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This paper describes the Conic Operator Splitting Method (COSMO) solver, an operator splitting algorithm for convex optimisation problems with quadratic objective function and conic constraints.
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A Miele, EE Cragg, and AV Levy · 1971
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Jonathan Eckstein and Dimitri P Bertsekas · 1992
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Sanjay Mehrotra · 1992
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Stephen Boyd, Laurent El Ghaoui, Eric Feron, and Venkataramanan Balakrishnan · 1994
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Interior point methods in semidefinite programming with applications to combinatorial optimization
Farid Alizadeh · 1995
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Support-vector networks
Corinna Cortes and Vladimir Vapnik · 1995
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Symmetric quasidefinite matrices
Robert J. Vanderbei · 1995
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An interior-point method for semidefinite programming
Christoph Helmberg, Franz Rendl, Robert J Vanderbei, and Henryfa Wolkowicz · 1996
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Anne Greenbaum · 1997
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Stephen J Wright · 1997
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Farid Alizadeh, Jean-Pierre A Haeberly, and Michael L Overton · 1998
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LAPACK Users’ guide
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SDPLIB 1.2, a library of semidefinite programming test problems
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Decomposition methods for large scale lp decoding
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Implementation of a large-scale optimal power flow solver based on semidefinite programming
Daniel K Molzahn, Jesse T Holzer, Bernard C Lesieutre, and Christopher L DeMarco · 2013
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Diagonal scaling in Douglas-Rachford splitting and ADMM
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Proximal algorithms
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A 3d map of the human genome at kilobase resolution reveals principles of chromatin looping
Suhas SP Rao, Miriam H Huntley, Neva C Durand, Elena K Stamenova, Ivan D Bochkov, James T Robinson, Adrian L Sanborn, Ido Machol, Arina D Omer, Eric S Lander, et al · 2014
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Decomposition in conic optimization with partially separable structure
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Jos F Sturm · 1999
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Kim-Chuan Toh, Michael J Todd, and Reha H Tütüncü · 1999
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Numerical optimization
Stephen Wright and Jorge Nocedal · 1999
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Seventh dimacs implementation challenge: Semidefinite and related problems, 2000
D Johnson, G Pataki, and F Alizadeh · 2000
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Operations research games: A survey
Peter Borm, Herbert Hamers, and Ruud Hendrickx · 2001
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Exploiting sparsity in semidefinite programming via matrix completion I: General framework
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Convex optimization in Julia
Madeleine Udell, Karanveer Mohan, David Zeng, Jenny Hong, Steven Diamond, and Stephen Boyd · 2014
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CHOMPACK: A python package for chordal matrix computations, 2015
M. S. Andersen and L. Vandenberghe · 2015
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Suitesparse: A suite of sparse matrix software
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Metric selection in fast dual forward-backward splitting
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Intel® math kernel library PARDISO* for intel® xeon phi tm manycore coprocessor
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Chordal graphs and semidefinite optimization
Lieven Vandenberghe, Martin S Andersen, et al · 2015
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Conic optimization via operator splitting and homogeneous self-dual embedding
B. O’Donoghue, E. Chu, N. Parikh, and S. Boyd · 2016
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Multi-period trading via convex optimization
Stephen Boyd, Enzo Busseti, Steve Diamond, Ronald N Kahn, Kwangmoo Koh, Peter Nystrup, Jan Speth, et al · 2017
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Julia: A fresh approach to numerical computing
Jeff Bezanson, Alan Edelman, Stefan Karpinski, and Viral B Shah · 2017
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Infeasibility detection in the alternating direction method of multipliers for convex optimization
G. Banjac, P. Goulart, B. Stellato, and S. Boyd · 2017
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JuMP: A modeling language for mathematical optimization
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The MOSEK optimization toolbox for MATLAB manual. Version 8.0 (revision 57), 2017
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OSQP: An Operator Splitting Solver for Quadratic Programs
B. Stellato, G. Banjac, P. Goulart, A. Bemporad, and S. Boyd · 2018
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Optimal approximation of doubly stochastic matrices
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Efficient semidefinite programming with approximate admm
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Chordal decomposition in operator-splitting methods for sparse semidefinite programs
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MathOptInterface: a data structure for mathematical optimization problems
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