@InProceedings{Nguyen2017_sarah,
  title = {{SARAH}: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient},
  author = {Lam M. Nguyen and Jie Liu and Katya Scheinberg and Martin Takac},
  booktitle = {Proceedings of the 34th International Conference on Machine Learning},
  pages = {2613--2621},
  year = {2017},
  volume = {70},
  series = {Proceedings of Machine Learning Research},
}

@article{Nguyen2017_sarahnonconvex,
  author    = {Lam M. Nguyen and
               Jie Liu and
               Katya Scheinberg and
               Martin Tak{\'{a}}c},
  title     = {Stochastic Recursive Gradient Algorithm for Nonconvex Optimization},
  journal   = {CoRR},
  volume    = {abs/1705.07261},
  year      = {2017},
  biburl    = {http://dblp.org/rec/bib/journals/corr/NguyenLST17a}
}

@article{Nguyen2020_iSARAH_GOMS,
author = {Lam M.   Nguyen  and  Katya   Scheinberg  and  Martin Takac},
title = {Inexact SARAH Algorithm for Stochastic Optimization},
journal = {Optimization Methods and Software},
volume = {0},
number = {0},
pages = {1-22},
year = {2020},
publisher = {Taylor & Francis},
doi = {10.1080/10556788.2020.1818081},
}

@ARTICLE{Nguyen2019_SARAH,
  author = {Lam M. Nguyen and Marten van Dijk and Dzung T. Phan and Phuong Ha Nguyen and Tsui-Wei Weng and Jayant R. Kalagnanam},
  title = {Finite-Sum Smooth Optimization with SARAH},
  journal = {arXiv preprint arXiv:1901.07648},
  year = {2019}
}

@article{Pham2020_ProxSARAH,
  author  = {Nhan H. Pham and Lam M. Nguyen and Dzung T. Phan and Quoc Tran-Dinh},
  title   = {ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization},
  journal = {Journal of Machine Learning Research},
  year    = {2020},
  volume  = {21},
  number  = {110},
  pages   = {1-48},
  url     = {http://jmlr.org/papers/v21/19-248.html}
}

@ARTICLE{Tran-Dinh2019_Hybrid_Composite,
  author = {Quoc Tran-Dinh and Nhan H. Pham and Dzung T. Phan and Lam M. Nguyen},
  title = {A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization},
  journal = {arXiv preprint arXiv:1907.03793},
  year = {2019}
}

@InProceedings{Pham2020_HyrbidRL,
  title = 	 {A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning},
  author = 	 {Pham, Nhan and Nguyen, Lam and Phan, Dzung and Nguyen, Phuong Ha and van Dijk, Marten and Tran-Dinh, Quoc},
  booktitle = 	 {Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics},
  pages = 	 {374--385},
  year = 	 {2020},
  editor = 	 {Chiappa, Silvia and Calandra, Roberto},
  volume = 	 {108},
  series = 	 {Proceedings of Machine Learning Research},
  address = 	 {Online},
  month = 	 {26--28 Aug},
  publisher = 	 {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v108/pham20a/pham20a.pdf},
  url = 	 {http://proceedings.mlr.press/v108/pham20a.html}
}

@ARTICLE{Tran-Dinh2020_SGN,
  author = {Quoc Tran-Dinh and Nhan H. Pham and Lam M. Nguyen},
  title = {Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization},
  journal = {arXiv preprint arXiv:2002.07290},
  year = {2020}
}

@ARTICLE{TranDinh2020_HybridMinMax,
  author = {Quoc Tran-Dinh and Deyi Liu and Lam M. Nguyen},
  title = {Hybrid Variance-Reduced SGD Algorithms For Nonconvex-Concave Minimax Problems},
  journal = {arXiv preprint arXiv:2006.15266},
  year = {2020}
}

@InProceedings{Nguyen2018_sgdhogwild,
  title = 	 {{SGD} and {H}ogwild! {C}onvergence Without the Bounded Gradients Assumption},
  author = 	 {Nguyen, Lam and Nguyen, Phuong Ha and van Dijk, Marten and Richtarik, Peter and Scheinberg, Katya and Takac, Martin},
  booktitle = 	 {Proceedings of the 35th International Conference on Machine Learning},
  pages = 	 {3747--3755},
  year = 	 {2018},
  volume = 	 {80},
  series = 	 {Proceedings of Machine Learning Research}
}

