Quoc Tran-Dinh

77 papers A* 9A 4Misc 3Journal 53Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Correction to: From Halpern's fixed-point iterations to Nesterov's accelerated interpretations for root-finding problems. Comput. Optim. Appl. Quoc Tran-Dinh
2026	J	`jnl`	Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems. Math. Oper. Res. Quoc Tran-Dinh, Yang Luo
2026	J	`jnl`	Unbiased and Biased Variance-Reduced Forward-Reflected-Backward Splitting Methods for Stochastic Composite Inclusions. CoRR Quoc Tran-Dinh, Nghia Nguyen-Trung
2025	J	`jnl`	VFOSA: Variance-Reduced Fast Operator Splitting Algorithms for Generalized Equations. J. Mach. Learn. Res. Quoc Tran-Dinh
2025	A*	`conf`	Variance-Reduced Forward-Reflected-Backward Splitting Methods for Nonmonotone Generalized Equations. ICML Quoc Tran-Dinh
2024	J	`jnl`	Extragradient-type methods with $\mathcal {O}\left( 1/k\right) $ last-iterate convergence rates for co-hypomonotone inclusions. J. Glob. Optim. Quoc Tran-Dinh
2024	J	`jnl`	From Halpern's fixed-point iterations to Nesterov's accelerated interpretations for root-finding problems. Comput. Optim. Appl. Quoc Tran-Dinh
2024	A*	`conf`	Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization. NeurIPS Quoc Tran-Dinh, Trang H. Tran, Lam M. Nguyen
2024	J	`jnl`	Shuffling Momentum Gradient Algorithm for Convex Optimization. CoRR Trang H. Tran, Quoc Tran-Dinh, Lam M. Nguyen
2023	J	`jnl`	A new randomized primal-dual algorithm for convex optimization with fast last iterate convergence rates. Optim. Methods Softw. Quoc Tran-Dinh, Deyi Liu
2022	J	`jnl`	A New Homotopy Proximal Variable-Metric Framework for Composite Convex Minimization. Math. Oper. Res. Quoc Tran-Dinh, Ling Liang, Kim-Chuan Toh
2022	J	`jnl`	A Newton Frank-Wolfe method for constrained self-concordant minimization. J. Glob. Optim. Deyi Liu, Volkan Cevher, Quoc Tran-Dinh
2022	J	`jnl`	A hybrid stochastic optimization framework for composite nonconvex optimization. Math. Program. Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen
2022	J	`jnl`	A unified convergence rate analysis of the accelerated smoothed gap reduction algorithm. Optim. Lett. Quoc Tran-Dinh
2022	J	`jnl`	New Primal-Dual Algorithms for a Class of Nonsmooth and Nonlinear Convex-Concave Minimax Problems. SIAM J. Optim. Yuzixuan Zhu, Deyi Liu, Quoc Tran-Dinh
2021	J	`jnl`	A Lyapunov function for the combined system-optimizer dynamics in inexact model predictive control. Autom. Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl
2021	J	`jnl`	A Unified Convergence Analysis for Shuffling-Type Gradient Methods. J. Mach. Learn. Res. Lam M. Nguyen, Quoc Tran-Dinh, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk
2021	A*	`conf`	FedDR - Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization. NeurIPS Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen
2021	J	`jnl`	Federated Learning with Randomized Douglas-Rachford Splitting Methods. CoRR Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh
2021	A	`conf`	Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes. AISTATS Nhuong V. Nguyen, Toan N. Nguyen, Phuong Ha Nguyen, Quoc Tran-Dinh, Lam M. Nguyen, Marten van Dijk
2021	J	`jnl`	Identifying Heterogeneous Effect Using Latent Supervised Clustering With Adaptive Fusion. J. Comput. Graph. Stat. Jingxiang Chen, Quoc Tran-Dinh, Michael R. Kosorok, Yufeng Liu
2021	Misc	`conf`	Improved Complexity Of Trust-Region Optimization For Zeroth-Order Stochastic Oracles with Adaptive Sampling. WSC Yunsoo Ha, Sara Shashaani, Quoc Tran-Dinh
2021	J	`jnl`	Minimization of a class of rare event probabilities and buffered probabilities of exceedance. Ann. Oper. Res. Amarjit Budhiraja, Shu Lu, Yang Yu, Quoc Tran-Dinh
2021	A*	`conf`	SMG: A Shuffling Gradient-Based Method with Momentum. ICML Trang H. Tran, Lam M. Nguyen, Quoc Tran-Dinh
