On Deterministic Sketching and Streaming for Sparse Recovery and Norm Estimation. - Jelani Nelson; Huy L. Nguyên 001; David P. Woodruff (APPROX-RANDOM, 2012)

Improved range searching lower bounds. - Kasper Green Larsen; Huy Le Nguyen 001 (SCG, 2012)

OSNAP: Faster Numerical Linear Algebra Algorithms via Sparser Subspace Embeddings. - Jelani Nelson; Huy L. Nguyen 001 (FOCS, 2013)

On the convergence of the Hegselmann-Krause system. - Arnab Bhattacharyya 001; Mark Braverman; Bernard Chazelle; Huy L. Nguyen 001 (ITCS, 2013)

Sparsity lower bounds for dimensionality reducing maps. - Jelani Nelson; Huy L. Nguyen 001 (STOC, 2013)

Online Bipartite Matching with Decomposable Weights. - Moses Charikar; Monika Henzinger; Huy L. Nguyen 001 (ESA, 2014)

From Graph to Hypergraph Multiway Partition: Is the Single Threshold the Only Route? - Alina Ene; Huy L. Nguyên 001 (ESA, 2014)

Lower Bounds for Oblivious Subspace Embeddings. - Jelani Nelson; Huy L. Nguyên 001 (ICALP (1), 2014)

Subspace Embeddings for the Polynomial Kernel. - Haim Avron; Huy L. Nguyen 001; David P. Woodruff (NIPS, 2014)

Beyond Locality-Sensitive Hashing. - Alexandr Andoni; Piotr Indyk; Huy L. Nguyen 001; Ilya P. Razenshteyn (SODA, 2014)

On Sketching Matrix Norms and the Top Singular Vector. - Yi Li 002; Huy L. Nguyen 001; David P. Woodruff (SODA, 2014)

Turnstile streaming algorithms might as well be linear sketches. - Yi Li 002; Huy L. Nguyen 001; David P. Woodruff (STOC, 2014)

Algorithms for High Dimensional Data - Huy Le Nguyen 001 (2014)

The Power of Randomization: Distributed Submodular Maximization on Massive Datasets. - Rafael da Ponte Barbosa; Alina Ene; Huy L. Nguyen 001; Justin Ward (ICML, 2015)

Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions. - Alina Ene; Huy L. Nguyen 001 (ICML, 2015)

Time Lower Bounds for Nonadaptive Turnstile Streaming Algorithms. - Kasper Green Larsen; Jelani Nelson; Huy L. Nguyên 001 (STOC, 2015)

A New Framework for Distributed Submodular Maximization. - Rafael da Ponte Barbosa; Alina Ene; Huy L. Nguyen 001; Justin Ward (FOCS, 2016)

Constrained Submodular Maximization: Beyond 1/e. - Alina Ene; Huy L. Nguyen 001 (FOCS, 2016)

Heavy Hitters via Cluster-Preserving Clustering. - Kasper Green Larsen; Jelani Nelson; Huy L. Nguyen 001; Mikkel Thorup (FOCS, 2016)

Communication lower bounds for statistical estimation problems via a distributed data processing inequality. - Mark Braverman; Ankit Garg 001; Tengyu Ma 001; Huy L. Nguyen 001; David P. Woodruff (STOC, 2016)

A Reduction for Optimizing Lattice Submodular Functions with Diminishing Returns. - Alina Ene; Huy L. Nguyen 001 (CoRR, 2016)

Width of Points in the Streaming Model. - Alexandr Andoni; Huy L. Nguyên 001 (ACM Trans. Algorithms, 2016)

Decomposable Submodular Function Minimization: Discrete and Continuous. - Alina Ene; Huy L. Nguyen 001; László A. Végh (NIPS, 2017)

Approximate near neighbors for general symmetric norms. - Alexandr Andoni; Huy L. Nguyen 001; Aleksandar Nikolov; Ilya P. Razenshteyn; Erik Waingarten (STOC, 2017)

Improved Algorithms for Collaborative PAC Learning. - Huy L. Nguyen 001; Lydia Zakynthinou (NeurIPS, 2018)

Submodular Maximization with Packing Constraints in Parallel. - Alina Ene; Huy L. Nguyen 001; Adrian Vladu (CoRR, 2018)

A Parallel Double Greedy Algorithm for Submodular Maximization. - Alina Ene; Huy L. Nguyen 001; Adrian Vladu (CoRR, 2018)

A Nearly-Linear Time Algorithm for Submodular Maximization with a Knapsack Constraint. - Alina Ene; Huy L. Nguyen 001 (ICALP, 2019)

