Quoc Tran-Dinh

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 55

Top Topics

Convergence Rate

Augmented Lagrangian

Adaptive Smoothing

Top Venues

Comput. Optim. Appl.

Publications

Quoc Tran-Dinh
From Halpern's fixed-point iterations to Nesterov's accelerated interpretations for root-finding problems. Comput. Optim. Appl. 87 (1) (2024)
Trang H. Tran, Quoc Tran-Dinh, Lam M. Nguyen
Shuffling Momentum Gradient Algorithm for Convex Optimization. CoRR (2024)
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) (2024)
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) (2023)
Quoc Tran-Dinh
A unified convergence rate analysis of the accelerated smoothed gap reduction algorithm. Optim. Lett. 16 (4) (2022)
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) (2022)
Quoc Tran-Dinh, Ling Liang, Kim-Chuan Toh
A New Homotopy Proximal Variable-Metric Framework for Composite Convex Minimization. Math. Oper. Res. 47 (1) (2022)
Deyi Liu, Volkan Cevher, Quoc Tran-Dinh
A Newton Frank-Wolfe method for constrained self-concordant minimization. J. Glob. Optim. 83 (2) (2022)
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) (2022)
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) (2021)
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 (2021)
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh
Federated Learning with Randomized Douglas-Rachford Splitting Methods. CoRR (2021)
Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl
A Lyapunov function for the combined system-optimizer dynamics in inexact model predictive control. Autom. 134 (2021)
Yunsoo Ha, Sara Shashaani, Quoc Tran-Dinh
Improved Complexity Of Trust-Region Optimization For Zeroth-Order Stochastic Oracles with Adaptive Sampling. WSC (2021)
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)
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)
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) (2021)
Trang H. Tran, Lam M. Nguyen, Quoc Tran-Dinh
SMG: A Shuffling Gradient-Based Method with Momentum. ICML (2021)
Deyi Liu, Quoc Tran-Dinh
An Inexact Interior-Point Lagrangian Decomposition Algorithm with Inexact Oracles. J. Optim. Theory Appl. 185 (3) (2020)
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)
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 (2020)
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 (2020)
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 (2020)
Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter
Convergence Analysis of Homotopy-SGD for non-convex optimization. CoRR (2020)
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 (2020)
Trang H. Tran, Lam M. Nguyen, Quoc Tran-Dinh
Shuffling Gradient-Based Methods with Momentum. CoRR (2020)
Quoc Tran-Dinh, Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher
An adaptive primal-dual framework for nonsmooth convex minimization. Math. Program. Comput. 12 (3) (2020)
Tianxiao Sun, Ion Necoara, Quoc Tran-Dinh
Composite convex optimization with global and local inexact oracles. Comput. Optim. Appl. 76 (1) (2020)
Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter
Transferring Optimality Across Data Distributions via Homotopy Methods. ICLR (2020)
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 (2020)
Deyi Liu, Volkan Cevher, Quoc Tran-Dinh
A Newton Frank-Wolfe Method for Constrained Self-Concordant Minimization. CoRR (2020)
Quoc Tran-Dinh, Yuzixuan Zhu
Non-stationary First-Order Primal-Dual Algorithms with Faster Convergence Rates. SIAM J. Optim. 30 (4) (2020)
Quoc Tran-Dinh, Deyi Liu, Lam M. Nguyen
Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function. NeurIPS (2020)
Quoc Tran-Dinh, Nhan H. Pham, Lam M. Nguyen
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization. ICML (2020)
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization. CoRR (2019)
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) (2019)
Chengde Qian, Quoc Tran-Dinh, Sheng Fu, Changliang Zou, Yufeng Liu
Robust multicategory support matrix machines. Math. Program. 176 (1-2) (2019)
Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen
A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization. CoRR (2019)
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) (2019)
Yuzixuan Zhu, Gábor Pataki, Quoc Tran-Dinh
Sieve-SDP: a simple facial reduction algorithm to preprocess semidefinite programs. Math. Program. Comput. 11 (3) (2019)
Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl
Contraction Estimates for Abstract Real-Time Algorithms for NMPC. CDC (2019)
Quoc Tran-Dinh
Proximal alternating penalty algorithms for nonsmooth constrained convex optimization. Comput. Optim. Appl. 72 (1) (2019)
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 (2019)
Tianxiao Sun, Quoc Tran-Dinh
Generalized self-concordant functions: a recipe for Newton-type methods. Math. Program. 178 (1-2) (2019)
Quoc Tran-Dinh
Non-Ergodic Alternating Proximal Augmented Lagrangian Algorithms with Optimal Rates. NeurIPS (2018)
Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
A Single-Phase, Proximal Path-Following Framework. Math. Oper. Res. 43 (4) (2018)
Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher
A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Convex Minimization. SIAM J. Optim. 28 (1) (2018)
Ahmet Alacaoglu, Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher
Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization. NIPS (2017)
Andrei Patrascu, Ion Necoara, Quoc Tran-Dinh
Adaptive inexact fast augmented Lagrangian methods for constrained convex optimization. Optim. Lett. 11 (3) (2017)
Quoc Tran-Dinh
Adaptive smoothing algorithms for nonsmooth composite convex minimization. Comput. Optim. Appl. 66 (3) (2017)
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)
Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
A single-phase, proximal path-following framework. CoRR (2016)
Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher
Convex block-sparse linear regression with expanders - provably. CoRR (2016)
Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher
Convex Block-sparse Linear Regression with Expanders - Provably. AISTATS (2016)
Duy Khuong Nguyen, Quoc Tran-Dinh, Tu Bao Ho
Simplicial Nonnegative Matrix Tri-factorization: Fast Guaranteed Parallel Algorithm. ICONIP (2) (2016)
Sanvesh Srivastava, Volkan Cevher, Quoc Tran-Dinh, David B. Dunson
WASP: Scalable Bayes via barycenters of subset posteriors. AISTATS (2015)
Alp Yurtsever, Quoc Tran-Dinh, Volkan Cevher
A Universal Primal-Dual Convex Optimization Framework. NIPS (2015)
Baran Gozcu, Luca Baldassarre, Quoc Tran-Dinh, Cosimo Aprile, Volkan Cevher
A primal-dual framework for mixtures of regularizers. EUSIPCO (2015)
Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
Composite self-concordant minimization. J. Mach. Learn. Res. 16 (2015)
Anastasios Kyrillidis, Luca Baldassarre, Marwa El Halabi, Quoc Tran-Dinh, Volkan Cevher
Structured Sparsity: Discrete and Convex approaches. CoRR (2015)
Quoc Tran-Dinh, Yen-Huan Li, Volkan Cevher
Composite Convex Minimization Involving Self-concordant-Like Cost Functions. MCO (1) (2015)
Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran-Dinh, Volkan Cevher
Scalable Sparse Covariance Estimation via Self-Concordance. AAAI (2014)
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) (2014)
Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
An Inexact Proximal Path-Following Algorithm for Constrained Convex Minimization. SIAM J. Optim. 24 (4) (2014)
Quoc Tran-Dinh, Yen-Huan Li, Volkan Cevher
Barrier smoothing for nonsmooth convex minimization. ICASSP (2014)
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) (2014)
Quoc Tran-Dinh, Volkan Cevher
Constrained convex minimization via model-based excessive gap. NIPS (2014)
Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran-Dinh, Volkan Cevher
Scalable sparse covariance estimation via self-concordance. CoRR (2014)
Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
Composite Self-Concordant Minimization. CoRR (2013)
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)
Michael B. McCoy, Volkan Cevher, Quoc Tran-Dinh, Afsaneh Asaei, Luca Baldassarre
Convexity in source separation: Models, geometry, and algorithms. CoRR (2013)