2020	A	`conf`	A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning. AISTATS Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk, Quoc Tran-Dinh
2020	J	`jnl`	A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning. CoRR Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk, Quoc Tran-Dinh
2020	J	`jnl`	A Newton Frank-Wolfe Method for Constrained Self-Concordant Minimization. CoRR Deyi Liu, Volkan Cevher, Quoc Tran-Dinh
2020	J	`jnl`	A Unified Convergence Analysis for Shuffling-Type Gradient Methods. CoRR Lam M. Nguyen, Quoc Tran-Dinh, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk
2020	J	`jnl`	An Inexact Interior-Point Lagrangian Decomposition Algorithm with Inexact Oracles. J. Optim. Theory Appl. Deyi Liu, Quoc Tran-Dinh
2020	J	`jnl`	An adaptive primal-dual framework for nonsmooth convex minimization. Math. Program. Comput. Quoc Tran-Dinh, Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher
2020	J	`jnl`	Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise. CoRR Marten van Dijk, Nhuong V. Nguyen, Toan N. Nguyen, Lam M. Nguyen, Quoc Tran-Dinh, Phuong Ha Nguyen
2020	J	`jnl`	Composite convex optimization with global and local inexact oracles. Comput. Optim. Appl. Tianxiao Sun, Ion Necoara, Quoc Tran-Dinh
2020	J	`jnl`	Convergence Analysis of Homotopy-SGD for non-convex optimization. CoRR Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter
2020	J	`jnl`	Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes. CoRR Marten van Dijk, Nhuong V. Nguyen, Toan N. Nguyen, Lam M. Nguyen, Quoc Tran-Dinh, Phuong Ha Nguyen
2020	A*	`conf`	Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function. NeurIPS Quoc Tran-Dinh, Deyi Liu, Lam M. Nguyen
2020	J	`jnl`	Non-stationary First-Order Primal-Dual Algorithms with Faster Convergence Rates. SIAM J. Optim. Quoc Tran-Dinh, Yuzixuan Zhu
2020	J	`jnl`	ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization. J. Mach. Learn. Res. Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh
2020	J	`jnl`	Shuffling Gradient-Based Methods with Momentum. CoRR Trang H. Tran, Lam M. Nguyen, Quoc Tran-Dinh
2020	A*	`conf`	Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization. ICML Quoc Tran-Dinh, Nhan H. Pham, Lam M. Nguyen
2020	A*	`conf`	Transferring Optimality Across Data Distributions via Homotopy Methods. ICLR Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter
2019	J	`jnl`	A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization. CoRR Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen
2019	—	`conf`	Contraction Estimates for Abstract Real-Time Algorithms for NMPC. CDC Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl
2019	J	`jnl`	Generalized self-concordant functions: a recipe for Newton-type methods. Math. Program. Tianxiao Sun, Quoc Tran-Dinh
2019	J	`jnl`	Non-stationary Douglas-Rachford and alternating direction method of multipliers: adaptive step-sizes and convergence. Comput. Optim. Appl. Dirk A. Lorenz, Quoc Tran-Dinh
2019	J	`jnl`	ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization. CoRR Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh
2019	J	`jnl`	Proximal alternating penalty algorithms for nonsmooth constrained convex optimization. Comput. Optim. Appl. Quoc Tran-Dinh
2019	J	`jnl`	Robust multicategory support matrix machines. Math. Program. Chengde Qian, Quoc Tran-Dinh, Sheng Fu, Changliang Zou, Yufeng Liu
2019	J	`jnl`	Self-concordant inclusions: a unified framework for path-following generalized Newton-type algorithms. Math. Program. Quoc Tran-Dinh, Tianxiao Sun, Shu Lu
2019	J	`jnl`	Sieve-SDP: a simple facial reduction algorithm to preprocess semidefinite programs. Math. Program. Comput. Yuzixuan Zhu, Gábor Pataki, Quoc Tran-Dinh
2019	J	`jnl`	Using positive spanning sets to achieve stationarity with the Boosted DC Algorithm. CoRR Francisco J. Aragón Artacho, Rubén Campoy, Quoc Tran-Dinh, Phan Tu Vuong
2018	J	`jnl`	A Single-Phase, Proximal Path-Following Framework. Math. Oper. Res. Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
