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Huy L. Nguyen 0001
Person information
- affiliation: Northeastern University, College of Computer and Information Science, Boston, MA, USA
- affiliation: Toyota Technological Institute at Chicago, Chicago, IL, USA
- affiliation: University of California, Berkeley, CA, USA
- affiliation (PhD 2014): Princeton University, Princeton, NJ, USA
Other persons with the same name
- Huy L. Nguyen (aka: Huy Le Nguyen, Huy L. Nguyên) — disambiguation page
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2020 – today
- 2026
[j8]Hongyang R. Zhang, Zhenshuo Zhang, Huy L. Nguyen, Guanghui Lan:
One-Sided Matrix Completion from Ultra-Sparse Samples. Trans. Mach. Learn. Res. 2026 (2026)
[i48]Hongyang R. Zhang, Zhenshuo Zhang, Huy L. Nguyen, Guanghui Lan:
One-Sided Matrix Completion from Ultra-Sparse Samples. CoRR abs/2601.12213 (2026)- 2025
[c51]Fabian Christian Spaeh, Alina Ene
, Huy L. Nguyen
:
Online and Streaming Algorithms for Constrained k-Submodular Maximization. AAAI 2025: 20567-20574
[c50]Alina Ene, Huy Le Nguyen, Ta Duy Nguyen, Adrian Vladu:
Solving Linear Programs with Differential Privacy. APPROX/RANDOM 2025: 65:1-65:17
[c49]Alina Ene, Alessandro Epasto, Vahab Mirrokni, Hoai-An Nguyen, Huy L. Nguyen, David P. Woodruff, Peilin Zhong:
Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures. ICML 2025
[c48]Thien Hang Nguyen, Huy L. Nguyen:
Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees. ICML 2025
[i47]Alina Ene, Alessandro Epasto, Vahab Mirrokni, Hoai-An Nguyen, Huy L. Nguyen, David P. Woodruff, Peilin Zhong:
Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures. CoRR abs/2504.18394 (2025)
[i46]Alina Ene, Huy L. Nguyen, Ta Duy Nguyen, Adrian Vladu:
Solving Linear Programs with Differential Privacy. CoRR abs/2507.10946 (2025)
[i45]Konstantina Bairaktari, Huy L. Nguyen:
Sample-efficient Multiclass Calibration under ℓp Error. CoRR abs/2509.23000 (2025)- 2024
[c47]Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou:
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. ICML 2024: 1945-1970
[i44]Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou:
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. CoRR abs/2404.10201 (2024)- 2023
[j7]Konstantina Bairaktari, Paul Langton, Huy L. Nguyen, Niklas Smedemark-Margulies, Jonathan R. Ullman:
Fair and Useful Cohort Selection. Trans. Mach. Learn. Res. 2023 (2023)
[j6]Dongyue Li, Huy L. Nguyen
, Hongyang Ryan Zhang:
Identification of Negative Transfers in Multitask Learning Using Surrogate Models. Trans. Mach. Learn. Res. 2023 (2023)
[j5]Thien Hang Nguyen, Hongyang R. Zhang, Huy L. Nguyen:
Improved Group Robustness via Classifier Retraining on Independent Splits. Trans. Mach. Learn. Res. 2023 (2023)
[c46]Matthew Jones, Huy L. Nguyen
, Thy Dinh Nguyen:
An Efficient Algorithm for Fair Multi-Agent Multi-Armed Bandit with Low Regret. AAAI 2023: 8159-8167
[c45]Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy L. Nguyen:
On the Convergence of AdaGrad(Norm) on ℝd: Beyond Convexity, Non-Asymptotic Rate and Acceleration. ICLR 2023
[c44]Thy Dinh Nguyen, Anamay Chaturvedi, Huy L. Nguyen:
Improved Learning-augmented Algorithms for k-means and k-medians Clustering. ICLR 2023
[c43]Anamay Chaturvedi, Huy L. Nguyen, Thy Dinh Nguyen:
Streaming Submodular Maximization with Differential Privacy. ICML 2023: 4116-4143
[c42]Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene
, Huy L. Nguyen:
High Probability Convergence of Stochastic Gradient Methods. ICML 2023: 21884-21914
[c41]Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar:
Fast Optimal Locally Private Mean Estimation via Random Projections. NeurIPS 2023
[c40]Ta Duy Nguyen, Alina Ene, Huy L. Nguyen:
On the Generalization Error of Stochastic Mirror Descent for Quadratically-Bounded Losses: an Improved Analysis. NeurIPS 2023
[c39]Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy L. Nguyen:
Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise. NeurIPS 2023
[i43]Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy L. Nguyen:
High Probability Convergence of Stochastic Gradient Methods. CoRR abs/2302.14843 (2023)
[i42]Dongyue Li, Huy L. Nguyen, Hongyang R. Zhang:
Identification of Negative Transfers in Multitask Learning Using Surrogate Models. CoRR abs/2303.14582 (2023)
[i41]Fabian Spaeh, Alina Ene, Huy L. Nguyen:
Online and Streaming Algorithms for Constrained k-Submodular Maximization. CoRR abs/2305.16013 (2023)
[i40]Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar:
Fast Optimal Locally Private Mean Estimation via Random Projections. CoRR abs/2306.04444 (2023)- 2022
[j4]Naor Alaluf, Alina Ene
, Moran Feldman
, Huy L. Nguyen
, Andrew Suh:
An Optimal Streaming Algorithm for Submodular Maximization with a Cardinality Constraint. Math. Oper. Res. 47(4): 2667-2690 (2022)
[c38]Alina Ene
, Huy Le Nguyen:
Adaptive and Universal Algorithms for Variational Inequalities with Optimal Convergence. AAAI 2022: 6559-6567
[c37]Alina Ene
, Huy L. Nguyen:
Streaming Algorithm for Monotone k-Submodular Maximization with Cardinality Constraints. ICML 2022: 5944-5967
[c36]Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar:
Private frequency estimation via projective geometry. ICML 2022: 6418-6433
[c35]Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy L. Nguyen:
Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction. ICML 2022: 13947-13994
[i39]Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy L. Nguyen:
Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction. CoRR abs/2201.12302 (2022)
[i38]Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar:
Private Frequency Estimation via Projective Geometry. CoRR abs/2203.00194 (2022)
[i37]Zijian Liu, Ta Duy Nguyen, Alina Ene
, Huy L. Nguyen:
On the Convergence of AdaGrad on $\R^{d}$: Beyond Convexity, Non-Asymptotic Rate and Acceleration. CoRR abs/2209.14827 (2022)
[i36]Zijian Liu, Ta Duy Nguyen, Thien Hang Nguyen, Alina Ene, Huy L. Nguyen:
META-STORM: Generalized Fully-Adaptive Variance Reduced SGD for Unbounded Functions. CoRR abs/2209.14853 (2022)
[i35]Alina Ene
, Huy L. Nguyen:
High Probability Convergence for Accelerated Stochastic Mirror Descent. CoRR abs/2210.00679 (2022)- 2021
[c34]Alina Ene, Huy L. Nguyen, Adrian Vladu:
Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities. AAAI 2021: 7314-7321
