Douglas–Rachford splitting and ADMM for pathological convex optimization
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Wotao Yin | Yanli Liu | Ernest K. Ryu | W. Yin | Yanli Liu
[1] H. Attouch. A General Duality Principle for the Sum of Two Operators 1 , 1996 .
[2] Masakazu Muramatsu,et al. A facial reduction algorithm for finding sparse SOS representations , 2010, Oper. Res. Lett..
[3] Stefano Di Cairano,et al. Infeasibility detection in alternating direction method of multipliers for convex quadratic programs , 2014, 53rd IEEE Conference on Decision and Control.
[4] J. Borwein,et al. Facial reduction for a cone-convex programming problem , 1981, Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics.
[5] Dmitriy Drusvyatskiy,et al. The Many Faces of Degeneracy in Conic Optimization , 2017, Found. Trends Optim..
[6] Henry Wolkowicz,et al. Strong Duality for Semidefinite Programming , 1997, SIAM J. Optim..
[7] D. Gabay. Applications of the method of multipliers to variational inequalities , 1983 .
[8] Stephen P. Boyd,et al. Graph Implementations for Nonsmooth Convex Programs , 2008, Recent Advances in Learning and Control.
[9] H. H. Rachford,et al. On the numerical solution of heat conduction problems in two and three space variables , 1956 .
[10] Heinz H. Bauschke,et al. On the Range of the Douglas-Rachford Operator , 2014, Math. Oper. Res..
[11] Henry Wolkowicz,et al. Strong duality and minimal representations for cone optimization , 2012, Computational Optimization and Applications.
[12] Heinz H. Bauschke,et al. The Douglas-Rachford Algorithm for Two (Not Necessarily Intersecting) Affine Subspaces , 2015, SIAM J. Optim..
[13] Shuzhong Zhang,et al. Duality Results for Conic Convex Programming , 1997 .
[14] Heinz H. Bauschke,et al. Finding best approximation pairs relative to two closed convex sets in Hilbert spaces , 2004, J. Approx. Theory.
[15] Patrick L. Combettes,et al. Proximal Splitting Methods in Signal Processing , 2009, Fixed-Point Algorithms for Inverse Problems in Science and Engineering.
[16] Gábor Pataki. A Simple Derivation of a Facial Reduction Algorithm and Extended Dual Systems , .
[17] Z. Luo,et al. Conic convex programming and self-dual embedding , 1998 .
[18] Wotao Yin,et al. An Envelope for Davis–Yin Splitting and Strict Saddle-Point Avoidance , 2018, J. Optim. Theory Appl..
[19] Wotao Yin,et al. Faster Convergence Rates of Relaxed Peaceman-Rachford and ADMM Under Regularity Assumptions , 2014, Math. Oper. Res..
[20] Jonathan M. Borwein,et al. The Cyclic Douglas-Rachford Method for Inconsistent Feasibility Problems , 2013, 1310.2195.
[21] Heinz H. Bauschke,et al. The method of cyclic projections for closed convex sets in Hilbert space , 1997 .
[22] Bolor Jargalsaikhan,et al. Linear conic programming: genericity and stability , 2015 .
[23] Masakazu Muramatsu,et al. Strange behaviors of interior-point methods for solving semidefinite programming problems in polynomial optimization , 2012, Comput. Optim. Appl..
[24] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[25] Damek Davis,et al. Convergence Rate Analysis of Primal-Dual Splitting Schemes , 2014, SIAM J. Optim..
[26] Damek Davis,et al. Convergence Rate Analysis of Several Splitting Schemes , 2014, 1406.4834.
[27] A. Tucker,et al. Linear Inequalities And Related Systems , 1956 .
[28] A. Pazy. Asymptotic behavior of contractions in hilbert space , 1971 .
[29] Hayato Waki,et al. How to generate weakly infeasible semidefinite programs via Lasserre’s relaxations for polynomial optimization , 2011, Optimization Letters.
[30] Kim-Chuan Toh,et al. On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming , 2018, Math. Program..
[31] Ernest K. Ryu. Cosmic divergence, weak cosmic convergence, and fixed points at infinity , 2017, Journal of Fixed Point Theory and Applications.
[32] Dimitri P. Bertsekas,et al. On the Douglas—Rachford splitting method and the proximal point algorithm for maximal monotone operators , 1992, Math. Program..
