Lam M. Nguyen  Lam M. Nguyen photo         

contact information

Research Staff Member
Thomas J. Watson Research Center, Yorktown Heights, NY USA
  

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Professional Associations

Professional Associations:  INFORMS  |  SIAM Optimization Activity Group

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More information:  Personal Website


2021

Ensuring the Quality of Optimization Solutions in Data Generated Optimization Models
Segev Wasserkrug, Orit Davidovith, Evgeny Shindin, Dharmashankar Subramanian, Parikshit Ram, Pavankumar Murali, Dzung Phan, Nianjun Zhou, Lam M. Nguyen
The 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), Data Science Meets Optimisation, DSO@IJCAI2021

Federated Learning with Randomized Douglas-Rachford Splitting Methods
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh
Technical Report, arXiv preprint, 2021

Differential Private Hogwild! over Distributed Local Data Sets
Marten van Dijk, Nhuong V. Nguyen, Toan N. Nguyen, Lam M. Nguyen, Phuong Ha Nguyen
Technical Report, arXiv preprint, 2021

Regression Optimization for System-level Production Control
Dzung T. Phan, Lam M. Nguyen, Pavankumar Murali, Nhan H. Pham, Hongsheng Liu, Jayant R. Kalagnanam
The 2021 American Control Conference (ACC 2021)

SMG: A Shuffling Gradient-Based Method with Momentum
Trang H. Tran, Lam M. Nguyen, Quoc Tran-Dinh
The 38th International Conference on Machine Learning (ICML 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
The 24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021)

A Hybrid Stochastic Optimization Framework for Composite Nonconvex Optimization
Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen
Mathematical Programming, Springer, 2021


2020


A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees
Haoran Zhu, Pavankumar Murali, Dzung T. Phan, Lam M. Nguyen, Jayant R. Kalagnanam.
The 34th Conference on Neural Information Processing Systems (NeurIPS 2020)

Pruning Deep Neural Networks with L0-constrained Optimization
Dzung T. Phan, Lam M. Nguyen, Nam H. Nguyen, Jayant R. Kalagnanam
The 20th IEEE International Conference on Data Mining (ICDM 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
Technical Report, arXiv preprint, 2020

Hybrid Variance-Reduced SGD Algorithms For Nonconvex-Concave Minimax Problems
Quoc Tran-Dinh, Deyi Liu, Lam M. Nguyen
The 34th Conference on Neural Information Processing Systems (NeurIPS 2020)

Finite-Time Analysis of Stochastic Gradient Descent under Markov Randomness
Thinh T. Doan, Lam M. Nguyen, Nhan H. Pham, Justin Romberg
Technical Report, arXiv preprint, 2020

A Unified Convergence Analysis for Shuffling-Type Gradient Methods
Lam M. Nguyen, Quoc Tran-Dinh, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk
Technical Report, arXiv preprint, 2020

Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization
Quoc Tran-Dinh, Nhan H. Pham, Lam M. Nguyen
The 37th International Conference on Machine Learning (ICML 2020)

Convergence Rates of Accelerated Markov Gradient Descent with Applications in Reinforcement Learning
Thinh T. Doan, Lam M. Nguyen, Nhan H. Pham, Justin Romberg
Technical Report, arXiv preprint, 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
The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020)

ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh
Journal of Machine Learning Research (JMLR)21, 1-48, 2020

Inexact SARAH Algorithm for Stochastic Optimization
Lam M. Nguyen, Katya Scheinberg, Martin Takac
Optimization Methods and Software 36(1), Taylor & Francis Online, 2020


2019

BUZz: BUffer Zones for Defending Adversarial examples in Image Classification
Phuong Ha Nguyen*, Kaleel Mahmood*, Lam M. Nguyen, Thanh Nguyen, Marten van Dijk
Technical Report, arXiv preprint, 2019

Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization
Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan, Lam M. Nguyen
Technical Report, arXiv preprint, 2019

Finite-Sum Smooth Optimization with SARAH
Lam M. Nguyen, Marten van Dijk, Dzung T. Phan, Phuong Ha Nguyen, Tsui-Wei Weng, Jayant R. Kalagnanam
Technical Report, arXiv preprint, 2019

PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach
Tsui-Wei Weng, Pin-Yu Chen*, Lam M. Nguyen*, Mark S. Squillante*, Akhilan Boopathy, Ivan Oseledets, Luca Daniel
The 36th International Conference on Machine Learning (ICML 2019), Proceedings of Machine Learning Research

New Convergence Aspects of Stochastic Gradient Algorithms
Lam M. Nguyen, Phuong Ha Nguyen, Peter Richtarik, Katya Scheinberg, Martin Takac, Marten van Dijk
Journal of Machine Learning Research (JMLR)20, 2019

Tight Dimension Independent Lower Bound on Optimal Expected Convergence Rate for Diminishing Step Sizes in SGD
Phuong Ha Nguyen, Lam M. Nguyen, Marten van Dijk
The 33th Annual Conference on Neural Information Processing Systems (NeurIPS 2019)

Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD
Marten van Dijk, Lam M. Nguyen, Phuong Ha Nguyen, Dzung T. Phan
The 36th International Conference on Machine Learning (ICML 2019), Proceedings of Machine Learning Research


2018

ChieF: A Change Pattern based Interpretable Failure Analyzer
Dhaval Patel, Lam M. Nguyen, Akshay Rangamani, Shrey Shrivastava, Jayant Kalagnanam
2018 IEEE International Conference on Big Data (IEEE BigData 2018), IEEE

When Does Stochastic Gradient Algorithm Work Well?
Lam M. Nguyen, Nam H. Nguyen, Dzung T. Phan, Jayant R. Kalagnanam, Katya Scheinberg
Technical Report, arXiv preprint, 2018

SGD and Hogwild! Convergence Without the Bounded Gradients Assumption
Lam M. Nguyen, Phuong Ha Nguyen, Marten van Dijk, Peter Richtarik, Katya Scheinberg, Martin Takac
The 35th International Conference on Machine Learning (ICML 2018), Proceedings of Machine Learning Research


2017

SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takac
The 34th International Conference on Machine Learning (ICML 2017), Proceedings of Machine Learning Research

A Queueing System with On-demand Servers: Local Stability of Fluid Limits
Lam M. Nguyen, Alexander L. Stolyar
Queueing Systems89, 243-268, Springer, 2017

Stochastic Recursive Gradient Algorithm for Nonconvex Optimization
Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takac
Technical Report, arXiv preprint, 2017


2016

A Service System with Randomly Behaving On-demand Agents
Lam M. Nguyen, Alexander L. Stolyar
The 42nd International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS 2016), ACM SIGMETRICS Performance Evaluation Review


2014

CEO Compensation: Does Financial Crisis Matter?
Prasad Vemala, Lam Nguyen, Dung Nguyen, Alekhya Kommasani
International Business Research, 125-131, 2014