Towards Nearly-Linear Time Algorithms for Submodular Maximization with a Matroid Constraint. - Alina Ene; Huy L. Nguyen 001 (ICALP, 2019)

Submodular Maximization with Nearly-optimal Approximation and Adaptivity in Nearly-linear Time. - Alina Ene; Huy L. Nguyen 001 (SODA, 2019)

Fast greedy for linear matroids. - Huy L. Nguyen 001 (SODA, 2019)

Submodular maximization with matroid and packing constraints in parallel. - Alina Ene; Huy L. Nguyen 001; Adrian Vladu (STOC, 2019)

Efficient Private Algorithms for Learning Halfspaces. - Huy L. Nguyen 001; Jonathan R. Ullman; Lydia Zakynthinou (CoRR, 2019)

A note on Cunningham's algorithm for matroid intersection. - Huy L. Nguyen 001 (CoRR, 2019)

An Optimal Streaming Algorithm for Non-monotone Submodular Maximization. - Alina Ene; Huy L. Nguyen 001; Andrew Suh (CoRR, 2019)

On Approximating Matrix Norms in Data Streams. - Yi Li 002; Huy L. Nguyen 001; David P. Woodruff (SIAM J. Comput., 2019)

Optimal Streaming Algorithms for Submodular Maximization with Cardinality Constraints. - Naor Alaluf; Alina Ene; Moran Feldman; Huy L. Nguyen 001; Andrew Suh (ICALP, 2020)

Parallel Algorithm for Non-Monotone DR-Submodular Maximization. - Alina Ene; Huy L. Nguyen 001 (ICML, 2020)

Fair k-Centers via Maximum Matching. - Matthew Jones; Huy L. Nguyen 001; Thy Dinh Nguyen (ICML, 2020)

Differentially Private Decomposable Submodular Maximization. - Anamay Chaturvedi; Huy L. Nguyen 001; Lydia Zakynthinou (CoRR, 2020)

Adaptive Gradient Methods for Constrained Convex Optimization. - Alina Ene; Huy L. Nguyen 001; Adrian Vladu (CoRR, 2020)

Differentially private k-means clustering via exponential mechanism and max cover. - Anamay Chaturvedi; Huy L. Nguyen 001; Eric Z. Xu (CoRR, 2020)

Fair and Useful Cohort Selection. - Niklas Smedemark-Margulies; Paul Langton; Huy L. Nguyen 001 (CoRR, 2020)

A note on differentially private clustering with large additive error. - Huy L. Nguyen 001 (CoRR, 2020)

Adaptive and Universal Single-gradient Algorithms for Variational Inequalities. - Alina Ene; Huy L. Nguyen 001 (CoRR, 2020)

Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities. - Alina Ene; Huy L. Nguyen 001; Adrian Vladu (AAAI, 2021)

Projection-Free Bandit Optimization with Privacy Guarantees. - Alina Ene; Huy L. Nguyen 001; Adrian Vladu (AAAI, 2021)

Differentially Private Clustering via Maximum Coverage. - Matthew Jones; Huy L. Nguyen 001; Thy Dinh Nguyen (AAAI, 2021)

Differentially Private k-Means via Exponential Mechanism and Max Cover. - Huy L. Nguyen 001; Anamay Chaturvedi; Eric Z. Xu (AAAI, 2021)

Locally Private k-Means Clustering with Constant Multiplicative Approximation and Near-Optimal Additive Error. - Anamay Chaturvedi; Matthew Jones; Huy L. Nguyen 001 (CoRR, 2021)

Adaptive and Universal Algorithms for Variational Inequalities with Optimal Convergence. - Alina Ene; Huy Le Nguyen 001 (AAAI, 2022)

Streaming Algorithm for Monotone k-Submodular Maximization with Cardinality Constraints. - Alina Ene; Huy L. Nguyen 001 (ICML, 2022)

Private frequency estimation via projective geometry. - Vitaly Feldman; Jelani Nelson; Huy L. Nguyen 001; Kunal Talwar (ICML, 2022)

Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction. - Zijian Liu 003; Ta Duy Nguyen; Alina Ene; Huy L. Nguyen 001 (ICML, 2022)

On the Convergence of AdaGrad on $ R^{d}$: Beyond Convexity, Non-Asymptotic Rate and Acceleration. - Zijian Liu 003; Ta Duy Nguyen; Alina Ene; Huy L. Nguyen 001 (CoRR, 2022)

