← Authors

Lam Nguyen

17 papers · 2018–2025 · 5 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (38) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (7) 🐝 Cross-Pollinator (10) πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (91) πŸ’Ž Century Club (17) ⚑ Prolific Year (5)

Conferences

NIPS (8) ICML (4) AAAI (2) AISTATS (2) ACL (1)

Top co-authors

Dzung Phan (5) PHUONG HA NGUYEN (4) Quoc Tran-Dinh (3) Marten van Dijk (3) Yilan Chen (2) Lily Weng (2) Quoc Tran Dinh (2) Marten Dijk (2) Wei Huang (2) Nhan Pham (2)

Keywords

stochastic gradient descent (5) stochastic optimization (3) convergence rate (2) oracle complexity (2) support vector machine (2) non-convex optimization (2) robustness certificate (2) nonconvex optimization (2) adversarial robustness (1) binary classification (1) stochastic gradient (1) convex optimization (1) density estimation (1) video segmentation (1) global convergence (1) reinforcement learning (1) prompt engineering (1) machine translation (1) action recognition (1) graph prediction (1)

Papers

Reasoning for Translation: Comparative Analysis of Chain-of-Thought and Tree-of-Thought Prompting for LLM Translation ACL 2025
Count What You Want: Exemplar Identification and Few-Shot Counting of Human Actions in the Wild AAAI 2024
Analyzing Generalization of Neural Networks through Loss Path Kernels NIPS 2023
On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms NIPS 2023
FedDR – Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization NIPS 2021
Interactive Video Object Mask Annotation AAAI 2021
Ensembling Graph Predictions for AMR Parsing NIPS 2021
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes AISTATS 2021
On the Equivalence between Neural Network and Support Vector Machine NIPS 2021
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization ICML 2020
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees NIPS 2020
Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function NIPS 2020
A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning AISTATS 2020
Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD ICML 2019
PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach ICML 2019
Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD NIPS 2019
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption ICML 2018