[c33]Alina Ene, Huy L. Nguyen, Adrian Vladu:
Projection-Free Bandit Optimization with Privacy Guarantees. AAAI 2021: 7322-7330
[c32]Huy L. Nguyen, Anamay Chaturvedi
, Eric Z. Xu:
Differentially Private k-Means via Exponential Mechanism and Max Cover. AAAI 2021: 9101-9108
[c31]Matthew Jones, Huy L. Nguyen, Thy Dinh Nguyen:
Differentially Private Clustering via Maximum Coverage. AAAI 2021: 11555-11563
[i34]Anamay Chaturvedi, Matthew Jones, Huy L. Nguyen:
Locally Private k-Means Clustering with Constant Multiplicative Approximation and Near-Optimal Additive Error. CoRR abs/2105.15007 (2021)- 2020
[c30]Naor Alaluf, Alina Ene, Moran Feldman, Huy L. Nguyen, Andrew Suh:
Optimal Streaming Algorithms for Submodular Maximization with Cardinality Constraints. ICALP 2020: 6:1-6:19
[c29]Alina Ene, Huy L. Nguyen:
Parallel Algorithm for Non-Monotone DR-Submodular Maximization. ICML 2020: 2902-2911
[c28]Matthew Jones, Huy L. Nguyen, Thy Dinh Nguyen:
Fair k-Centers via Maximum Matching. ICML 2020: 4940-4949
[i33]Anamay Chaturvedi, Huy L. Nguyen, Lydia Zakynthinou
:
Differentially Private Decomposable Submodular Maximization. CoRR abs/2005.14717 (2020)
[i32]Alina Ene, Huy L. Nguyen, Adrian Vladu:
Adaptive Gradient Methods for Constrained Convex Optimization. CoRR abs/2007.08840 (2020)
[i31]Anamay Chaturvedi, Huy L. Nguyen, Eric Z. Xu:
Differentially private k-means clustering via exponential mechanism and max cover. CoRR abs/2009.01220 (2020)
[i30]Niklas Smedemark-Margulies, Paul Langton, Huy L. Nguyen:
Fair and Useful Cohort Selection. CoRR abs/2009.02207 (2020)
[i29]Huy L. Nguyen:
A note on differentially private clustering with large additive error. CoRR abs/2009.13317 (2020)
[i28]Alina Ene, Huy L. Nguyen:
Adaptive and Universal Single-gradient Algorithms for Variational Inequalities. CoRR abs/2010.07799 (2020)
[i27]Alina Ene, Huy L. Nguyen, Adrian Vladu:
Projection-Free Bandit Optimization with Privacy Guarantees. CoRR abs/2012.12138 (2020)
2010 – 2019
- 2019
[j3]Kasper Green Larsen
, Jelani Nelson, Huy L. Nguyen, Mikkel Thorup
:
Heavy hitters via cluster-preserving clustering. Commun. ACM 62(8): 95-100 (2019)
[j2]Yi Li
, Huy L. Nguyen, David P. Woodruff:
On Approximating Matrix Norms in Data Streams. SIAM J. Comput. 48(6): 1643-1697 (2019)
[c27]Alina Ene, Huy L. Nguyen:
A Nearly-Linear Time Algorithm for Submodular Maximization with a Knapsack Constraint. ICALP 2019: 53:1-53:12
[c26]Alina Ene, Huy L. Nguyen:
Towards Nearly-Linear Time Algorithms for Submodular Maximization with a Matroid Constraint. ICALP 2019: 54:1-54:14
[c25]Alina Ene, Huy L. Nguyen:
Submodular Maximization with Nearly-optimal Approximation and Adaptivity in Nearly-linear Time. SODA 2019: 274-282
[c24]Huy L. Nguyen:
Fast greedy for linear matroids. SODA 2019: 516-524
[c23]Alina Ene, Huy L. Nguyen, Adrian Vladu:
Submodular maximization with matroid and packing constraints in parallel. STOC 2019: 90-101
[i26]Huy L. Nguyen, Jonathan R. Ullman, Lydia Zakynthinou
:
Efficient Private Algorithms for Learning Halfspaces. CoRR abs/1902.09009 (2019)
[i25]Huy L. Nguyen:
A note on Cunningham's algorithm for matroid intersection. CoRR abs/1904.04129 (2019)
[i24]Alina Ene, Huy L. Nguyen:
