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2020 – today
- 2024
[j31]Quoc Tran-Dinh
:
From Halpern's fixed-point iterations to Nesterov's accelerated interpretations for root-finding problems. Comput. Optim. Appl. 87(1): 181-218 (2024)- [j30]Quoc Tran-Dinh:
Extragradient-type methods with $\mathcal {O}\left( 1/k\right) $ last-iterate convergence rates for co-hypomonotone inclusions. J. Glob. Optim. 89(1): 197-221 (2024) - [i18]Trang H. Tran, Quoc Tran-Dinh, Lam M. Nguyen:
Shuffling Momentum Gradient Algorithm for Convex Optimization. CoRR abs/2403.03180 (2024) - 2023
- [j29]Quoc Tran-Dinh, Deyi Liu:
A new randomized primal-dual algorithm for convex optimization with fast last iterate convergence rates. Optim. Methods Softw. 38(1): 184-217 (2023) - 2022
- [j28]Deyi Liu, Volkan Cevher, Quoc Tran-Dinh:
A Newton Frank-Wolfe method for constrained self-concordant minimization. J. Glob. Optim. 83(2): 273-299 (2022) - [j27]Quoc Tran-Dinh, Ling Liang, Kim-Chuan Toh:
A New Homotopy Proximal Variable-Metric Framework for Composite Convex Minimization. Math. Oper. Res. 47(1): 508-539 (2022) - [j26]Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen:
A hybrid stochastic optimization framework for composite nonconvex optimization. Math. Program. 191(2): 1005-1071 (2022) - [j25]Quoc Tran-Dinh:
A unified convergence rate analysis of the accelerated smoothed gap reduction algorithm. Optim. Lett. 16(4): 1235-1257 (2022) - [j24]Yuzixuan Zhu, Deyi Liu, Quoc Tran-Dinh:
New Primal-Dual Algorithms for a Class of Nonsmooth and Nonlinear Convex-Concave Minimax Problems. SIAM J. Optim. 32(4): 2580-2611 (2022) - 2021
- [j23]Amarjit Budhiraja, Shu Lu, Yang Yu, Quoc Tran-Dinh:
Minimization of a class of rare event probabilities and buffered probabilities of exceedance. Ann. Oper. Res. 302(1): 49-83 (2021) - [j22]Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl:
A Lyapunov function for the combined system-optimizer dynamics in inexact model predictive control. Autom. 134: 109901 (2021) - [j21]Jingxiang Chen, Quoc Tran-Dinh, Michael R. Kosorok, Yufeng Liu:
Identifying Heterogeneous Effect Using Latent Supervised Clustering With Adaptive Fusion. J. Comput. Graph. Stat. 30(1): 43-54 (2021) - [j20]Lam M. Nguyen, Quoc Tran-Dinh, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk:
A Unified Convergence Analysis for Shuffling-Type Gradient Methods. J. Mach. Learn. Res. 22: 207:1-207:44 (2021) - [c22]Nhuong V. Nguyen, Toan N. Nguyen, Phuong Ha Nguyen, Quoc Tran-Dinh, Lam M. Nguyen, Marten van Dijk:
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes. AISTATS 2021: 1207-1215 - [c21]Trang H. Tran, Lam M. Nguyen, Quoc Tran-Dinh:
SMG: A Shuffling Gradient-Based Method with Momentum. ICML 2021: 10379-10389 - [c20]Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen:
FedDR - Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization. NeurIPS 2021: 30326-30338 - [c19]Yunsoo Ha, Sara Shashaani, Quoc Tran-Dinh:
Improved Complexity Of Trust-Region Optimization For Zeroth-Order Stochastic Oracles with Adaptive Sampling. WSC 2021: 1-12 - [i17]Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh:
Federated Learning with Randomized Douglas-Rachford Splitting Methods. CoRR abs/2103.03452 (2021) - 2020
- [j19]Tianxiao Sun, Ion Necoara, Quoc Tran-Dinh:
Composite convex optimization with global and local inexact oracles. Comput. Optim. Appl. 76(1): 69-124 (2020) - [j18]Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh:
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization. J. Mach. Learn. Res. 21: 110:1-110:48 (2020) - [j17]Deyi Liu, Quoc Tran-Dinh:
An Inexact Interior-Point Lagrangian Decomposition Algorithm with Inexact Oracles. J. Optim. Theory Appl. 185(3): 903-926 (2020) - [j16]Quoc Tran-Dinh, Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher:
An adaptive primal-dual framework for nonsmooth convex minimization. Math. Program. Comput. 12(3): 451-491 (2020) - [j15]Quoc Tran-Dinh, Yuzixuan Zhu:
