Some of my publications can be downloaded here, some others are not available online. To request any papers in electronic format, please contact me. Here is my google scholar
Working and submitted papers
- Survey Manuscript – STOR-UNC, April 2023:
- Author: Quoc Tran-Dinh
- Title: Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on Classical and Recent Developments
- Status: Submitted
- Preprint: https://arxiv.org/abs/2303.17192
- Manuscript – STOR-UNC, January 2023:
- Authors: Quoc Tran-Dinh & Yang Luo
- Title: Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems
- Status: Submitted
- Preprint: https://arxiv.org/abs/2301.03113
- Manuscript – STAT & OR – UNC, October 2021:
- Authors: Q. Tran-Dinh and Yang Luo
- Title: Halpern-Type Accelerated and Splitting Algorithms for Monotone Inclusions
- Status: Working paper
- Preprint: https://arxiv.org/abs/2006.09263.
- Short Note (not a paper) – STAT & OR – UNC, August 2020:
- Authors: Deyi Liu, Lam M. Nguyen, and Quoc Tran-Dinh
- Title: An Optimal Hybrid Variance-Reduced Algorithm for Stochastic Composite Nonconvex Optimization
- Status: Working draft.
- Preprint: https://arxiv.org/abs/2008.09055 (Arxiv)
Publications (Peer-reviewed papers sorted by year)
2023:
- Paper – STOR-UNC, February 2023 (December 2023):
- Author: Quoc Tran-Dinh
- Title: Extragradient-Type Methods with O(1/k) Convergence Rates for Co-Hypomonotone Inclusions
- Status: Accepted for publication on Journal of Global Optimization.
- Preprint: https://arxiv.org/abs/2302.04099
- Book chapter – STOR-UNC, December 2022:
- Authors: Quoc Tran-Dinh and Marten van Dijk
- Title: Gradient Descent-Type Methods: Background and Simple Unified Convergence Analysis
- Status: To appear in “Federated learning: Theory and Practice” edited by L. M. Nguyen, T. N. Hoang, and P.-Y. Chen, Elsevier publisher, 2023.
- Preprint: https://arxiv.org/abs/2212.09413
- Paper – STAT & OR – UNC, March 2022:
- Author: Q. Tran-Dinh
- Title: From Halpern’s fixed-point iterations to Nesterov’s accelerated interpretations for root-finding problems.
- Status: Computational Optimization and Applications [PDF]
- Preprint: https://arxiv.org/abs/2203.04869.
2022:
- Paper – STAT & OR – UNC April 2022:
- Authors: Y. Zhu, D. Liu, and Q. Tran-Dinh
- Title: A New Primal-Dual Algorithm for a Class of Nonlinear Compositional Convex Optimization Problems
- Status: Accepted for publication on SIAM Journal on Optimization (SIOPT).
- Preprint: https://arxiv.org/abs/2006.09263.
- Manuscript – STAT & OR – UNC, June 2022:
- Authors: Q. Tran-Dinh and Deyi Liu
- Title: Randomized Primal-Dual Algorithms for Composite Convex Minimization with Faster Convergence Rates
- Status: Accepted for publication on Optimization Methods & Software
- Preprint: https://arxiv.org/abs/2003.01322.
2021:
- Journal Paper (STAT & OR – UNC, February 2020), October 2021:
- Authors: Deyi Liu, Volkan Cevher, and Q. Tran-Dinh
- Title: A Newton Frank-Wolfe Method for Constrained Self-Concordant Minimization.
- Status: Accepted for Journal of Global Optimization (JOGO).
- Preprint: https://arxiv.org/abs/2002.07003
- Conference Paper (Initialization: STAT & OR – UNC, February 2021), September 2021:
- Authors: Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, and Lam M. Nguyen
- Title: FedDR – Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization
- Status: Accepted for NeurIPs 2021.
- Preprint: https://arxiv.org/abs/2103.03452 (Arxiv)
- Journal Paper – STAT & OR – UNC (February 2020), September 2021:
- Authors: Lam M. Nguyen, Q. Tran-Dinh, Dzung T. Phan, Ha P. Nguyen, and Marten van Dijk
- Title: A Unified Convergence Analysis for Shuffling-Type Gradient Methods
- Status: Journal of Machine Learning Research (JMLR), vol. 22, pp. 1–44, 2021.
- Preprint: https://arxiv.org/abs/2002.08246.
- Conference Paper (August 2021):
- Authors: Y. Ha, S. Shashaani, and Q. Tran-Dinh
- Title: Improved Complexity of Trust-region Optimization for Zeroth-order Stochastic Oracles with Adaptive Sampling
- Status: Accepted for publication in Proceedings of The 2021 Winter Simulation Conference.