META-STORM: Generalized Fully-Adaptive Variance Reduced SGD for Unbounded Functions. - Zijian Liu 003; Ta Duy Nguyen; Thien Hang Nguyen; Alina Ene; Huy L. Nguyen 001 (CoRR, 2022)

High Probability Convergence for Accelerated Stochastic Mirror Descent. - Alina Ene; Huy L. Nguyen 001 (CoRR, 2022)

An Optimal Streaming Algorithm for Submodular Maximization with a Cardinality Constraint. - Naor Alaluf; Alina Ene; Moran Feldman; Huy L. Nguyen 001; Andrew Suh (Math. Oper. Res., 2022)

An Efficient Algorithm for Fair Multi-Agent Multi-Armed Bandit with Low Regret. - Matthew Jones; Huy L. Nguyen 001; Thy Dinh Nguyen (AAAI, 2023)

On the Convergence of AdaGrad(Norm) on ℝd: Beyond Convexity, Non-Asymptotic Rate and Acceleration. - Zijian Liu 003; Ta Duy Nguyen; Alina Ene; Huy L. Nguyen 001 (ICLR, 2023)

Improved Learning-augmented Algorithms for k-means and k-medians Clustering. - Thy Dinh Nguyen; Anamay Chaturvedi; Huy L. Nguyen 001 (ICLR, 2023)

Streaming Submodular Maximization with Differential Privacy. - Anamay Chaturvedi; Huy L. Nguyen 001; Thy Dinh Nguyen (ICML, 2023)

High Probability Convergence of Stochastic Gradient Methods. - Zijian Liu 003; Ta Duy Nguyen; Thien Hang Nguyen; Alina Ene; Huy L. Nguyen 001 (ICML, 2023)

Fast Optimal Locally Private Mean Estimation via Random Projections. - Hilal Asi; Vitaly Feldman; Jelani Nelson; Huy L. Nguyen 001; Kunal Talwar (NeurIPS, 2023)

On the Generalization Error of Stochastic Mirror Descent for Quadratically-Bounded Losses: an Improved Analysis. - Ta Duy Nguyen; Alina Ene; Huy L. Nguyen 001 (NeurIPS, 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 001 (NeurIPS, 2023)

Fair and Useful Cohort Selection. - Konstantina Bairaktari; Paul Langton; Huy L. Nguyen 001; Niklas Smedemark-Margulies; Jonathan R. Ullman (Trans. Mach. Learn. Res., 2023)

Identification of Negative Transfers in Multitask Learning Using Surrogate Models. - Dongyue Li; Huy L. Nguyen 001; Hongyang Ryan Zhang (Trans. Mach. Learn. Res., 2023)

Improved Group Robustness via Classifier Retraining on Independent Splits. - Thien Hang Nguyen; Hongyang R. Zhang; Huy L. Nguyen 001 (Trans. Mach. Learn. Res., 2023)

Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. - Hilal Asi; Vitaly Feldman; Jelani Nelson; Huy L. Nguyen 001; Kunal Talwar; Samson Zhou (ICML, 2024)

Online and Streaming Algorithms for Constrained k-Submodular Maximization. - Fabian Christian Spaeh; Alina Ene; Huy L. Nguyen 001 (AAAI, 2025)

Solving Linear Programs with Differential Privacy. - Alina Ene; Huy Le Nguyen 001; Ta Duy Nguyen; Adrian Vladu (APPROX/RANDOM, 2025)

Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures. - Alina Ene; Alessandro Epasto; Vahab Mirrokni; Hoai-An Nguyen; Huy L. Nguyen 001; David P. Woodruff; Peilin Zhong (ICML, 2025)

Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees. - Thien Hang Nguyen; Huy L. Nguyen 001 (ICML, 2025)

Sample-efficient Multiclass Calibration under ℓp Error. - Konstantina Bairaktari; Huy L. Nguyen 001 (CoRR, 2025)

One-Sided Matrix Completion from Ultra-Sparse Samples. - Hongyang R. Zhang; Zhenshuo Zhang; Huy L. Nguyen 001; Guanghui Lan (Trans. Mach. Learn. Res., 2026)

Adaptive Power Iteration Method for Differentially Private PCA. - Ta Duy Nguyen; Alina Ene; Huy Le Nguyen 001 (CoRR, 2026)

Solving Positive Linear Programs with Differential Privacy. - Alina Ene; Huy L. Nguyen 001; Ta Duy Nguyen; Adrian Vladu (CoRR, 2026)

Testable and Actionable Calibration for Full Swap Regret. - Konstantina Bairaktari; Lunjia Hu; Huy L. Nguyen 001; Jonathan R. Ullman (CoRR, 2026)