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This paper considers a generic convex minimization template with affine constraints over a compact domain, which covers key semidefinite programming applications.
An algorithm for quadratic programming
M. Frank and P. Wolfe · 1956
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N. Komodakis and J.-C. Pesquet · 2015
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Universal gradient methods for convex optimization problems
Y. Nesterov · 2015
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A universal primal-dual convex optimization framework
A. Yurtsever, Q. Tran-Dinh, and V. Cevher · 2015
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C. Dünner, S. Forte, M. Takác, and M. Jaggi · 2016
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Conditional gradient sliding for convex optimization
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Y. LeCun and C. Cortes · 2016
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Greedy direction method of multiplier for MAP inference of large output domain
X. Huang, I. E.-H. Yen, R. Zhang, Q. Huang, P. Ravikumar, and I. S. Dhillon · 2017
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D. G. Mixon, S. Villar, and R. Ward · 2017
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Sketchy decisions: Convex low-rank matrix optimization with optimal storage
A. Yurtsever, M. Udell, J. Tropp, and V. Cevher · 2017
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Deterministic guarantees for Burer–Monteiro factorizations of smooth semidefinite programs
N. Boumal, V. Voroninski, and A. Bandeira · 2018
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Frank-Wolfe splitting via augmented Lagrangian method
G. Gidel, F. Pedregosa, and S. Lacoste-Julien · 2018
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Primer on monotone operator methods
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Pajek datasets, http://vlado.fmf.uni-lj.si/pub/networks/data/
V. Batagelj and A. Mrvar
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Smooth minimization of non-smooth functions
Y. Nesterov
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Excessive gap technique in nonsmooth convex minimization
Y. Nesterov
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Gset random graphs, https://www.cise.ufl.edu/research/sparse/matrices/gset/
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On the non-ergodic convergence rate of an inexact augmented Lagrangian framework for composite convex programming
Y.-F. Liu, X. Liu, and S. Ma · 2018
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A smooth primal-dual optimization framework for nonsmooth composite convex minimization
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A. Yurtsever, O. Fercoq, F. Locatello, and V. Cevher · 2018
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