Lam Nguyen
17 papers · 2018–2025 · 5 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (5) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (7)
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Conference Polyglot
(5)
🏃
Academic Marathon
(7)
🐝
Cross-Pollinator
(10)
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Keyword Champion
(2)
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Keyword Collector
(91)
💎
Century Club
(17)
⚡
Prolific Year
(5)
Conferences
NIPS (8)
ICML (4)
AAAI (2)
AISTATS (2)
ACL (1)
Top co-authors
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