@article{Nguyen2019_sgd_new_aspects,
  author  = {Lam M. Nguyen and Phuong Ha Nguyen and Peter Richt{{\'a}}rik and Katya Scheinberg and Martin Tak{{\'a}}{\v{c}} and Marten van Dijk},
  title   = {New Convergence Aspects of Stochastic Gradient Algorithms},
  journal = {Journal of Machine Learning Research},
  year    = {2019},
  volume  = {20},
  number  = {176},
  pages   = {1-49},
  url     = {http://jmlr.org/papers/v20/18-759.html}
}

@InProceedings{vanDijk2018_sgdconvex,
  title = 	 {Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD},
  author = 	 {Marten van Dijk and Lam M. Nguyen and Phuong Ha Nguyen and Dzung T. Phan},
  booktitle = 	 {Proceedings of the 36th International Conference on Machine Learning},
  pages = 	 {6392--6400},
  year = 	 {2019},
  volume = 	 {97},
  series = 	 {Proceedings of Machine Learning Research}
}

@incollection{NIPS2019_8624,
title = {Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD},
author = {NGUYEN, PHUONG\_HA and Nguyen, Lam and van Dijk, Marten},
booktitle = {Advances in Neural Information Processing Systems 32},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {3660--3669},
year = {2019},
publisher = {Curran Associates, Inc.},
url = {http://papers.nips.cc/paper/8624-tight-dimension-independent-lower-bound-on-the-expected-convergence-rate-for-diminishing-step-sizes-in-sgd.pdf}
}

@ARTICLE{vanDijk_HogwildDistributed,
  author = {Marten van Dijk and Nhuong V. Nguyen and Toan N. Nguyen and Lam M. Nguyen and Quoc Tran-Dinh and Phuong Ha Nguyen},
  title = {Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes},
  journal = {arXiv preprint arXiv:2010.14763},
  year = {2020}
}

@ARTICLE{Nguyen2024_ISTA,
  author = {Lam M. Nguyen and Katya Scheinberg and Trang H. Tran},
  title = {Stochastic ISTA/FISTA Adaptive Step Search Algorithms for Convex Composite Optimization},
  journal = {arXiv preprint arXiv:2402.15646},
  year = {2024}
}

@article{Nguyen2021ShufflingUnified,
  author  = {Lam M. Nguyen and Quoc Tran-Dinh and Dzung T. Phan and Phuong Ha Nguyen and Marten van Dijk},
  title   = {A Unified Convergence Analysis for Shuffling-Type Gradient Methods},
  journal = {Journal of Machine Learning Research},
  year    = {2021},
  volume  = {22},
  number  = {207},
  pages   = {1-44},
  url     = {http://jmlr.org/papers/v22/20-1238.html}
}

@InProceedings{pmlr-v139-tran21b,
  title = 	 {SMG: A Shuffling Gradient-Based Method with Momentum},
  author =       {Tran, Trang H and Nguyen, Lam M and Tran-Dinh, Quoc},
  booktitle = 	 {Proceedings of the 38th International Conference on Machine Learning},
  pages = 	 {10379--10389},
  year = 	 {2021},
  editor = 	 {Meila, Marina and Zhang, Tong},
  volume = 	 {139},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {18--24 Jul},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v139/tran21b/tran21b.pdf},
  url = 	 {http://proceedings.mlr.press/v139/tran21b.html}
}

@InProceedings{Tran2022_ShufflingNesterov,
  title = 	 {{N}esterov Accelerated Shuffling Gradient Method for Convex Optimization},
  author =       {Tran, Trang H and Scheinberg, Katya and Nguyen, Lam M},
  booktitle = 	 {Proceedings of the 39th International Conference on Machine Learning},
  pages = 	 {21703--21732},
  year = 	 {2022},
  editor = 	 {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
  volume = 	 {162},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {17--23 Jul},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v162/tran22a/tran22a.pdf},
  url = 	 {https://proceedings.mlr.press/v162/tran22a.html}
}

@ARTICLE{Nguyen2022_SGDPL,
  author = {Lam M. Nguyen and Trang H. Tran},
  title = {On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms},
  journal = {arXiv preprint arXiv:2206.05869},
  year = {2022}
}

@ARTICLE{Nguyen2022_OptDL,
  author = {Lam M. Nguyen and Trang H. Tran and Marten van Dijk},
  title = {Finite-Sum Optimization: A New Perspective for Convergence to a Global Solution},
  journal = {arXiv preprint arXiv:2202.03524},
  year = {2022}
}