[33] Dmitriy Drusvyatskiy,et al. A note on alternating projections for ill-posed semidefinite feasibility problems , 2017, Math. Program..
[34] Heinz H. Bauschke,et al. Affine Nonexpansive Operators, Attouch–Théra Duality and the Douglas–Rachford Algorithm , 2016, 1603.09418.
[35] H. H. Rachford,et al. The Numerical Solution of Parabolic and Elliptic Differential Equations , 1955 .
[36] Wotao Yin,et al. On the Global and Linear Convergence of the Generalized Alternating Direction Method of Multipliers , 2016, J. Sci. Comput..
[37] Minghui Liu,et al. Exact duals and short certificates of infeasibility and weak infeasibility in conic linear programming , 2015, Math. Program..
[38] Wotao Yin,et al. A new use of Douglas–Rachford splitting for identifying infeasible, unbounded, and pathological conic programs , 2019, Math. Program..
[39] M. Fortin,et al. On decomposition - coordination methods using an augmented Lagrangian , 1983 .
[40] Michael J. Todd,et al. Infeasible-start primal-dual methods and infeasibility detectors for nonlinear programming problems , 1999, Math. Program..
[41] Heinz H. Bauschke,et al. On the Douglas–Rachford algorithm , 2016, Mathematical Programming.
[42] J. Borwein,et al. Regularizing the Abstract Convex Program , 1981 .
[43] Maretsugu Yamasaki. Some generalizations of duality theorems in mathematical programming problems , 1969 .
[44] Wotao Yin,et al. A New Use of Douglas-Rachford Splitting and ADMM for Identifying Infeasible, Unbounded, and Pathological Conic Programs , 2017, ArXiv.
[45] P. L. Combettes,et al. Solving monotone inclusions via compositions of nonexpansive averaged operators , 2004 .
[46] Pablo A. Parrilo,et al. Computation with Polynomial Equations and Inequalities Arising in Combinatorial Optimization , 2009, 0909.0808.
[47] Gábor Pataki,et al. Sieve-SDP: a simple facial reduction algorithm to preprocess semidefinite programs , 2017, Mathematical Programming Computation.
[48] Heinz H. Bauschke,et al. On a result of Pazy concerning the asymptotic behaviour of nonexpansive mappings , 2015, 1505.04129.
[49] Motakuri V. Ramana,et al. An exact duality theory for semidefinite programming and its complexity implications , 1997, Math. Program..
[50] Heinz H. Bauschke,et al. Generalized Solutions for the Sum of Two Maximally Monotone Operators , 2013, SIAM J. Control. Optim..
[51] M. Théra,et al. Generalized sums of monotone operators , 1999 .
[52] Simon P. Schurr,et al. Preprocessing and Regularization for Degenerate Semidefinite Programs , 2013 .
[53] R. Glowinski,et al. Sur l'approximation, par éléments finis d'ordre un, et la résolution, par pénalisation-dualité d'une classe de problèmes de Dirichlet non linéaires , 1975 .
[54] J. Borwein,et al. Characterizations of optimality without constraint qualification for the abstract convex program , 1982 .
[55] R. Rockafellar. Convex Analysis: (pms-28) , 1970 .
[56] Matthew K. Tam,et al. DOUGLAS–RACHFORD FEASIBILITY METHODS FOR MATRIX COMPLETION PROBLEMS , 2013, The ANZIAM Journal.
[57] Frank Permenter,et al. Solving Conic Optimization Problems via Self-Dual Embedding and Facial Reduction: A Unified Approach , 2017, SIAM J. Optim..
[58] Pablo A. Parrilo,et al. Basis selection for SOS programs via facial reduction and polyhedral approximations , 2014, 53rd IEEE Conference on Decision and Control.
[59] Panagiotis Patrinos,et al. Forward–backward quasi-Newton methods for nonsmooth optimization problems , 2016, Computational Optimization and Applications.
[60] Paul Tseng. Some convex programs without a duality gap , 2009, Math. Program..
[61] R. Rockafellar. Conjugate Duality and Optimization , 1987 .
[62] Johan Löfberg,et al. Pre- and Post-Processing Sum-of-Squares Programs in Practice , 2009, IEEE Transactions on Automatic Control.
[63] J. Farkas. Theorie der einfachen Ungleichungen. , 1902 .