- Preprint: https://arxiv.org/abs/2002.08246.
- Journal Paper (2021) (STAT & OR – UNC, April 2020):
- Authors: Andrea Zanelli, Quoc Tran-Dinh, and Moritz Diehl
- Title: A Lyapunov Function for the Combined System-Optimizer Dynamics in Nonlinear Model Predictive Control
- Status: Automatica, vol. 134, 2021.
- Preprint: https://arxiv.org/abs/2104.01314
- Journal Paper (2021) (STAT & OR – UNC, December 2020):
- Author: Quoc Tran-Dinh
- Title: A Unified Convergence Rate Analysis of The Accelerated Smoothed Gap Reduction Algorithm
- Status: Optimization Letters (in press)
- Preprint: https://arxiv.org/abs/2104.01314
- Conference Paper (2021) (STAT & OR – UNC, November 2020):
- Authors: Trang H. Tran, Lam M. Nguyen, and Quoc Tran-Dinh
- Title: Shuffling Gradient-Based Methods with Momentum
- Status: ICML 2021.
- Preprint: https://arxiv.org/abs/2011.11884 (Arxiv)
- Invited Paper, February 2021:
- Authors: Q. Tran-Dinh
- Title: Extended Gauss-Newton and ADMM-Gauss-Newton algorithms for low-rank matrix optimization
- Status: Journal of Applied and Numerical Optimization, vol. 3, no. 1 (2021).
- Preprint: http://arxiv.org/abs/1606.03358, (Tech. Report) [pdf].
- Journal Paper, March 2021:
- Author: A. Budhiraja, S. Lu, Y. Yu, and Q. Tran-Dinh
- Title: Minimization of a class of rare event probabilities and buffer probabilities of exceedance
- Status: Annals of Operations Research (online first)
- Preprint: https://arxiv.org/abs/1902.07829
- Conference Paper, March 2021:
- Author: Ilyes Mezghani, Q. Tran-Dinh, Ion Necoara, and Anthony Papavasiliou.
- Title: A Penalty Method Based on a Gauss-Newton Scheme for AC-OPF
- Status: The 2021 IEEE Madrid PowerTech Conference.
- Preprint: https://arxiv.org/pdf/1905.08588.pdf
- Conference paper – January 22, 2021 (STAT & OR – UNC):
- Authors: Nhuong V. Nguyen, Toan N. Nguyen, P. Ha Nguyen, Q. Tran-Dinh, Lam M. Nguyen, and M. van Dijk.
- Title: Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes
- Status: The 24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021), 2021.
- Preprint: https://arxiv.org/abs/2010.14763
2020:
- Journal Paper – October 28, 2020 (STAT & OR – UNC, December 2018):
- Author: Q. Tran-Dinh, Liang Ling, and Kim-Chuan Toh
- Title: A New Homotopy Proximal Variable-Metric Framework for Composite Convex Minimization
- Status: Accepted for publication on Mathematics of Operations Research.
- Preprint: https://arxiv.org/abs/1812.05243.
- Journal Paper, Oct 2020 (Manuscript STAT & OR – UNC, July 2019):
- Authors: Q. Tran-Dinh, N. H. Pham, D. T. Phan, and L. M. Nguyen
- Title: A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization
- Status: Accepted for publication on Mathematical Programming, Ser. A.
- Preprint: https://arxiv.org/pdf/1907.03793.pdf
- Note: This paper is a journal extension version of our preprint “Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization” below.
- Conference Paper – STAT & OR – UNC, September 2020:
- Authors: Q. Tran-Dinh, Deyi Liu, and Lam M. Nguyen
- Title: Hybrid Variance-Reduced SGD Algorithms for Nonconvex-Concave Minimax Problems.
- Status: Accepted for presenting at NeurIPs 2020.
- Preprint: https://arxiv.org/abs/2006.15266 and Codes.
- Journal Paper, July 2020 (Manuscript, STAT & OR – UNC, March 2019):
- Author: Q. Tran-Dinh and Y. Zhu
- Title: Non-Stationary First-Order Primal-Dual Algorithms with Fast Convergence Rates
- Status: SIAM Journal on Optimization (SIOPT), Vol. 30, No. 4, pp. 2866–2896, 2020.
- Preprint: https://arxiv.org/abs/1903.05282.
- Conference Paper, June 2020 (STAT & OR – UNC, February 2020):
- Authors: Q. Tran-Dinh, N. H. Pham, and L. M. Nguyen
- Title: Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization
- Status: Accepted for ICML 2020.
- Preprint: https://arxiv.org/abs/2002.07290
- Journal Paper, May 2020:
- Author: J. Chen, Q. Tran-Dinh, M. Kosorok, and Y. Liu
- Title: Identifying Heterogeneous Effect using Latent Supervised Clustering with Adaptive Fusion
- Status: Journal of Computational and Graphical Statistics (online first), 2020.
