Lam M. Nguyen
13 papers · 2017–2024 · 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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Interdisciplinary Bridge
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Conference Polyglot
(5)
🏃
Academic Marathon
(7)
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Keyword Champion
(3)
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Grand Slam
🗃️
Keyword Collector
(66)
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Century Club
(13)
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Prolific Year
(6)
Conferences
JMLR (4)
ICML (3)
NIPS (3)
AAAI (2)
ICLR (1)
Top co-authors
Keywords
gradient method
(3)
domain adaptation
(2)
variance reduction
(2)
stochastic optimization
(2)
stochastic gradient descent
(2)
nonconvex optimization
(2)
convergence analysis
(2)
sinkhorn algorithm
(2)
oracle complexity
(2)
zero-shot learning
(1)
uncertainty quantification
(1)
computer vision
(1)
epistemic uncertainty
(1)
optimal transport
(1)
stochastic gradient
(1)
probabilistic modeling
(1)
contrastive learning
(1)
distributed optimization
(1)
minimax optimization
(1)
model aggregation
(1)
Papers
Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
NIPS 2024
Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification
NIPS 2024
Proactive DP: A Multiple Target Optimization Framework for DP-SGD
ICML 2024
On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods
AAAI 2024
One Step Closer to Unbiased Aleatoric Uncertainty Estimation
AAAI 2024
Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data
NIPS 2024
On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error
JMLR 2023
Label-free Concept Bottleneck Models
ICLR 2023
ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction
ICML 2023
A Unified Convergence Analysis for Shuffling-Type Gradient Methods
JMLR 2021
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization
JMLR 2020
New Convergence Aspects of Stochastic Gradient Algorithms
JMLR 2019
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
ICML 2017