@ARTICLE{Nguyen2022_SGDPL,
  author = {Lam M. Nguyen and Trang H. Tran},
  title = {On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms},
  journal = {arXiv preprint arXiv:2206.05869},
  year = {2022}
}

@ARTICLE{Nguyen2023_RobustTimeSeries,
  author = {Anh Duy Nguyen and Trang H. Tran and Hieu H. Pham and Phi Le Nguyen and Lam M. Nguyen},
  title = {Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient Encoder},
  journal = {arXiv preprint arXiv:2306.06579},
  year = {2023}
}

@ARTICLE{Tran2023_AdaptiveTimeSeries,
  author = {Trang H. Tran and Lam M. Nguyen and Kyongmin Yeo and Nam Nguyen and Dzung Phan and Roman Vaculin and Jayant Kalagnanam},
  title = {An End-to-End Time Series Model for Simultaneous Imputation and Forecast},
  journal = {arXiv preprint arXiv:2306.00778},
  year = {2023}
}

@ARTICLE{Nguyen2023_CAB,
  author = {Quang Minh Nguyen and Lam M. Nguyen and Subhro Das},
  title = {Correlated Attention in Transformers for Multivariate Time Series},
  journal = {arXiv preprint arXiv:2311.11959},
  year = {2023}
}

@ARTICLE{Tran2023_SCLTS,
  author = {Trang H. Tran and Lam M. Nguyen and Kyongmin Yeo and Nam Nguyen and Roman Vaculin},
  title = {A Supervised Contrastive Learning Pretrain-Finetune Approach for Time Series},
  journal = {arXiv preprint arXiv:2311.12290},
  year = {2023}
}

@ARTICLE{zhang2023_concernet,
  author = {Wang Zhang and Tsui-Wei Weng and Subhro Das and Alexandre Megretski and Luca Daniel and Lam M. Nguyen},
  title = {ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction},
  journal = {arXiv preprint arXiv:2302.05783},
  year = {2023}
}

@inproceedings{Zhang2024_UncertaintyAAAI2024,
  title={One Step Closer to Unbiased Aleatoric Uncertainty Estimation},
  author={Wang Zhang and Martin Ma and Subhro Das and Lily Weng and Alexandre Megretsky and Luca Daniel and Lam M. Nguyen},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  year={2024}
}

@article{Nguyen2016_agent,
 author = {Nguyen, Lam M. and Stolyar, Alexander L.},
 title = {A Service System with Randomly Behaving On-demand Agents},
 journal = {SIGMETRICS Perform. Eval. Rev.},
 issue_date = {June 2016},
 volume = {44},
 number = {1},
 month = jun,
 year = {2016},
 issn = {0163-5999},
 pages = {365--366},
 numpages = {2},
 url = {http://doi.acm.org/10.1145/2964791.2901484},
 doi = {10.1145/2964791.2901484},
 acmid = {2901484},
 publisher = {ACM},
 address = {New York, NY, USA},
}

@Article{Nguyen2017_fluid,
author = "Nguyen, Lam M. and Stolyar, Alexander L.",
title = "A queueing system with on-demand servers: local stability of fluid limits",
journal = "Queueing Systems",
year = "2017",
month = "Nov",
day = "22",
issn = "1572-9443",
doi = "10.1007/s11134-017-9564-8",
url = "https://doi.org/10.1007/s11134-017-9564-8"
}

@InProceedings{Pham2020_HyrbidRL,
  title = 	 {A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning},
  author = 	 {Pham, Nhan and Nguyen, Lam and Phan, Dzung and Nguyen, Phuong Ha and van Dijk, Marten and Tran-Dinh, Quoc},
  booktitle = 	 {Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics},
  pages = 	 {374--385},
  year = 	 {2020},
  editor = 	 {Chiappa, Silvia and Calandra, Roberto},
  volume = 	 {108},
  series = 	 {Proceedings of Machine Learning Research},
  address = 	 {Online},
  month = 	 {26--28 Aug},
  publisher = 	 {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v108/pham20a/pham20a.pdf},
  url = 	 {http://proceedings.mlr.press/v108/pham20a.html}
}

@ARTICLE{Pham2022_MARL,
  author = {Nhan H. Pham and Lam M. Nguyen and Jie Chen and Hoang Thanh Lam and Subhro Das and Tsui-Wei Weng},
  title = {Evaluating Robustness of Cooperative MARL: A Model-based Approach},
  journal = {arXiv preprint arXiv:2202.03558},
  year = {2022}
}