2018	J	`jnl`	A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Convex Minimization. SIAM J. Optim. Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher
2018	A*	`conf`	Non-Ergodic Alternating Proximal Augmented Lagrangian Algorithms with Optimal Rates. NeurIPS Quoc Tran-Dinh
2017	J	`jnl`	Adaptive inexact fast augmented Lagrangian methods for constrained convex optimization. Optim. Lett. Andrei Patrascu, Ion Necoara, Quoc Tran-Dinh
2017	J	`jnl`	Adaptive smoothing algorithms for nonsmooth composite convex minimization. Comput. Optim. Appl. Quoc Tran-Dinh
2017	—	`conf`	Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization. NIPS Ahmet Alacaoglu, Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher
2016	J	`jnl`	A single-phase, proximal path-following framework. CoRR Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
2016	A	`conf`	Convex Block-sparse Linear Regression with Expanders - Provably. AISTATS Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher
2016	J	`jnl`	Convex block-sparse linear regression with expanders - provably. CoRR Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher
2016	Misc	`conf`	Frank-Wolfe works for non-Lipschitz continuous gradient objectives: Scalable poisson phase retrieval. ICASSP Gergely Ódor, Yen-Huan Li, Alp Yurtsever, Ya-Ping Hsieh, Quoc Tran-Dinh, Marwa El Halabi, Volkan Cevher
2016	—	`conf`	Simplicial Nonnegative Matrix Tri-factorization: Fast Guaranteed Parallel Algorithm. ICONIP (2) Duy Khuong Nguyen, Quoc Tran-Dinh, Tu Bao Ho
2015	—	`conf`	A Universal Primal-Dual Convex Optimization Framework. NIPS Alp Yurtsever, Quoc Tran-Dinh, Volkan Cevher
2015	—	`conf`	A primal-dual framework for mixtures of regularizers. EUSIPCO Baran Gozcu, Luca Baldassarre, Quoc Tran-Dinh, Cosimo Aprile, Volkan Cevher
2015	—	`conf`	Composite Convex Minimization Involving Self-concordant-Like Cost Functions. MCO (1) Quoc Tran-Dinh, Yen-Huan Li, Volkan Cevher
2015	J	`jnl`	Composite self-concordant minimization. J. Mach. Learn. Res. Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
2015	J	`jnl`	Structured Sparsity: Discrete and Convex approaches. CoRR Anastasios Kyrillidis, Luca Baldassarre, Marwa El Halabi, Quoc Tran-Dinh, Volkan Cevher
2015	A	`conf`	WASP: Scalable Bayes via barycenters of subset posteriors. AISTATS Sanvesh Srivastava, Volkan Cevher, Quoc Tran-Dinh, David B. Dunson
2014	J	`jnl`	An Inexact Proximal Path-Following Algorithm for Constrained Convex Minimization. SIAM J. Optim. Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
2014	Misc	`conf`	Barrier smoothing for nonsmooth convex minimization. ICASSP Quoc Tran-Dinh, Yen-Huan Li, Volkan Cevher
2014	J	`jnl`	Computational Complexity of Inexact Gradient Augmented Lagrangian Methods: Application to Constrained MPC. SIAM J. Control. Optim. Valentin Nedelcu, Ion Necoara, Quoc Tran-Dinh
2014	—	`conf`	Constrained convex minimization via model-based excessive gap. NIPS Quoc Tran-Dinh, Volkan Cevher
2014	J	`jnl`	Convexity in Source Separation : Models, geometry, and algorithms. IEEE Signal Process. Mag. Michael B. McCoy, Volkan Cevher, Quoc Tran-Dinh, Afsaneh Asaei, Luca Baldassarre
2014	A*	`conf`	Scalable Sparse Covariance Estimation via Self-Concordance. AAAI Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran-Dinh, Volkan Cevher
2014	J	`jnl`	Scalable sparse covariance estimation via self-concordance. CoRR Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran-Dinh, Volkan Cevher
2013	—	`conf`	A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions. ICML (2) Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
2013	J	`jnl`	Composite Self-Concordant Minimization. CoRR Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
2013	J	`jnl`	Convexity in source separation: Models, geometry, and algorithms. CoRR Michael B. McCoy, Volkan Cevher, Quoc Tran-Dinh, Afsaneh Asaei, Luca Baldassarre