Huy L. Nguyen

According to our database, Huy L. Nguyen authored at least 79 papers between 2012 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Testable and Actionable Calibration for Full Swap Regret.

Konstantina Bairaktari, Lunjia Hu, Huy L. Nguyen, Jonathan R. Ullman

CoRR, May, 2026

Solving Positive Linear Programs with Differential Privacy.

Alina Ene, Huy L. Nguyen, Ta Duy Nguyen, Adrian Vladu

CoRR, April, 2026

Adaptive Power Iteration Method for Differentially Private PCA.

Ta Duy Nguyen, Alina Ene, Huy Le Nguyen

CoRR, February, 2026

One-Sided Matrix Completion from Ultra-Sparse Samples.

Hongyang R. Zhang, Zhenshuo Zhang, Huy L. Nguyen, Guanghui Lan

Trans. Mach. Learn. Res., 2026

2025

Sample-efficient Multiclass Calibration under ℓ_p Error.

Konstantina Bairaktari, Huy L. Nguyen

CoRR, September, 2025

Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees.

Thien Hang Nguyen, Huy L. Nguyen

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures.

Alina Ene, Alessandro Epasto, Vahab Mirrokni, Hoai-An Nguyen, Huy L. Nguyen, David P. Woodruff, Peilin Zhong

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Solving Linear Programs with Differential Privacy.

Alina Ene, Huy Le Nguyen, Ta Duy Nguyen, Adrian Vladu

Proceedings of the Approximation, 2025

Online and Streaming Algorithms for Constrained k-Submodular Maximization.

Fabian Christian Spaeh, Alina Ene, Huy L. Nguyen

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages.

Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Improved Group Robustness via Classifier Retraining on Independent Splits.

Thien Hang Nguyen, Hongyang R. Zhang, Huy L. Nguyen

Trans. Mach. Learn. Res., 2023

Identification of Negative Transfers in Multitask Learning Using Surrogate Models.

Dongyue Li, Huy L. Nguyen, Hongyang Ryan Zhang

Trans. Mach. Learn. Res., 2023

Fair and Useful Cohort Selection.

Konstantina Bairaktari, Paul Langton, Huy L. Nguyen, Niklas Smedemark-Margulies, Jonathan R. Ullman

Trans. Mach. Learn. Res., 2023

Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise.

Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy L. Nguyen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Generalization Error of Stochastic Mirror Descent for Quadratically-Bounded Losses: an Improved Analysis.

Ta Duy Nguyen, Alina Ene, Huy L. Nguyen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fast Optimal Locally Private Mean Estimation via Random Projections.

Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

High Probability Convergence of Stochastic Gradient Methods.

Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy L. Nguyen

Proceedings of the International Conference on Machine Learning, 2023

Streaming Submodular Maximization with Differential Privacy.

Anamay Chaturvedi, Huy L. Nguyen, Thy Dinh Nguyen

Proceedings of the International Conference on Machine Learning, 2023

Improved Learning-augmented Algorithms for k-means and k-medians Clustering.

Thy Dinh Nguyen, Anamay Chaturvedi, Huy L. Nguyen

Proceedings of the Eleventh International Conference on Learning Representations, 2023

On the Convergence of AdaGrad(Norm) on ℝ^d: Beyond Convexity, Non-Asymptotic Rate and Acceleration.

Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy L. Nguyen

Proceedings of the Eleventh International Conference on Learning Representations, 2023

An Efficient Algorithm for Fair Multi-Agent Multi-Armed Bandit with Low Regret.

Matthew Jones, Huy L. Nguyen, Thy Dinh Nguyen

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

An Optimal Streaming Algorithm for Submodular Maximization with a Cardinality Constraint.

Naor Alaluf, Alina Ene, Moran Feldman, Huy L. Nguyen, Andrew Suh

Math. Oper. Res., November, 2022

High Probability Convergence for Accelerated Stochastic Mirror Descent.

Alina Ene, Huy L. Nguyen

CoRR, 2022

META-STORM: Generalized Fully-Adaptive Variance Reduced SGD for Unbounded Functions.

Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy L. Nguyen

CoRR, 2022

On the Convergence of AdaGrad on $\R^{d}$: Beyond Convexity, Non-Asymptotic Rate and Acceleration.

Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy L. Nguyen

CoRR, 2022

Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction.

Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy L. Nguyen

Proceedings of the International Conference on Machine Learning, 2022

Private frequency estimation via projective geometry.

Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar

Proceedings of the International Conference on Machine Learning, 2022

Streaming Algorithm for Monotone k-Submodular Maximization with Cardinality Constraints.

Alina Ene, Huy L. Nguyen

Proceedings of the International Conference on Machine Learning, 2022

Adaptive and Universal Algorithms for Variational Inequalities with Optimal Convergence.

Alina Ene, Huy Le Nguyen

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Locally Private k-Means Clustering with Constant Multiplicative Approximation and Near-Optimal Additive Error.

Anamay Chaturvedi, Matthew Jones, Huy L. Nguyen

CoRR, 2021

Differentially Private k-Means via Exponential Mechanism and Max Cover.

Huy L. Nguyen, Anamay Chaturvedi, Eric Z. Xu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Differentially Private Clustering via Maximum Coverage.

Matthew Jones, Huy L. Nguyen, Thy Dinh Nguyen

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Projection-Free Bandit Optimization with Privacy Guarantees.

Alina Ene, Huy L. Nguyen, Adrian Vladu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities.

Alina Ene, Huy L. Nguyen, Adrian Vladu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Adaptive and Universal Single-gradient Algorithms for Variational Inequalities.

Alina Ene, Huy L. Nguyen

CoRR, 2020

A note on differentially private clustering with large additive error.

Huy L. Nguyen

CoRR, 2020

Fair and Useful Cohort Selection.

Niklas Smedemark-Margulies, Paul Langton, Huy L. Nguyen

CoRR, 2020

Differentially private k-means clustering via exponential mechanism and max cover.

Anamay Chaturvedi, Huy L. Nguyen, Eric Z. Xu

CoRR, 2020

Adaptive Gradient Methods for Constrained Convex Optimization.

Alina Ene, Huy L. Nguyen, Adrian Vladu

CoRR, 2020

Differentially Private Decomposable Submodular Maximization.

Anamay Chaturvedi, Huy L. Nguyen, Lydia Zakynthinou

CoRR, 2020

Fair k-Centers via Maximum Matching.

Matthew Jones, Huy L. Nguyen, Thy Dinh Nguyen

Proceedings of the 37th International Conference on Machine Learning, 2020

Parallel Algorithm for Non-Monotone DR-Submodular Maximization.

Alina Ene, Huy L. Nguyen

Proceedings of the 37th International Conference on Machine Learning, 2020

Optimal Streaming Algorithms for Submodular Maximization with Cardinality Constraints.

Naor Alaluf, Alina Ene, Moran Feldman, Huy L. Nguyen, Andrew Suh

Proceedings of the 47th International Colloquium on Automata, Languages, and Programming, 2020

2019

On Approximating Matrix Norms in Data Streams.

Yi Li, Huy L. Nguyen, David P. Woodruff

SIAM J. Comput., 2019

An Optimal Streaming Algorithm for Non-monotone Submodular Maximization.

Alina Ene, Huy L. Nguyen, Andrew Suh

CoRR, 2019

A note on Cunningham's algorithm for matroid intersection.

Huy L. Nguyen

CoRR, 2019

Efficient Private Algorithms for Learning Halfspaces.

Huy L. Nguyen, Jonathan R. Ullman, Lydia Zakynthinou

CoRR, 2019

Submodular maximization with matroid and packing constraints in parallel.

Alina Ene, Huy L. Nguyen, Adrian Vladu

Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Fast greedy for linear matroids.

Huy L. Nguyen

Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Submodular Maximization with Nearly-optimal Approximation and Adaptivity in Nearly-linear Time.

Alina Ene, Huy L. Nguyen

Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Towards Nearly-Linear Time Algorithms for Submodular Maximization with a Matroid Constraint.

Alina Ene, Huy L. Nguyen

Proceedings of the 46th International Colloquium on Automata, Languages, and Programming, 2019

A Nearly-Linear Time Algorithm for Submodular Maximization with a Knapsack Constraint.

Alina Ene, Huy L. Nguyen

Proceedings of the 46th International Colloquium on Automata, Languages, and Programming, 2019

2018

A Parallel Double Greedy Algorithm for Submodular Maximization.

Alina Ene, Huy L. Nguyen, Adrian Vladu

CoRR, 2018

Submodular Maximization with Packing Constraints in Parallel.

Alina Ene, Huy L. Nguyen, Adrian Vladu

CoRR, 2018

Improved Algorithms for Collaborative PAC Learning.