@article{zhu2020scalable,
  title={A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees},
  author={Zhu, Haoran and Murali, Pavankumar and Phan, Dzung T and Nguyen, Lam M and Kalagnanam, Jayant R}
}

@INPROCEEDINGS{9482638,
  author={Phan, Dzung T. and Nguyen, Lam M. and Murali, Pavankumar and Pham, Nhan H. and Liu, Hongsheng and Kalagnanam, Jayant R.},
  booktitle={2021 American Control Conference (ACC)}, 
  title={Regression Optimization for System-level Production Control}, 
  year={2021},
  volume={},
  number={},
  pages={5023-5028},
  doi={10.23919/ACC50511.2021.9482638}}

@INPROCEEDINGS{9482638,
  author={Lima, Vinicius and Phan, Dzung T. and Nguyen, Lam M. and Kalagnanam, Jayant R.},
  booktitle={2021 American Control Conference (ACC)}, 
  title={Regression Optimization for System-level Production Control}, 
  year={2023},
  volume={},
  number={},
  pages={},
  doi={}}

@ARTICLE{Nguyen2023_UOT_JMLR,
  author = {Quang Minh Nguyen and Hoang H. Nguyen and Yi Zhou and Lam M. Nguyen},
  title = {On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error},
  journal = {arXiv preprint arXiv:2202.03618},
  year = {2022}
}

@inproceedings{Nguyen2024_POT_AAAI2024,
  title={On Partial Optimal Transport: Revised Sinkhorn and Efficient Gradient Methods},
  author={Anh Duc Nguyen and Tuan Dung Nguyen and Quang Nguyen and Hoang Nguyen and Lam M. Nguyen and Kim-Chuan Toh},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  year={2024}
}

@InProceedings{Weng2018_PROVEN,
  title = 	 {PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach},
  author = 	 {Tsui-Wei Weng and Pin-Yu Chen and Lam M. Nguyen and Mark S. Squillante and Akhilan Boopathy and Ivan Oseledets and Luca Daniel},
  booktitle = 	 {Proceedings of the 36th International Conference on Machine Learning},
  pages = 	 {6727--6736},
  year = 	 {2019},
  volume = 	 {97},
  series = 	 {Proceedings of Machine Learning Research}
}

@ARTICLE{Nguyen2019_Buzz,
  author = {Phuong Ha Nguyen and Kaleel Mahmood and Lam M. Nguyen and Thanh Nguyen and and Marten van Dijk},
  title = {BUZz: BUffer Zones for Defending Adversarial Examples in Image Classification},
  journal = {arXiv preprint arXiv:1910.02785},
  year = {2019}
}

@INPROCEEDINGS{9482638,
  author={Oikarinen, Tuomas and Das, Subhro and Nguyen, Lam M. and Weng, Tsui-Wei},
  booktitle={International Conference on Learning Representations (ICLR 2023)}, 
  title={Label-free Concept Bottleneck Models}, 
  year={2023},
  volume={},
  number={},
  pages={},
  doi={}}

@ARTICLE{Pham2022_MARL,
  author = {Nhan H. Pham and Lam M. Nguyen and Jie Chen and Hoang Thanh Lam and Subhro Das and Tsui-Wei Weng},
  title = {Evaluating Robustness of Cooperative MARL: A Model-based Approach},
  journal = {arXiv preprint arXiv:2202.03558},
  year = {2022}
}

@ARTICLE{vanDijk_HogwildDistributed,
  author = {Marten van Dijk and Nhuong V. Nguyen and Toan N. Nguyen and Lam M. Nguyen and Quoc Tran-Dinh and Phuong Ha Nguyen},
  title = {Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes},
  journal = {arXiv preprint arXiv:2010.14763},
  year = {2020}
}

@ARTICLE{TranDinh2021_FLDR,
  author = {Quoc Tran-Dinh and Nhan H. Pham and Dzung T. Phan and Lam M. Nguyen},
  title = {FedDR -- Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization},
  journal = {arXiv preprint arXiv:2103.03452},
  year = {2021}
}

@INPROCEEDINGS{Nguyen2023_FedXGBoost,
  author={Quang Nguyen and Nhan Khanh Le and Lam M. Nguyen},
  booktitle={The 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023)}, 
  title={Scalable and Secure Federated XGBoost}, 
  year={2023},
  volume={},
  number={},
  pages={},
  doi={}}