Non-stationary First-Order Primal-Dual Algorithms with Faster Convergence Rates. SIAM J. Optim. 30(4): 2866-2896 (2020) - [c18]Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk, Quoc Tran-Dinh:
A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning. AISTATS 2020: 374-385 - [c17]Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter:
Transferring Optimality Across Data Distributions via Homotopy Methods. ICLR 2020 - [c16]Quoc Tran-Dinh, Nhan H. Pham, Lam M. Nguyen:
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization. ICML 2020: 9572-9582 - [c15]Quoc Tran-Dinh, Deyi Liu, Lam M. Nguyen:
Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function. NeurIPS 2020 - [i16]Deyi Liu, Volkan Cevher, Quoc Tran-Dinh:
A Newton Frank-Wolfe Method for Constrained Self-Concordant Minimization. CoRR abs/2002.07003 (2020) - [i15]Lam M. Nguyen, Quoc Tran-Dinh, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk:
A Unified Convergence Analysis for Shuffling-Type Gradient Methods. CoRR abs/2002.08246 (2020) - [i14]Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk, Quoc Tran-Dinh:
A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning. CoRR abs/2003.00430 (2020) - [i13]Marten van Dijk, Nhuong V. Nguyen, Toan N. Nguyen, Lam M. Nguyen, Quoc Tran-Dinh, Phuong Ha Nguyen:
Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise. CoRR abs/2007.09208 (2020) - [i12]Marten van Dijk, Nhuong V. Nguyen, Toan N. Nguyen, Lam M. Nguyen, Quoc Tran-Dinh, Phuong Ha Nguyen:
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes. CoRR abs/2010.14763 (2020) - [i11]Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter:
Convergence Analysis of Homotopy-SGD for non-convex optimization. CoRR abs/2011.10298 (2020) - [i10]Trang H. Tran, Lam M. Nguyen, Quoc Tran-Dinh:
Shuffling Gradient-Based Methods with Momentum. CoRR abs/2011.11884 (2020)
2010 – 2019
- 2019
- [j14]Quoc Tran-Dinh:
Proximal alternating penalty algorithms for nonsmooth constrained convex optimization. Comput. Optim. Appl. 72(1): 1-43 (2019) - [j13]Dirk A. Lorenz, Quoc Tran-Dinh:
Non-stationary Douglas-Rachford and alternating direction method of multipliers: adaptive step-sizes and convergence. Comput. Optim. Appl. 74(1): 67-92 (2019) - [j12]Chengde Qian, Quoc Tran-Dinh, Sheng Fu, Changliang Zou, Yufeng Liu:
Robust multicategory support matrix machines. Math. Program. 176(1-2): 429-463 (2019) - [j11]Quoc Tran-Dinh, Tianxiao Sun, Shu Lu:
Self-concordant inclusions: a unified framework for path-following generalized Newton-type algorithms. Math. Program. 177(1-2): 173-223 (2019) - [j10]Tianxiao Sun, Quoc Tran-Dinh:
Generalized self-concordant functions: a recipe for Newton-type methods. Math. Program. 178(1-2): 145-213 (2019) - [j9]Yuzixuan Zhu, Gábor Pataki, Quoc Tran-Dinh:
Sieve-SDP: a simple facial reduction algorithm to preprocess semidefinite programs. Math. Program. Comput. 11(3): 503-586 (2019) - [c14]Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl:
Contraction Estimates for Abstract Real-Time Algorithms for NMPC. CDC 2019: 8085-8092 - [i9]Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh:
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization. CoRR abs/1902.05679 (2019) - [i8]Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen:
A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization. CoRR abs/1907.03793 (2019) - [i7]Francisco J. Aragón Artacho, Rubén Campoy, Quoc Tran-Dinh, Phan Tu Vuong:
Using positive spanning sets to achieve stationarity with the Boosted DC Algorithm. CoRR abs/1907.11471 (2019) - 2018
- [j8]Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher:
A Single-Phase, Proximal Path-Following Framework. Math. Oper. Res. 43(4): 1326-1347 (2018) - [j7]Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher:
A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Convex Minimization. SIAM J. Optim. 28(1): 96-134 (2018) - [c13]Quoc Tran-Dinh:
Non-Ergodic Alternating Proximal Augmented Lagrangian Algorithms with Optimal Rates. NeurIPS 2018: 4816-4824 - 2017