- PDF Link: https://www.tandfonline.com/doi/abs/10.1080/10618600.2020.1763808.
- Journal Paper, April 2020 (STAT & OR – UNC, February 2019):
- Author: Nhan Pham H., Lam Nguyen M., Dzung Phan T., and Q. Tran-Dinh
- Title: ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization
- Status: Journal of Machine Learning Research (JMLR), Vol. 21, pp. 1–48, 2020.
- Preprint: https://arxiv.org/abs/1902.05679.
- Journal Paper: April 2020 (STAT & OR – UNC, April 2019):
- Author: Deyi Liu and Q. Tran-Dinh
- Title: An Inexact Interior-Point Lagrangian Decomposition Algorithm with Inexact Oracles
- Status: Journal of Optimization Theory and Applications (JOTA), vol 185, pp. 903-926, 2020.
- Preprint: https://arxiv.org/pdf/1904.09016.pdf.
- Conference Paper: March 2020
- Authors: A. Zanelli, Q. Tran Dinh, M. Diehl
- Title: Stability Analysis of Real-Time Methods for Equality Constrained NMPC
- Status: Accepted for presentation at IFAC 2020.
- Conference: 21st IFAC World Congress, 2020.
- Journal paper: February 2020 (First version, August 2018):
- Author: Tianxiao Sun, Ion Necoara, and Q. Tran-Dinh
- Title: Composite Convex Optimization with Global and Local Inexact Oracles
- Status: Computational Optimization and Applications (COAP), Feb., 2020, vol. 76, pp. 69–124.
- Preprint: https://arxiv.org/abs/1808.02121.
- Conference Paper, January 2020:
- Authors: N. H. Pham, L. M. Nguyen, D. T. Phan, H. P. Nguyen, M. van Dijk, and Q. Tran-Dinh
- Title: A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning.
- Status: In the proceedings of the 23rd International Conference: Artificial Intelligence and Statistics (AISTATS 2020), Italy, 2020.
- Preprint: https://arxiv.org/abs/2003.00430.
2019
- Conference Paper, December 2019:
- Authors: Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter.
- Title: Transferring Optimality Across Data Distributions via Homotopy Methods.
- Status: In the proceedings of the Eighth International Conference on Learning Representations (ICLR 2020), Ethiopia, April 2020.
- Preprint: https://openreview.net/forum?id=S1gEIerYwH
- Journal Paper – STAT & OR – UNC, August 2018:
- Authors: Q. Tran-Dinh, A. Alacaoglu, O. Fercoq, and V. Cevher
- Title: An Adaptive Primal-Dual Framework for Nonsmooth Convex Minimization
- Status: Mathematical Programming Computation (MPC), 2019 (online first).
- Preprint: https://arxiv.org/pdf/1808.04648.pdf.
- Conference Paper – STATE & OR – UNC, September 2019:
- Author: Andrea Zanelli, Q. Tran-Dinh, Moritz Diehl
- Title: Contraction Estimates for Abstract Real-Time Algorithms for NMPC
- Status: In the proceedings of the Conference on Decision and Control (CDC), Nice, France, December 2019.
- Preprint: Available on Researchgate.
- Journal Paper – STAT & OR – UNC, April 2019:
- Author: Dirk Lorenz, and Q. Tran-Dinh
- Title: Non-stationary Douglas-Rachford and alternating direction method of multipliers: adaptive stepsizes and convergence.
- Status: Computational Optimization and Applications, vol. 74, pp. 67–92, 2019.
- Preprint: https://arxiv.org/pdf/1801.03765.pdf.
- Journal Paper – STAT & OR – UNC, March 2019:
- Author: C. Qian, Quoc Tran-Dinh, S. Fu, C. Zou, and Y. Liu
- Title: Robust Multicategory Support Matrix Machines.
- Status: Mathematical Programming (Ser. B).
- Journal Paper – STAT & OR – UNC, February 2019:
- Author: Y. Zhu, G. Pataki, and Q. Tran-Dinh
- Title: Sieve-SDP: a simple facial reduction algorithm to preprocess semidefinite programs.
- Status: Mathematical Programming Computation (MPC), vol. 11, No. 3, pp. 503-586.
- Preprint: https://arxiv.org/abs/1710.08954.
- Codes: Matlab-code is available at https://github.com/quoctd/SieveSDP
2018
- Journal paper (STAT & OR – UNC, September 2018):
- Author: Q. Tran-Dinh
- Title: Proximal Alternating Penalty Algorithms for Nonsmooth Constrained Convex Optimization.
