Quoc Tran-Dinh
Quoc Tran-Dinh
Department of Statistics and Operations Research, UNC
Verified email at - Homepage
Cited by
Cited by
Extragradient algorithms extended to equilibrium problems¶
Q Tran-Dinh, M Le Dung, VH Nguyen
Optimization 57 (6), 749-776, 2008
Learning with tensors: a framework based on convex optimization and spectral regularization
M Signoretto, Q Tran-Dinh, L De Lathauwer, JAK Suykens
Machine Learning 94, 303-351, 2014
Combining convex–concave decompositions and linearization approaches for solving BMIs, with application to static output feedback
Q Tran-Dinh, S Gumussoy, W Michiels, M Diehl
IEEE Transactions on Automatic Control 57 (6), 1377-1390, 2011
WASP: Scalable Bayes via barycenters of subset posteriors
S Srivastava, V Cevher, Q Tran-Dinh, D Dunson
Artificial Intelligence and Statistics, 912-920, 2015
Local convergence of sequential convex programming for nonconvex optimization
Q Tran-Dinh, M Diehl
Recent Advances in Optimization and its Applications in Engineering: The …, 2010
Dual extragradient algorithms extended to equilibrium problems
Q Tran-Dinh, PN Anh, LD Muu
Journal of Global Optimization 52 (1), 139-159, 2012
ProxSARAH: An efficient algorithmic framework for stochastic composite nonconvex optimization
NH Pham, LM Nguyen, DT Phan, Q Tran-Dinh
Journal of Machine Learning Research 21 (110), 1-48, 2020
Regularization algorithms for solving monotone Ky Fan inequalities with application to a Nash-Cournot equilibrium model
M Le Dung, Q Tran-Dinh
Journal of optimization theory and applications 142 (1), 185-204, 2009
A hybrid stochastic optimization framework for composite nonconvex optimization
Q Tran-Dinh, NH Pham, DT Phan, LM Nguyen
Mathematical Programming, 1-67, 2021
Computational complexity of inexact gradient augmented Lagrangian methods: application to constrained MPC
V Nedelcu, I Necoara, Q Tran-Dinh
SIAM Journal on Control and Optimization 52 (5), 3109-3134, 2014
Composite self-concordant minimization.
Q Tran-Dinh, A Kyrillidis, V Cevher
J. Mach. Learn. Res. 16 (1), 371-416, 2015
A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Convex Minimization
Q Tran-Dinh, O Fercoq, V Cevher
SIAM Journal on Optimization, 28(1), 96–134 (2018), 2015
Time-optimal path following for robots with convex–concave constraints using sequential convex programming
F Debrouwere, W Van Loock, G Pipeleers, Q Tran-Dinh, M Diehl, ...
IEEE Transactions on Robotics 29 (6), 1485-1495, 2013
Generalized self-concordant functions: a recipe for newton-type methods
T Sun, Q Tran-Dinh
Mathematical Programming 178 (1), 145-213, 2019
Adjoint-based predictor-corrector sequential convex programming for parametric nonlinear optimization
Q Tran-Dinh, C Savorgnan, M Diehl
SIAM Journal on Optimization 22 (4), 1258-1284, 2012
A unified convergence analysis for shuffling-type gradient methods
LM Nguyen, Q Tran-Dinh, DT Phan, PH Nguyen, M Van Dijk
Journal of Machine Learning Research 22 (207), 1-44, 2021
A universal primal-dual convex optimization framework
A Yurtsever, Q Tran-Dinh, V Cevher
Advances in Neural Information Processing Systems 28, 2015
Convexity in source separation: Models, geometry, and algorithms
MB McCoy, V Cevher, Q Tran-Dinh, A Asaei, L Baldassarre
IEEE Signal Processing Magazine 31 (3), 87-95, 2014
Sequential convex programming methods for solving nonlinear optimization problems with DC constraints
Q Tran-Dinh, M Diehl
arXiv preprint arXiv:1107.5841, 2011
An inexact perturbed path-following method for Lagrangian decomposition in large-scale separable convex optimization
Q Tran-Dinh, I Necoara, C Savorgnan, M Diehl
SIAM Journal on Optimization 23 (1), 95-125, 2013
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