedure for Separable Convex Programming , 2017, Math. Oper. Res..
[9] Amir Beck,et al. First-Order Methods in Optimization , 2017 .
[10] Bingsheng He,et al. A class of ADMM-based algorithms for three-block separable convex programming , 2018, Computational Optimization and Applications.
[11] Alexandre d'Aspremont,et al. Model Selection Through Sparse Max Likelihood Estimation Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data , 2022 .
[12] Bingsheng He,et al. Linearized Alternating Direction Method with Gaussian Back Substitution for Separable Convex Programming , 2011 .
[13] Jonathan Eckstein. Augmented Lagrangian and Alternating Direction Methods for Convex Optimization: A Tutorial and Some Illustrative Computational Results , 2012 .
[14] Bingsheng He,et al. The direct extension of ADMM for multi-block convex minimization problems is not necessarily convergent , 2014, Mathematical Programming.
[15] Antonin Chambolle,et al. An introduction to continuous optimization for imaging , 2016, Acta Numerica.
[16] Yuh-Jye Lee,et al. SSVM: A Smooth Support Vector Machine for Classification , 2001, Comput. Optim. Appl..
[17] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[18] R. Glowinski,et al. Numerical Methods for Nonlinear Variational Problems , 1985 .
[19] M. Powell. A method for nonlinear constraints in minimization problems , 1969 .
[20] R. Glowinski,et al. Augmented Lagrangian and Operator-Splitting Methods in Nonlinear Mechanics , 1987 .
[21] Bingsheng He,et al. Optimally linearizing the alternating direction method of multipliers for convex programming , 2019, Comput. Optim. Appl..
[22] Simon Haykin,et al. Generalized support vector machines , 1999, ESANN.
[23] M. Fortin,et al. Augmented Lagrangian methods : applications to the numerical solution of boundary-value problems , 1983 .
[24] Dustin Boswell,et al. Introduction to Support Vector Machines , 2002 .
[25] Bingsheng He,et al. On the O(1/n) Convergence Rate of the Douglas-Rachford Alternating Direction Method , 2012, SIAM J. Numer. Anal..
[26] Roland Glowinski,et al. On Alternating Direction Methods of Multipliers: A Historical Perspective , 2014, Modeling, Simulation and Optimization for Science and Technology.
[27] D. Ruppert. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .
[28] M. Hestenes. Multiplier and gradient methods , 1969 .