- Status: Computational Optimization and Applications, vol. 72, pp. 1–43, 2018.
- Preprint: https://arxiv.org/abs/1711.01367.
- Codes: Matlab-code is available at https://github.com/quoctd/PAPA-1.0
- Conference Paper (Manuscript – STAT & OR – UNC, September 2018):
- Author: Q. Tran-Dinh
- Title: Non-Ergodic Alternating Proximal Augmented Lagrangian Algorithms with Optimal Rates.
- Status: Thirty-second Conference on Neural Information Processing Systems (NIPS, 2018).
- The extended version is available at: https://arxiv.org/pdf/1801.03765.pdf. This version was collaborated with my Ph.D. student, Y. Zhu.
- Journal paper (manuscript – STAT & OR – UNC, March 2017):
- Authors: T. Sun and Q. Tran-Dinh
- Title: Generalized self-concordant functions: A recipe for Newton-type methods.
- Status: Mathematical Programming (online first).
- Preprint: https://arxiv.org/pdf/1703.04599.pdf [pdf]
- Journal paper (manuscript – STAT & OR – UNC, October 2016):
- Authors: Q. Tran-Dinh, T. Sun, and S. Lu
- Title: Self-concordant inclusions: A unified framework for proximal path-following generalized Newton algorithms
- Status: Mathematical Programming (online first)
- Preprint: https://arxiv.org/pdf/1707.07403.pdf [pdf].
- Book chapter (manuscript – STAT & OR – UNC, September 2016):
- Authors: Q. Tran-Dinh and V. Cevher
- Title: Smooth alternating direction methods for nonsmooth constrained convex optimization.
- Status: Book chapter in “Distributed and Large-Scale Optimization“, edited by P. Giselsson and A. Rantzer, Springer-Verlag, 2018.
- Preprint: Online at: http://arxiv.org/pdf/1507.03734.pdf [pdf].
2017
- Journal paper:
- Authors: Q. Tran-Dinh, A. Kyrillidis, and V. Cevher
- Title: A single-phase, proximal path-following framework.
- Status: Mathematics of Operations Research (MOR), 2017 (accepted).
- Preprint: http://arxiv.org/abs/1603.01681, (2016) [pdf].
- Conference paper (NIPS):
- Authors: A. Alacaoglu, Q. Tran-Dinh, O. Fercoq, and V. Cevher
- Title: Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization
- Conference: Conference on Neural Information Processing Systems (NIPS), Long Beach, CA, USA, 2017.
- Status: Accepted (https://nips.cc/Conferences/2017/Schedule?showEvent=9358)
- Preprint: https://arxiv.org/pdf/1711.03439.pdf
- Journal paper:
- Authors: Q. Tran-Dinh, O. Fercoq, and V. Cevher
- Title: A smooth primal-dual optimization framework for nonsmooth convex optimization.
- Journal: SIAM J. Optimization
- Status: Accepted.
- Preprint: Online at: http://arxiv.org/pdf/1507.06243.pdf [pdf].
- Journal paper.
- Authors: Q. Tran-Dinh
- Title: Adaptive Smoothing Algorithms for Nonsmooth Composite Convex Minimization
- Journal: Computational Optimization and Applications, vol. 66, issue 3, pp. 425–451, 2017.
- Link: DOI 10.1007/s10589-016-9873-6 [pdf]
- Preprint: http://arxiv.org/abs/1509.00106, (2015) [pdf].
- Journal paper.
- Authors: A. Patrascu, I. Necoara, and Q. Tran-Dinh
- Title: Adaptive inexact fast augmented Lagrangian methods for constrained convex optimization
- Journal: Optimization Letters, Vol. 11, Issue 3, pp. 609–626 (2017).
- Link: http://link.springer.com/article/10.1007%2Fs11590-016-1024-6[pdf].
- Preprint: http://arxiv.org/pdf/1505.03175.pdf, (submitted), (2015) [pdf].
2016
- Conference paper
- Authors: D. K. Nguyen, Q. Tran-Dinh, T. B. Ho
- Title: Simplicial Nonnegative Matrix Tri-Factorization: Fast Guaranteed Parallel Algorithm
- Proceedings: The 23rd International Conference on Neural Information Processing, ICONIP2016, Kyoto 16-21, 2016, (accepted).
- Conference paper
- Authors: G. Odor, Y.-H. Li, A. Yurtsever, Y.-P. Hsieh and Q. Tran Dinh, and V. Cevher
- Title: Frank-Wolfe Works for Non-Lipschitz Continuous Gradient Objectives: Scalable Poisson Phase Retrieval
- Proceedings: 41st IEEE International Conference on Acoustics, Speech and Signal Processing, 2016.(ICASSP2016), 2016.
