Lam M. Nguyen  Lam M. Nguyen photo         

contact information

Research Scientist
Thomas J. Watson Research Center, Yorktown Heights, NY USA
  

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Professional Associations

Professional Associations:  INFORMS  |  SIAM Optimization Activity Group

more information

More information:  Personal Website


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
Technical Report, arXiv preprint, 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
Accepted to Journal of Machine Learning Research (JMLR) conditioned on minor revisions, 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

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

Inexact SARAH Algorithm for Stochastic Optimization
Lam M. Nguyen, Katya Scheinberg, Martin Takac
Technical Report, arXiv preprint, 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