Quoc Tran-Dinh

According to our database, Quoc Tran-Dinh authored at least 60 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

From Halpern's fixed-point iterations to Nesterov's accelerated interpretations for root-finding problems.

Quoc Tran-Dinh

Comput. Optim. Appl., January, 2024

Shuffling Momentum Gradient Algorithm for Convex Optimization.

Trang H. Tran, Quoc Tran-Dinh, Lam M. Nguyen

CoRR, 2024

2023

A new randomized primal-dual algorithm for convex optimization with fast last iterate convergence rates.

Quoc Tran-Dinh, Deyi Liu

Optim. Methods Softw., January, 2023

2022

New Primal-Dual Algorithms for a Class of Nonsmooth and Nonlinear Convex-Concave Minimax Problems.

Yuzixuan Zhu, Deyi Liu, Quoc Tran-Dinh

SIAM J. Optim., 2022

A unified convergence rate analysis of the accelerated smoothed gap reduction algorithm.

Quoc Tran-Dinh

Optim. Lett., 2022

A hybrid stochastic optimization framework for composite nonconvex optimization.

Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen

Math. Program., 2022

A New Homotopy Proximal Variable-Metric Framework for Composite Convex Minimization.

Quoc Tran-Dinh, Ling Liang, Kim-Chuan Toh

Math. Oper. Res., 2022

A Newton Frank-Wolfe method for constrained self-concordant minimization.

Deyi Liu, Volkan Cevher, Quoc Tran-Dinh

J. Glob. Optim., 2022

2021

A Unified Convergence Analysis for Shuffling-Type Gradient Methods.

Lam M. Nguyen, Quoc Tran-Dinh, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk

J. Mach. Learn. Res., 2021

Identifying Heterogeneous Effect Using Latent Supervised Clustering With Adaptive Fusion.

Jingxiang Chen, Quoc Tran-Dinh, Michael R. Kosorok, Yufeng Liu

J. Comput. Graph. Stat., 2021

Federated Learning with Randomized Douglas-Rachford Splitting Methods.

Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh

CoRR, 2021

A Lyapunov function for the combined system-optimizer dynamics in inexact model predictive control.

Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl

Autom., 2021

Minimization of a class of rare event probabilities and buffered probabilities of exceedance.

Amarjit Budhiraja, Shu Lu, Yang Yu, Quoc Tran-Dinh

Ann. Oper. Res., 2021

Improved Complexity Of Trust-Region Optimization For Zeroth-Order Stochastic Oracles with Adaptive Sampling.

Yunsoo Ha, Sara Shashaani, Quoc Tran-Dinh

Proceedings of the Winter Simulation Conference, 2021

FedDR - Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization.

Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SMG: A Shuffling Gradient-Based Method with Momentum.

Trang H. Tran, Lam M. Nguyen, Quoc Tran-Dinh

Proceedings of the 38th International Conference on Machine Learning, 2021

Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes.

Nhuong V. Nguyen, Toan N. Nguyen, Phuong Ha Nguyen, Quoc Tran-Dinh, Lam M. Nguyen, Marten van Dijk

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Non-stationary First-Order Primal-Dual Algorithms with Faster Convergence Rates.

Quoc Tran-Dinh, Yuzixuan Zhu

SIAM J. Optim., 2020

An adaptive primal-dual framework for nonsmooth convex minimization.

Quoc Tran-Dinh, Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher

Math. Program. Comput., 2020

An Inexact Interior-Point Lagrangian Decomposition Algorithm with Inexact Oracles.

Deyi Liu, Quoc Tran-Dinh

J. Optim. Theory Appl., 2020

ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization.

Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh

J. Mach. Learn. Res., 2020

Shuffling Gradient-Based Methods with Momentum.

Trang H. Tran, Lam M. Nguyen, Quoc Tran-Dinh

CoRR, 2020

Convergence Analysis of Homotopy-SGD for non-convex optimization.

Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter

CoRR, 2020

Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise.

Marten van Dijk, Nhuong V. Nguyen, Toan N. Nguyen, Lam M. Nguyen, Quoc Tran-Dinh, Phuong Ha Nguyen

CoRR, 2020

Composite convex optimization with global and local inexact oracles.

Tianxiao Sun, Ion Necoara, Quoc Tran-Dinh

Comput. Optim. Appl., 2020

Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function.

Quoc Tran-Dinh, Deyi Liu, Lam M. Nguyen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization.

Quoc Tran-Dinh, Nhan H. Pham, Lam M. Nguyen

Proceedings of the 37th International Conference on Machine Learning, 2020

Transferring Optimality Across Data Distributions via Homotopy Methods.

Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter

Proceedings of the 8th International Conference on Learning Representations, 2020

A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning.

Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk, Quoc Tran-Dinh

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Sieve-SDP: a simple facial reduction algorithm to preprocess semidefinite programs.