- Preprint: http://arxiv.org/abs/1602.00724, (2015) [pdf].
- Conference paper (AISTATS)
- Authors: Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran Dinh, Luca Baldassarre, Volkan Cevher
- Title: Convex block-sparse linear regression with expanders, provably
- Proceedings: The 19th International Conference on Artificial Intelligence and Statistics (AISTATS2016), 2016, Spain.
- Preprint: http://arxiv.org/abs/1603.06313
- Journal paper
- Authors Q. Tran-Dinh, I. Necoara, M. Diehl
- Title: Fast inexact distributed optimization algorithms for separable convex optimization
- Journal: Optimization, Vol. 65, No. 2, pp. 325-356, 2016.
- Link: http://www.tandfonline.com/doi/abs/10.1080/02331934.2015.1044898?src=recsys&journalCode=gopt20
- Preprint: http://arxiv.org/abs/1107.5841, (2012) [pdf].
2015
- Conference paper (NIPS)
- Authors: A. Yurtsever, Q. Tran-Dinh, and V. Cevher
- Title: Universal Primal-Dual Proximal-Gradient Methods
- Proceedings: 29th Ann. Conf. Neural Information Processing Systems (NIPS), 2015.
- Preprint: http://arxiv.org/pdf/1502.03123.pdf, (2015) [pdf].
- Conference paper
- Authors: Gozcu, B. and Baldassarre, L., Tran-Dinh, Q., Aprile, C. and Cevher, V.
- Title: A Primal-dual Framework For Mixtures Of Regularisers
- Proceedings: Proceedings of the 23rd European Signal Processing Conference (EUSIPCO 2015), 2015.
- Book chapter
- Authors: Kyrillidis, Anastasios and Baldassarre, Luca and El Halabi, Marwa and Tran-Dinh, Quoc and Cevher, Volkan
- Title: Structured Sparsity: Discrete and Convex Approaches
- Book chapter: Compressed Sensing and its Applications: MATHEON Workshop, 2013, pp. 341–378, (2015), Birkhauser.
- Book chapter
- Authors: Q. Tran-Dinh, Y.-H. Li, and V. Cevher
- Title: Composite Convex Minimization Involving Self-concordant-Like Cost Functions
- Book chapter: Modelling, Computation and Optimization in Information Systems and Management Sciences, Advances in Intelligent Systems and Computing, Vol. 359, 2015, pp. 155–168. Available at: http://link.springer.com/chapter/10.1007/978-3-319-18161-5_14
- Link: This links to the paper [pdf]
- Preprint: http://arxiv.org/pdf/1502.01068.pdf ([pdf]).
- Conference paper (AISTATS)
- Authors: S. Srivastava, V. Cevher, Q. Tran-Dinh and D. B. Dunson.
- Title: WASP: Scalable Bayes via barycenters of subset posteriors
- Proceedings: Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS), 2015, San Diego, CA, USA. JMLR: W&CP volume 38, (2015).
- Journal paper
- Authors: Q. Tran-Dinh, Anastasios Kyrillidis, and Volkan Cevher
- Title: Composite Self-concordant minimization
- Journal: Journal of Machine Learning Research (JMLR), 16(Mar):371−416, 2015.
- Link: http://www.jmlr.org/papers/volume16/trandihn15a/trandihn15a.pdf [pdf].
- Preprint: http://arxiv.org/abs/1308.2867 [pdf]
2014
- Conference paper (NIPS)
- Authors: Q. Tran-Dinh and V. Cevher
- Title: Constrained convex minimization via model-based excessive gap
- Proceedings: Proceedings of the annual conference on Neural Information Processing Systems Foundation (NIPS), Montreal, Canada, (2014).
- Conference paper (AAAI)
- Authors: A. Kyrillidis, R.K. Mahabadi, Q. Tran-Dinh and V. Cevher
- Title: Scalable sparse covariance estimation via self-concordance
- Proceedings: Proceedings of the 28th AAAI Conference on Artificial Intelligence, Quebec, Canada, (2014).
- Conference paper
- Authors: Q. Tran-Dinh, Y.H.Li and V. Cevher.
- Title: Barrier Smoothing for Nonsmooth Convex Minimization
- Proceedings: Proceedings of the 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Florence, Italy, (2014).
- Journal paper
- Authors: Q. Tran-Dinh, Anastasios Kyrillidis and Volkan Cevher
- Title: An Inexact Proximal Path-Following Algorithm for Constrained Convex Minimization
- Journal: SIAM J. Optimization, vol. 24, no. 4, pages 1718–1745, (2014), Preprint is available at:
- Preprint: http://arxiv.org/abs/1311.1756 [pdf]
- Journal paper
- Authors: V. Nedelcu, I. Necoara and Q. Tran-Dinh
- Title: Computational Complexity of Inexact Gradient Augmented Lagrangian Methods: Application to Constrained MPC
- Journal: SIAM J. Optimization and Control, vol. 52, no. 5, pages 3109–3134, 2014. Preprint: http://arxiv.org/abs/1302.4355 [pdf].
