Viet Anh Nguyen
33 papers · 2018–2026 · 12 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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Venues
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Research topics
Machine Learning
(30)
Optimization & Theory
(20)
Artificial Intelligence
(16)
Core AI
(13)
Core Methods
(12)
Mathematics & Optimization
(11)
Optimization
(11)
Application Areas
(9)
Learning Types Β· Machine Learning
(8)
Deep Learning
(7)
Bayesian & Probabilistic Β· Artificial Intelligence
(3)
Bayesian & Probabilistic Β· Machine Learning
(3)
Mathematics
(3)
Architectures
(2)
Learning Types Β· Deep Learning
(2)
Keywords
distributionally robust optimization
(10)
convex optimization
(5)
optimal transport
(4)
robust optimization
(3)
kullback-leibler divergence
(3)
activation intervention
(2)
attention head
(2)
activation steering
(2)
dimensionality reduction
(2)
bayesian inference
(2)
generalized linear model
(2)
algorithmic recourse
(2)
determinantal point process
(2)
transfer learning
(2)
wasserstein distance
(2)
model shift
(2)
language model
(2)
semidefinite programming
(1)
learning theory
(1)
binary classification
(1)
Papers
Provably Data-Driven Projection Method for Quadratic Programming
AAAI 2026
Test-time Diverse Reasoning by Riemannian Activation Steering
AAAI 2026
Distributional Surgery for Language Model Activations
EMNLP 2025
Mixture-of-Personas Language Models for Population Simulation
ACL 2025
Probe-Free Low-Rank Activation Intervention
NAACL 2025
Structured Pruning for Diverse Best-of-N Reasoning Optimization
ACL 2025
Task-driven Layerwise Additive Activation Intervention
NAACL 2025
Bellman Optimal Stepsize Straightening of Flow-Matching Models
ICLR 2024
Cold-start Recommendation by Personalized Embedding Region Elicitation
UAI 2024
Explaining Graph Neural Networks via Structure-aware Interaction Index
ICML 2024
Generative Conditional Distributions by Neural (Entropic) Optimal Transport
ICML 2024
Distributionally Robust Recourse Action
ICLR 2023
Dropout Training is Distributionally Robust Optimal
JMLR 2023
Dynamic Flows on Curved Space Generated by Labeled Data
IJCAI 2023
Efficient Failure Pattern Identification of Predictive Algorithms
UAI 2023
Feasible Recourse Plan via Diverse Interpolation
AISTATS 2023
Counterfactual Plans under Distributional Ambiguity
ICLR 2022
Distributionally Robust Fair Principal Components via Geodesic Descents
ICLR 2022
Robust Bayesian recourse
UAI 2022
Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics
AISTATS 2022
Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints
NeurIPS 2022
Adversarial Regression with Doubly Non-negative Weighting Matrices
NeurIPS 2021
Principal Component Hierarchy for Sparse Quadratic Programs
ICML 2021
Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts
ICML 2021
S-NLP at SemEval-2021 Task 5: An Analysis of Dual Networks for Sequence Tagging
SemEval 2021
Testing Group Fairness via Optimal Transport Projections
ICML 2021
Distributionally Robust Local Non-parametric Conditional Estimation
NeurIPS 2020
Distributionally Robust Parametric Maximum Likelihood Estimation
NeurIPS 2020
Robust Bayesian Classification Using An Optimistic Score Ratio
ICML 2020
SunBear at WNUT-2020 Task 2: Improving BERT-Based Noisy Text Classification with Knowledge of the Data domain
EMNLP 2020
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization
NeurIPS 2019
Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation
NeurIPS 2019
Wasserstein Distributionally Robust Kalman Filtering
NeurIPS 2018