Yuzixuan Zhu, Gábor Pataki, Quoc Tran-Dinh

Math. Program. Comput., 2019

Self-concordant inclusions: a unified framework for path-following generalized Newton-type algorithms.

Quoc Tran-Dinh, Tianxiao Sun, Shu Lu

Math. Program., 2019

Generalized self-concordant functions: a recipe for Newton-type methods.

Tianxiao Sun, Quoc Tran-Dinh

Math. Program., 2019

Robust multicategory support matrix machines.

Chengde Qian, Quoc Tran-Dinh, Sheng Fu, Changliang Zou, Yufeng Liu

Math. Program., 2019

Using positive spanning sets to achieve stationarity with the Boosted DC Algorithm.

Francisco J. Aragón Artacho, Rubén Campoy, Quoc Tran-Dinh, Phan Tu Vuong

CoRR, 2019

A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization.

Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen

CoRR, 2019

Proximal alternating penalty algorithms for nonsmooth constrained convex optimization.

Quoc Tran-Dinh

Comput. Optim. Appl., 2019

Non-stationary Douglas-Rachford and alternating direction method of multipliers: adaptive step-sizes and convergence.

Dirk A. Lorenz, Quoc Tran-Dinh

Comput. Optim. Appl., 2019

Contraction Estimates for Abstract Real-Time Algorithms for NMPC.

Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018

A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Convex Minimization.

Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher

SIAM J. Optim., 2018

A Single-Phase, Proximal Path-Following Framework.

Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher

Math. Oper. Res., 2018

Non-Ergodic Alternating Proximal Augmented Lagrangian Algorithms with Optimal Rates.

Quoc Tran-Dinh

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Adaptive inexact fast augmented Lagrangian methods for constrained convex optimization.

Andrei Patrascu, Ion Necoara, Quoc Tran-Dinh

Optim. Lett., 2017

Adaptive smoothing algorithms for nonsmooth composite convex minimization.

Quoc Tran-Dinh

Comput. Optim. Appl., 2017

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization.

Ahmet Alacaoglu, Quoc Tran-Dinh, Olivier Fercoq, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Simplicial Nonnegative Matrix Tri-factorization: Fast Guaranteed Parallel Algorithm.

Duy Khuong Nguyen, Quoc Tran-Dinh, Tu Bao Ho

Proceedings of the Neural Information Processing - 23rd International Conference, 2016

Frank-Wolfe works for non-Lipschitz continuous gradient objectives: Scalable poisson phase retrieval.

Gergely Ódor, Yen-Huan Li, Alp Yurtsever, Ya-Ping Hsieh, Quoc Tran-Dinh, Marwa El Halabi, Volkan Cevher

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Convex Block-sparse Linear Regression with Expanders - Provably.

Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Composite self-concordant minimization.

Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher

J. Mach. Learn. Res., 2015

Structured Sparsity: Discrete and Convex approaches.

Anastasios Kyrillidis, Luca Baldassarre, Marwa El Halabi, Quoc Tran-Dinh, Volkan Cevher

CoRR, 2015

A Universal Primal-Dual Convex Optimization Framework.

Alp Yurtsever, Quoc Tran-Dinh, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Composite Convex Minimization Involving Self-concordant-Like Cost Functions.

Quoc Tran-Dinh, Yen-Huan Li, Volkan Cevher

Proceedings of the Modelling, Computation and Optimization in Information Systems and Management Sciences - Proceedings of the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences, 2015

A primal-dual framework for mixtures of regularizers.

Baran Gozcu, Luca Baldassarre, Quoc Tran-Dinh, Cosimo Aprile, Volkan Cevher

Proceedings of the 23rd European Signal Processing Conference, 2015

WASP: Scalable Bayes via barycenters of subset posteriors.

Sanvesh Srivastava, Volkan Cevher, Quoc Tran-Dinh, David B. Dunson

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Convexity in Source Separation : Models, geometry, and algorithms.

Michael B. McCoy, Volkan Cevher, Quoc Tran-Dinh, Afsaneh Asaei, Luca Baldassarre

IEEE Signal Process. Mag., 2014

An Inexact Proximal Path-Following Algorithm for Constrained Convex Minimization.

Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher

SIAM J. Optim., 2014

Computational Complexity of Inexact Gradient Augmented Lagrangian Methods: Application to Constrained MPC.

Valentin Nedelcu, Ion Necoara, Quoc Tran-Dinh

SIAM J. Control. Optim., 2014

Constrained convex minimization via model-based excessive gap.

Quoc Tran-Dinh, Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Barrier smoothing for nonsmooth convex minimization.

Quoc Tran-Dinh, Yen-Huan Li, Volkan Cevher

Proceedings of the IEEE International Conference on Acoustics, 2014

Scalable Sparse Covariance Estimation via Self-Concordance.

Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran-Dinh, Volkan Cevher

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions.

Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher

Proceedings of the 30th International Conference on Machine Learning, 2013