[64] Alberto Bemporad,et al. Douglas-rachford splitting: Complexity estimates and accelerated variants , 2014, 53rd IEEE Conference on Decision and Control.
[65] G. Pataki. Strong Duality in Conic Linear Programming: Facial Reduction and Extended Duals , 2013, 1301.7717.
[66] Gábor Pataki,et al. Bad Semidefinite Programs: They All Look the Same , 2011, SIAM J. Optim..
[67] Jonathan Eckstein. Splitting methods for monotone operators with applications to parallel optimization , 1989 .
[68] R. Glowinski,et al. Numerical Methods for Nonlinear Variational Problems , 1985 .
[69] John N. Tsitsiklis,et al. Parallel and distributed computation , 1989 .
[70] B. Mercier,et al. A dual algorithm for the solution of nonlinear variational problems via finite element approximation , 1976 .
[71] Bruno F. Lourenço,et al. Solving SDP completely with an interior point oracle , 2021, Optim. Methods Softw..
[72] Jonathan Eckstein,et al. Understanding the Convergence of the Alternating Direction Method of Multipliers: Theoretical and Computational Perspectives , 2015 .
[73] M. Fortin,et al. Augmented Lagrangian methods : applications to the numerical solution of boundary-value problems , 1983 .
[74] R. Kellogg. A nonlinear alternating direction method , 1969 .
[75] B. Mercier. Inequations variationnelles de la mécanique , 1980 .
[76] Heinz H. Bauschke,et al. Convex Analysis and Monotone Operator Theory in Hilbert Spaces , 2011, CMS Books in Mathematics.
[77] Walaa M. Moursi,et al. The Forward–Backward Algorithm and the Normal Problem , 2016, J. Optim. Theory Appl..
[78] K. S. Kretschmer,et al. Programmes in Paired Spaces , 1961, Canadian Journal of Mathematics.
[79] Heinz H. Bauschke,et al. Attouch-Théra duality revisited: Paramonotonicity and operator splitting , 2011, J. Approx. Theory.
[80] Masakazu Muramatsu,et al. A structural geometrical analysis of weakly infeasible SDPs , 2015 .
[81] Patrick L. Combettes,et al. Monotone operator theory in convex optimization , 2018, Math. Program..
[82] Ming Yan,et al. Self Equivalence of the Alternating Direction Method of Multipliers , 2014, 1407.7400.
[83] Dimitri P. Bertsekas,et al. Convex Optimization Theory , 2009 .
[84] A. Bemporad,et al. Forward-backward truncated Newton methods for convex composite optimization , 2014, 1402.6655.
[85] Pablo A. Parrilo,et al. Partial facial reduction: simplified, equivalent SDPs via approximations of the PSD cone , 2014, Math. Program..
[86] W. Fenchel. Convex cones, sets, and functions , 1953 .
[87] Stephen P. Boyd,et al. Infeasibility Detection in the Alternating Direction Method of Multipliers for Convex Optimization , 2018, Journal of Optimization Theory and Applications.
[88] P. Lions,et al. Splitting Algorithms for the Sum of Two Nonlinear Operators , 1979 .
[89] Michel Théra,et al. Enlargements and Sums of Monotone Operators , 2001 .
[90] Masakazu Muramatsu,et al. Facial Reduction Algorithms for Conic Optimization Problems , 2012, Journal of Optimization Theory and Applications.
[91] Jonathan M. Borwein,et al. Global behavior of the Douglas–Rachford method for a nonconvex feasibility problem , 2015, J. Glob. Optim..
[92] Paul Tseng,et al. Hankel Matrix Rank Minimization with Applications to System Identification and Realization , 2013, SIAM J. Matrix Anal. Appl..
[93] Kim-Chuan Toh,et al. A note on the convergence of ADMM for linearly constrained convex optimization problems , 2015, Computational Optimization and Applications.
[94] H. Attouch,et al. Variational Sum of Monotone Operators , 1994 .
[95] James Renegar,et al. Computing approximate solutions for convex conic systems of constraints , 2000, Math. Program..
[96] Stephen P. Boyd,et al. OSQP: an operator splitting solver for quadratic programs , 2017, 2018 UKACC 12th International Conference on Control (CONTROL).
[97] Mattias Fält,et al. Envelope Functions: Unifications and Further Properties , 2016, J. Optim. Theory Appl..