Nguyen, Lam M.

21 publications

NeurIPS 2024 Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-Series Classification Yunshi Wen, Tengfei Ma, Tsui-Wei Weng, Lam M. Nguyen, Anak Agung Julius

NeurIPSW 2024 Guaranteeing Conservation Laws with Projection in Physics-Informed Neural Networks Anthony Baez, Wang Zhang, Ziwen Ma, Subhro Das, Lam M. Nguyen, Luca Daniel

AAAI 2024 On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods Anh Duc Nguyen, Tuan Dung Nguyen, Quang Minh Nguyen, Hoang H. Nguyen, Lam M. Nguyen, Kim-Chuan Toh

AAAI 2024 One Step Closer to Unbiased Aleatoric Uncertainty Estimation Wang Zhang, Ziwen Martin Ma, Subhro Das, Tsui-Wei Lily Weng, Alexandre Megretski, Luca Daniel, Lam M. Nguyen

ICML 2024 Proactive DP: A Multiple Target Optimization Framework for DP-SGD Marten Van Dijk, Nhuong Van Nguyen, Toan N. Nguyen, Lam M. Nguyen, Phuong Ha Nguyen

NeurIPS 2024 Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data Pei-Yau Weng, Minh Hoang, Lam M. Nguyen, My T. Thai, Tsui-Wei Weng, Trong Nghia Hoang

NeurIPS 2024 Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization Quoc Tran-Dinh, Trang H. Tran, Lam M. Nguyen

ICML 2023 ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen

ICLR 2023 Label-Free Concept Bottleneck Models Tuomas Oikarinen, Subhro Das, Lam M. Nguyen, Tsui-Wei Weng

JMLR 2023 On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error Quang Minh Nguyen, Hoang H. Nguyen, Yi Zhou, Lam M. Nguyen

NeurIPSW 2023 Stochastic FISTA Step Search Algorithm for Convex Optimization Trang H. Tran, Lam M. Nguyen, Katya Scheinberg

ICMLW 2022 Fast Convergence for Unstable Reinforcement Learning Problems by Logarithmic Mapping Wang Zhang, Lam M. Nguyen, Subhro Das, Alexandre Megretski, Luca Daniel, Tsui-Wei Weng

NeurIPSW 2022 C-MBA: Adversarial Attack for Cooperative MARL Using Learned Dynamics Model Nhan H Pham, Lam M. Nguyen, Jie Chen, Hoang Thanh Lam, Subhro Das, Lily Weng

AAAI 2022 Interpretable Clustering via Multi-Polytope Machines Connor Lawless, Jayant Kalagnanam, Lam M. Nguyen, Dzung T. Phan, Chandra Reddy

ICML 2022 Nesterov Accelerated Shuffling Gradient Method for Convex Optimization Trang H Tran, Katya Scheinberg, Lam M Nguyen

ICLRW 2022 Robust Randomized Smoothing via Two Cost-Effective Approaches Linbo Liu, Trong Nghia Hoang, Lam M. Nguyen, Tsui-Wei Weng

JMLR 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

ICML 2021 SMG: A Shuffling Gradient-Based Method with Momentum Trang H Tran, Lam M Nguyen, Quoc Tran-Dinh

JMLR 2020 ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Quoc Tran-Dinh

JMLR 2019 New Convergence Aspects of Stochastic Gradient Algorithms Lam M. Nguyen, Phuong Ha Nguyen, Peter Richtárik, Katya Scheinberg, Martin Takáč, Marten van Dijk

ICML 2017 SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takáč