- Journal paper
- Authors: M. B. McCoy, V. Cevher, Q. Tran-Dinh, A. Asaei, L. Baldassarre
- Title: Convexity in source separation: Models, geometry, and algorithms
- Journal: Signal Processing Magazine, Vol. 31, No. 3, pages 87–95, 2014.
- Preprint: http://arxiv.org/abs/1311.0258 [pdf]
- Journal paper
- Authors: Q. Tran-Dinh, I. Necoara and M. Diehl
- Title: Path-Following Gradient-Based Decomposition Algorithms For Separable Convex Optimization
- Journal: Journal of Global Optimization, Vol. 59, No. 1, pp. 59–80, 2014.
- Link: http://link.springer.com/article/10.1007%2Fs10898-013-0085-7, [pdf] or at [pdf].
- Journal paper
- Authors: Signoretto M., Tran-Dinh Q., De Lathauwer L., Suykens J.A.K.
- Title: Learning with Tensors: a Framework Based on Convex Optimization and Spectral Regularization
- Journal: Machine Learning, vol. 95, no. 3, pp. 303–351, 2014.
- Link: http://link.springer.com/article/10.1007%2Fs10994-013-5366-3
2013
- Journal paper
- Authors: Debrouwere, F., Van Loock, W., Pipeleers, G., Tran-Dinh, Q., Diehl, M., De Schutter, J., Swevers, J.
- Title: Time-Optimal Path Following for Robots with Convex-Concave Constraints using Sequential Convex Programming
- Journal: IEEE Transactions on Robotics, Vol. 99, No. 6, pp. 1485–1495, 2013
- Link: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=arnumber=6634254 [pdf]
- Conference paper (ICML)
- Authors: Q. Tran-Dinh, Anastasios Kyrillidis and Volkan Cevher
- Title: A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions
- Proceedings: In Proc. of the International Conference on Machine Learning (ICML)
- Link: http://icml.cc/2013/?page_id=876,(2013) [pdf].
- Conference paper (CDC)
- Authors: Q. Tran-Dinh, I. Necoara and M. Diehl
- Title: A dual decomposition algorithm for separable nonconvex optimization using the penalty function framework
- Proceedings: Proceedings of the Conference on Decision and Control (CDC), pp. 2372–2377, (2013).
- Link: The pdf is here [pdf]
- Conference paper
- Authors: Debrouwere, F., Van Loock, W., Pipeleers, G., Tran-Dinh, Q., Diehl, M., De Schutter, J., Swevers, J.
- Title: Time-Optimal Path Following for Robots with Trajectory Jerk Constraints using Sequential Convex Programming.
- Proceedings: IEEE International Conference on Robotics and Automation (ICRA). IEEE International Conference on Robotics and Automation. Karlsruhe, Germany, 6-10 May 2013 (pp. 1908-1913).
- Conference paper
- Authors: Debrouwere, F., Van Loock, W., Pipeleers, G., Tran-Dinh, Q., Diehl, M., De Schutter, J., Swevers, J.
- Title: Optimal Robot Path Following for Minimal Time versus Energy Loss Trade-Off using Sequential Convex Programming.
- Proceedings: IEEE International Conference on Mechatronics. Vicenza, Italy, February 27 – March 1, 2013.
- Journal paper
- Authors: Q. Tran-Dinh, I. Necoara, C. Savorgnan and M. Diehl
- Title: An inexact perturbed path-following method for Lagrangian decomposition in large-scale separable convex optimization
- Journal: SIAM J. Optimization, vol. 23, no. 1 (2013), pp. 95-125.
- Preprint: http://arxiv.org/abs/1109.3323, 2011 [pdf].
2012
- Journal paper
- Authors: Q. Tran-Dinh, C. Savorgnan and M. Diehl
- Title: Adjoint-based predictor-corrector sequential convex programming for parametric nonlinear optimization
- Journal: SIAM Journal on Optimization, Vol. 22, No. 4, pp. 1258–1284, ,2012
- Link: http://epubs.siam.org/doi/abs/10.1137/110844349 [pdf]
- Preprint: http://arxiv.org/abs/1109.2800 [pdf].
- Conference paper
- Authors: Debrouwere, F., Van Loock, W., Pipeleers, G., Tran-Dinh, Q., Diehl, M., De Schutter, J., Swevers, J.
- Title: Time-optimal robot path following with Cartesian acceleration constraints: a convex optimization approach.