Huy L. Nguyen, Lydia Zakynthinou

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Approximate near neighbors for general symmetric norms.

Alexandr Andoni, Huy L. Nguyen, Aleksandar Nikolov, Ilya P. Razenshteyn, Erik Waingarten

Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

Decomposable Submodular Function Minimization: Discrete and Continuous.

Alina Ene, Huy L. Nguyen, László A. Végh

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Width of Points in the Streaming Model.

Alexandr Andoni, Huy L. Nguyên

ACM Trans. Algorithms, 2016

A Reduction for Optimizing Lattice Submodular Functions with Diminishing Returns.

Alina Ene, Huy L. Nguyen

CoRR, 2016

Communication lower bounds for statistical estimation problems via a distributed data processing inequality.

Mark Braverman, Ankit Garg, Tengyu Ma, Huy L. Nguyen, David P. Woodruff

Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

Heavy Hitters via Cluster-Preserving Clustering.

Kasper Green Larsen, Jelani Nelson, Huy L. Nguyen, Mikkel Thorup

Proceedings of the IEEE 57th Annual Symposium on Foundations of Computer Science, 2016

Constrained Submodular Maximization: Beyond 1/e.

Alina Ene, Huy L. Nguyen

Proceedings of the IEEE 57th Annual Symposium on Foundations of Computer Science, 2016

A New Framework for Distributed Submodular Maximization.

Rafael da Ponte Barbosa, Alina Ene, Huy L. Nguyen, Justin Ward

Proceedings of the IEEE 57th Annual Symposium on Foundations of Computer Science, 2016

2015

Time Lower Bounds for Nonadaptive Turnstile Streaming Algorithms.

Kasper Green Larsen, Jelani Nelson, Huy L. Nguyên

Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, 2015

Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions.

Alina Ene, Huy L. Nguyen

Proceedings of the 32nd International Conference on Machine Learning, 2015

The Power of Randomization: Distributed Submodular Maximization on Massive Datasets.

Rafael da Ponte Barbosa, Alina Ene, Huy L. Nguyen, Justin Ward

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Algorithms for High Dimensional Data

Huy Le Nguyen

PhD thesis, 2014

Turnstile streaming algorithms might as well be linear sketches.

Yi Li, Huy L. Nguyen, David P. Woodruff

Proceedings of the Symposium on Theory of Computing, 2014

On Sketching Matrix Norms and the Top Singular Vector.

Yi Li, Huy L. Nguyen, David P. Woodruff

Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Beyond Locality-Sensitive Hashing.

Alexandr Andoni, Piotr Indyk, Huy L. Nguyen, Ilya P. Razenshteyn

Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Subspace Embeddings for the Polynomial Kernel.

Haim Avron, Huy L. Nguyen, David P. Woodruff

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Lower Bounds for Oblivious Subspace Embeddings.

Jelani Nelson, Huy L. Nguyên

Proceedings of the Automata, Languages, and Programming - 41st International Colloquium, 2014

From Graph to Hypergraph Multiway Partition: Is the Single Threshold the Only Route?

Alina Ene, Huy L. Nguyên

Proceedings of the Algorithms - ESA 2014, 2014

Online Bipartite Matching with Decomposable Weights.

Moses Charikar, Monika Henzinger, Huy L. Nguyen

Proceedings of the Algorithms - ESA 2014, 2014

2013

Sparsity lower bounds for dimensionality reducing maps.

Jelani Nelson, Huy L. Nguyen

Proceedings of the Symposium on Theory of Computing Conference, 2013

On the convergence of the Hegselmann-Krause system.

Arnab Bhattacharyya, Mark Braverman, Bernard Chazelle, Huy L. Nguyen

Proceedings of the Innovations in Theoretical Computer Science, 2013

OSNAP: Faster Numerical Linear Algebra Algorithms via Sparser Subspace Embeddings.

Jelani Nelson, Huy L. Nguyen

Proceedings of the 54th Annual IEEE Symposium on Foundations of Computer Science, 2013

2012

Improved range searching lower bounds.

Kasper Green Larsen, Huy Le Nguyen

Proceedings of the 28th ACM Symposium on Computational Geometry, 2012

On Deterministic Sketching and Streaming for Sparse Recovery and Norm Estimation.

Jelani Nelson, Huy L. Nguyên, David P. Woodruff

Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 2012