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Lam M. Nguyen
Lam M. Nguyen
Staff Research Scientist at IBM Research; IBM Master Inventor
Verified email at ibm.com - Homepage
Title
Cited by
Cited by
Year
SARAH: A novel method for machine learning problems using stochastic recursive gradient
LM Nguyen, J Liu, K Scheinberg, M Takáč
The 34th International Conference on Machine Learning (ICML 2017), 2017
6172017
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption
LM Nguyen, PH Nguyen, M van Dijk, P Richtárik, K Scheinberg, M Takác
The 35th International Conference on Machine Learning (ICML 2018), 2018
2292018
ProxSARAH: An efficient algorithmic framework for stochastic composite nonconvex optimization
NH Pham, LM Nguyen, DT Phan, Q Tran-Dinh
Journal of Machine Learning Research 21 (110), 1-48, 2020
1382020
Stochastic recursive gradient algorithm for nonconvex optimization
LM Nguyen, J Liu, K Scheinberg, M Takáč
Technical Report, arXiv:1705.07261, 2017
1112017
PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach
TW Weng, PY Chen, LM Nguyen, MS Squillante, A Boopathy, I Oseledets, ...
The 36th International Conference on Machine Learning (ICML 2019), 2019
872019
Finite-Sum Smooth Optimization with SARAH
LM Nguyen, M van Dijk, DT Phan, PH Nguyen, TW Weng, ...
Computational Optimization and Applications, 2022
68*2022
Label-free Concept Bottleneck Models
T Oikarinen, S Das, LM Nguyen, TW Weng
The 11th International Conference on Learning Representations (ICLR 2023), 2023
662023
A unified convergence analysis for shuffling-type gradient methods
LM Nguyen, Q Tran-Dinh, DT Phan, PH Nguyen, M van Dijk
Journal of Machine Learning Research, 2021, 2021
642021
New convergence aspects of stochastic gradient algorithms
LM Nguyen, PH Nguyen, P Richtárik, K Scheinberg, M Takáč, M van Dijk
Journal of Machine Learning Research 20 (176), 1-49, 2019
622019
A hybrid stochastic optimization framework for composite nonconvex optimization
Q Tran-Dinh, NH Pham, DT Phan, LM Nguyen
Mathematical Programming 191 (2), 1005-1071, 2022
582022
Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization
Q Tran-Dinh, NH Pham, DT Phan, LM Nguyen
Technical Report, arXiv:1905.05920, 2019
532019
Inexact SARAH algorithm for stochastic optimization
LM Nguyen, K Scheinberg, M Takáč
Optimization Methods and Software 36 (1), 237-258, 2021
522021
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees
H Zhu, P Murali, DT Phan, LM Nguyen, JR Kalagnanam
The 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 2020
432020
CEO Compensation: Does Financial Crisis Matter?
P Vemala, L Nguyen, D Nguyen, A Kommasani
International Business Research 7 (4), 125-131, 2014
382014
Hybrid Variance-Reduced SGD Algorithms For Nonconvex-Concave Minimax Problems
Q Tran-Dinh, D Liu, LM Nguyen
The 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 2020
35*2020
Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD
PH Nguyen, LM Nguyen, M van Dijk
The 33th Conference on Neural Information Processing Systems (NeurIPS 2019), 2019
32*2019
FedDR–Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization
Q Tran-Dinh, NH Pham, DT Phan, LM Nguyen
The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021
312021
Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise
M van Dijk, NV Nguyen, TN Nguyen, LM Nguyen, Q Tran-Dinh, ...
Technical Report, arXiv:2007.09208, 2020
312020
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization
Q Tran-Dinh, NH Pham, LM Nguyen
The 37th International Conference on Machine Learning (ICML 2020), 2020
272020
Ensembling Graph Predictions for AMR Parsing
HT Lam, G Picco, Y Hou, YS Lee, LM Nguyen, DT Phan, V López, ...
The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021
26*2021
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Articles 1–20