- Proceedings: The 13th Mechatronics Forum International Conference: Vol. 2 (3). Mechatronics Forum International Conference. Linz, Austria, 17-19 September 2012 (pp. 469-475).
- Journal paper
- Authors: Q. Tran-Dinh, C. Savorgnan and M. Diehl
- Title: Combining Lagrangian Decomposition and Excessive Gap Smoothing Technique for Solving Large-Scale Separable Convex Optimization Problems
- Journal: Computational Optimization and Applications, vol. 55, no. 1, pp. 75–111, 2012
- Link: http://link.springer.com/article/10.1007%2Fs10589-012-9515-6 [online]
- Preprint: http://arxiv.org/abs/1105.5427.
- Journal paper
- Authors: Q. Tran-Dinh, S. Gumussoy, W. Michiels and M. Diehl
- Title: Combining convex-concave decompositions and linearization approaches for solving BMIs, with application to static output feedback
- Journal: IEEE Transactions on Automatic Control, vol. 57, No. 6, pp. 1377–1390, 2012 (regular paper)
- Preprint: http://arxiv.org/abs/1109.3320
- Conference paper (CDC)
- Authors: Q. Tran-Dinh, W. Michiels, S. Gros and M. Diehl
- Title: An inner convex approximation algorithm for BMI optimization and applications in control
- Proceedings: Proc. of the 51st IEEE Conference on Decision and Control (CDC)
- Preprint: http://arxiv.org/abs/1202.5488, (2012) [pdf].
- Journal paper
- Authors: M. Le Dung, Q. Tran-Dinh, H.A. Le Thi and T. Pham Dinh
- Title: Decomposition algorithms for globally solving mathematical programs with affine equilibrium constraints
- Journal: Acta Mathematica Vietnamica, Vol. 37, No. 2, pp. 201–218, 2012
- Preprint: http://arxiv.org/abs/1105.3343 [pdf].
- Journal paper
- Authors: Q. Tran-Dinh, A. Pham Ngoc, and M. Le Dung
- Title: Dual extragradient algorithms extended to equilibrium problems Journal: Journal of Global Optimization, Vol. 52, No. 1, pp. 139–159, (2012)
- Link: http://link.springer.com/article/10.1007%2Fs10898-011-9693-2 [pdf].
2011
- Conference paper (CDC)
- Authors: Q. Tran-Dinh, C. Savorgnan and M. Diehl
- Title: Real-Time Sequential Convex Programming for Nonlinear Model Predictive Control and Application to a Hydro-Power Plant
- Proceedings: Proc. of the 50th IEEE Conference on Decision and Control (CDC), Orlando, Florida, USA, 2011
- Link: Can be found here [pdf].
- Journal paper
- Authors: Q. Tran-Dinh and M. Le Dung
- Title: A splitting proximal point method for Nash-Cournot equilibrium models involving nonconvex cost functions
- Journal: Journal of Nonlinear and Convex Analysis, Vol. 12, No. 3, pp. 519–533, 2011.
- Link: http://www.ybook.co.jp/online2/opjnca/vol12/p519.html [pdf].
2o1o
- Book chapter
- Authors: Q. Tran-Dinh and M. Diehl
- Title: Local convergence of sequential convex programming for nonlinear programming
- Book chapter: Diehl, M.; Glineur, F.; Jarlebring, E.; Michiels, W. (Eds.), Recent advances in optimization and its application in engineering, Springer-Verlag, pp. 93–102 (2010)
- Link: http://link.springer.com/chapter/10.1007%2F978-3-642-12598-0_9#page-1 [pdf].
- Journal paper
- Authors: Q. Tran-Dinh and M. Le Dung
- Title: Iterative methods for solving monotone equilibrium problems via dual gap functions
- Journal: Computational Optimization and Applications, Vol. 51, No. 2, pp. 709–728 (2010)
- Link: http://link.springer.com/article/10.1007%2Fs10589-010-9360-4#page-1 [pdf].
- Journal paper
- Authors: M. Le Dung and Q. Tran-Dinh
- Title: One step from DC optimization to DC mixed variational inequalities
- Journal: Optimization, Vol. 59, No 1, 63-76 (2010)
- Link:http://www.tandfonline.com/doi/abs/10.1080/02331930903500282#.U6c0qBZbz1o [pdf].
2009
- Book chapter
- Authors: Q. Tran-Dinh, C. Savorgnan and M. Diehl
- Title: Real-time sequential convex programming for optimal control applications
- Book chapter: In: H.G. Bock, P. Hoang Xuan et al (Eds.), Modeling, Simulation and Optimization of Complex Processes, Springer-Verlag, (2009).
- Preprint: http://arxiv.org/abs/1105.3427 ([pdf]).