- [j6]Quoc Tran-Dinh:
Adaptive smoothing algorithms for nonsmooth composite convex minimization. Comput. Optim. Appl. 66(3): 425-451 (2017) - [j5]Andrei Patrascu, Ion Necoara, Quoc Tran-Dinh:
Adaptive inexact fast augmented Lagrangian methods for constrained convex optimization. Optim. Lett. 11(3): 609-626 (2017) - [c12]Ahmet Alacaoglu, Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher:
Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization. NIPS 2017: 5852-5861 - 2016
- [c11]Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher:
Convex Block-sparse Linear Regression with Expanders - Provably. AISTATS 2016: 19-27 - [c10]Gergely Ódor, Yen-Huan Li, Alp Yurtsever, Ya-Ping Hsieh, Quoc Tran-Dinh, Marwa El Halabi, Volkan Cevher:
Frank-Wolfe works for non-Lipschitz continuous gradient objectives: Scalable poisson phase retrieval. ICASSP 2016: 6230-6234 - [c9]Duy Khuong Nguyen, Quoc Tran-Dinh, Tu Bao Ho:
Simplicial Nonnegative Matrix Tri-factorization: Fast Guaranteed Parallel Algorithm. ICONIP (2) 2016: 117-125 - [i6]Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher:
A single-phase, proximal path-following framework. CoRR abs/1603.01681 (2016) - [i5]Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher:
Convex block-sparse linear regression with expanders - provably. CoRR abs/1603.06313 (2016) - 2015
- [j4]Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher:
Composite self-concordant minimization. J. Mach. Learn. Res. 16: 371-416 (2015) - [c8]Sanvesh Srivastava, Volkan Cevher, Quoc Tran-Dinh, David B. Dunson:
WASP: Scalable Bayes via barycenters of subset posteriors. AISTATS 2015 - [c7]Baran Gozcu, Luca Baldassarre, Quoc Tran-Dinh, Cosimo Aprile, Volkan Cevher:
A primal-dual framework for mixtures of regularizers. EUSIPCO 2015: 240-244 - [c6]Quoc Tran-Dinh, Yen-Huan Li, Volkan Cevher:
Composite Convex Minimization Involving Self-concordant-Like Cost Functions. MCO (1) 2015: 155-168 - [c5]Alp Yurtsever, Quoc Tran-Dinh, Volkan Cevher:
A Universal Primal-Dual Convex Optimization Framework. NIPS 2015: 3150-3158 - [i4]Anastasios Kyrillidis, Luca Baldassarre, Marwa El Halabi, Quoc Tran-Dinh, Volkan Cevher:
Structured Sparsity: Discrete and Convex approaches. CoRR abs/1507.05367 (2015) - 2014
- [j3]Valentin Nedelcu, Ion Necoara, Quoc Tran-Dinh:
Computational Complexity of Inexact Gradient Augmented Lagrangian Methods: Application to Constrained MPC. SIAM J. Control. Optim. 52(5): 3109-3134 (2014) - [j2]Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher:
An Inexact Proximal Path-Following Algorithm for Constrained Convex Minimization. SIAM J. Optim. 24(4): 1718-1745 (2014) - [j1]Michael B. McCoy, Volkan Cevher, Quoc Tran-Dinh, Afsaneh Asaei, Luca Baldassarre:
Convexity in Source Separation : Models, geometry, and algorithms. IEEE Signal Process. Mag. 31(3): 87-95 (2014) - [c4]Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran-Dinh, Volkan Cevher:
Scalable Sparse Covariance Estimation via Self-Concordance. AAAI 2014: 1946-1952 - [c3]Quoc Tran-Dinh, Yen-Huan Li, Volkan Cevher:
Barrier smoothing for nonsmooth convex minimization. ICASSP 2014: 1503-1507 - [c2]Quoc Tran-Dinh, Volkan Cevher:
Constrained convex minimization via model-based excessive gap. NIPS 2014: 721-729 - [i3]Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran-Dinh, Volkan Cevher:
Scalable sparse covariance estimation via self-concordance. CoRR abs/1405.3263 (2014) - 2013
- [c1]Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher:
A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions. ICML (2) 2013: 271-279 - [i2]Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher:
Composite Self-Concordant Minimization. CoRR abs/1308.2867 (2013) - [i1]Michael B. McCoy, Volkan Cevher, Quoc Tran-Dinh, Afsaneh Asaei, Luca Baldassarre:
Convexity in source separation: Models, geometry, and algorithms. CoRR abs/1311.0258 (2013)
Coauthor Index
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