Lam Nguyen
18 papers · 2018–2026 · 6 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (38)
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(6)
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Research topics
Machine Learning
(15)
Optimization & Theory Β· Machine Learning
(11)
Mathematics & Optimization
(10)
Optimization
(10)
Deep Learning
(6)
Artificial Intelligence
(5)
Core Methods
(4)
Application Areas
(3)
Core AI
(3)
Optimization & Theory Β· Deep Learning
(3)
Computer Vision
(2)
Architectures
(2)
Learning Paradigms
(2)
Data Science & Analytics
(1)
Natural Language Processing
(1)
Keywords
stochastic gradient descent
(5)
non-convex optimization
(4)
stochastic optimization
(3)
convergence rate
(2)
oracle complexity
(2)
support vector machine
(2)
robustness certificate
(2)
adversarial robustness
(1)
convex optimization
(1)
stochastic gradient
(1)
binary classification
(1)
density estimation
(1)
video segmentation
(1)
policy gradient
(1)
convergence analysis
(1)
reinforcement learning
(1)
global convergence
(1)
prompt engineering
(1)
action recognition
(1)
machine translation
(1)
Papers
Verifying Neural Network Robustness with Dual Perturbations
CVPR 2026
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
NeurIPS 2023
On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms
NeurIPS 2023
Ensembling Graph Predictions for AMR Parsing
NeurIPS 2021
FedDR β Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization
NeurIPS 2021
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes
AISTATS 2021
Interactive Video Object Mask Annotation
AAAI 2021
On the Equivalence between Neural Network and Support Vector Machine
NeurIPS 2021
A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning
AISTATS 2020
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees
NeurIPS 2020
Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function
NeurIPS 2020
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization
ICML 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
NeurIPS 2019
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption
ICML 2018