- Conference paper (CDC)
- Authors: I. Necoara, C. Savorgnan, Q. Tran-Dinh, J.A.K. Suykens, M. Diehl
- Title: Distributed Nonlinear Optimal Control Using Sequential Convex Programming and Smoothing Techniques
- Proceedings: Proc. of the 48th IEEE Conference on Decision and Control (CDC), Shanghai, China, 2009.
- Link: Can be found here [pdf]
- Conference paper (CDC)
- Authors: Q. Tran-Dinh and M. Diehl
- Title: An application of sequential convex programming methods to time optimal trajectory planning of a car motion
- Proceedings: Proc. of the 48th IEEE Conference on Decision and Control (CDC), Shanghai, China, 4366–4371, 2009
- Link: Can be found here [pdf].
- Journal paper
- Authors: M. Le Dung and Q. Tran-Dinh
- Title: Regularization algorithms for solving monotone equilibrium problems
- Journal: Journal of Optimization Theory and Applications, Vol. 124, 185-204 (2009)
- Link: http://link.springer.com/article/10.1007%2Fs10957-009-9529-0 [pdf].
2008
- Journal paper
- Authors: Q. Tran-Dinh, M. Le Dung, and H. Nguyen Van
- Title: Extragradient algorithms extended to equilibrium problems
- Journal: Optimization, Vol.57, 749-776 (2008)
- Link:http://www.tandfonline.com/doi/abs/10.1080/02331930601122876#.U6c0_xZbz1o [pdf].
Technical reports and unpublished papers
- Unpublished Manuscript – STAT & OR – UNC, May 2019:
- Author: Q. Tran-Dinh, Nhan H. Pham, Dzung T. Phan, and Lam M. Nguyen
- Title: Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization
- Preprint: https://arxiv.org/pdf/1905.05920.pdf.
- Technical Report – STAT & OR – UNC, January 2016
- Author: Q. Tran-Dinh
- Title: Construction and Iteration-Complexity of Primal Sequences in Alternating Minimization Algorithms
- Year: 2015.
- Preprint: http://arxiv.org/abs/1511.03305, (submitted), (2015) [pdf].
- Technical Report, August 2014 (EPFL-REPORT-199844)
- Authors: Q. Tran-Dinh and Volkan Cevher
- Title: A Primal-Dual Algorithmic Framework for Constrained Convex Minimization
- Year: 2014.
- Preprint: http://arxiv.org/abs/1406.5403 [pdf]
- Unpublished manuscript
- Authors: Q. Tran-Dinh and M. Diehl
- Title: Proximal methods for minimizing the sum of a convex function and a composite function
- Preprint: http://arxiv.org/abs/1105.0276, (2010) [pdf].
- Unpublished manuscript
- Authors: Q. Tran-Dinh and M. Diehl
- Title: Sequential Convex Programming Methods for Solving Nonlinear Optimization Problems with DC constraints
- Year: 2009.
- Preprint: Online at: http://arxiv.org/abs/1107.5841, (2009) [pdf].
Ph.D. Thesis
- Author: Q. Tran-Dinh
- Title: Sequential Convex Programming and Decomposition Approaches for Nonlinear Optimization
- Year: November 2012
- Place: Department of Electrical Engineering (ESAT), and Optimization in Engineering Center (OPTEC), KU Leuven, Belgium.
- Link: https://lirias.kuleuven.be/handle/123456789/359872, November, 2012, [pdf].
- Preprint: The preprint is available HERE.
Co-authors
Some co-authors of my work are listed here, but not a complete list.
- Moritz Diehl – KU Leuven, ESAT and OPTEC, Belgium.
- Ion Necoara – Automation and System Engineering Department, University Politehnica Bucharest, Romania.
- Carlo Savorgnan – KU Leuven, ESAT and OPTEC, Belgium.
- Le Dung Muu – Institute of Mathematics, Hanoi, Vietnam.
- Pham Ngoc Anh – Posts and Telecommunications Institute of Technology, Hanoi, Vietnam.
- Nguyen Van Hien – FUNDP Namur, Belgium.
- Johan Suykens – KU Leuven, ESAT and OPTEC, Belgium.
- Marco Signoretto – KU Leuven, ESAT and OPTEC, Belgium.
- Le Thi Hoai An – Universite Paul Verlaine – Metz, France.
- Pham Dinh Tao – INSA, Rouen, France.
- Suat Gumussoy – CS Department, KU Leuven, Belgium.
- Wim Michiels – CS Department, KU Leuven, Belgium.
- Volkan Cevher – Laboratory for Information and Inference Systems (LIONS), EPFL.
- Anastasios Kyrillidis – Laboratory for Information and Inference Systems (LIONS), EPFL.