Parallel Algorithm for Non-Monotone DR-Submodular Maximization. CoRR abs/1905.13272 (2019)
[i23]Alina Ene, Huy L. Nguyen, Andrew Suh:
An Optimal Streaming Algorithm for Non-monotone Submodular Maximization. CoRR abs/1911.12959 (2019)- 2018
[c22]Huy L. Nguyen, Lydia Zakynthinou:
Improved Algorithms for Collaborative PAC Learning. NeurIPS 2018: 7642-7650
[i22]Alina Ene, Huy L. Nguyen:
Submodular Maximization with Nearly-optimal Approximation and Adaptivity in Nearly-linear Time. CoRR abs/1804.05379 (2018)
[i21]Huy L. Nguyen, Lydia Zakynthinou
:
Improved Algorithms for Collaborative PAC Learning. CoRR abs/1805.08356 (2018)
[i20]Alina Ene, Huy L. Nguyen, Adrian Vladu:
Submodular Maximization with Packing Constraints in Parallel. CoRR abs/1808.09987 (2018)
[i19]Alina Ene, Huy L. Nguyen:
Towards Nearly-linear Time Algorithms for Submodular Maximization with a Matroid Constraint. CoRR abs/1811.07464 (2018)
[i18]Alina Ene, Huy L. Nguyen, Adrian Vladu:
A Parallel Double Greedy Algorithm for Submodular Maximization. CoRR abs/1812.01591 (2018)- 2017
[c21]Alina Ene, Huy L. Nguyen, László A. Végh:
Decomposable Submodular Function Minimization: Discrete and Continuous. NIPS 2017: 2870-2880
[c20]Alexandr Andoni, Huy L. Nguyen, Aleksandar Nikolov
, Ilya P. Razenshteyn, Erik Waingarten
:
Approximate near neighbors for general symmetric norms. STOC 2017: 902-913
[i17]Alina Ene, Huy L. Nguyen, László A. Végh:
Decomposable Submodular Function Minimization: Discrete and Continuous. CoRR abs/1703.01830 (2017)
[i16]Alina Ene, Huy L. Nguyen:
A Nearly-linear Time Algorithm for Submodular Maximization with a Knapsack Constraint. CoRR abs/1709.09767 (2017)- 2016
[j1]Alexandr Andoni, Huy L. Nguyên:
Width of Points in the Streaming Model. ACM Trans. Algorithms 12(1): 5:1-5:10 (2016)
[c19]Kasper Green Larsen
, Jelani Nelson, Huy L. Nguyen, Mikkel Thorup
:
Heavy Hitters via Cluster-Preserving Clustering. FOCS 2016: 61-70
[c18]Alina Ene, Huy L. Nguyen:
Constrained Submodular Maximization: Beyond 1/e. FOCS 2016: 248-257
[c17]Rafael da Ponte Barbosa, Alina Ene, Huy L. Nguyen, Justin Ward:
A New Framework for Distributed Submodular Maximization. FOCS 2016: 645-654
[c16]Mark Braverman, Ankit Garg, Tengyu Ma, Huy L. Nguyen, David P. Woodruff:
Communication lower bounds for statistical estimation problems via a distributed data processing inequality. STOC 2016: 1011-1020
[i15]Kasper Green Larsen
, Jelani Nelson, Huy L. Nguyen, Mikkel Thorup:
Heavy hitters via cluster-preserving clustering. CoRR abs/1604.01357 (2016)
[i14]Alina Ene, Huy L. Nguyen:
A Reduction for Optimizing Lattice Submodular Functions with Diminishing Returns. CoRR abs/1606.08362 (2016)
[i13]Alina Ene, Huy L. Nguyen:
Constrained Submodular Maximization: Beyond 1/e. CoRR abs/1608.03611 (2016)- 2015
[c15]Alina Ene, Huy L. Nguyen:
Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions. ICML 2015: 787-795
[c14]Rafael da Ponte Barbosa, Alina Ene, Huy L. Nguyen, Justin Ward:
The Power of Randomization: Distributed Submodular Maximization on Massive Datasets. ICML 2015: 1236-1244
[c13]Kasper Green Larsen
, Jelani Nelson, Huy L. Nguyên:
Time Lower Bounds for Nonadaptive Turnstile Streaming Algorithms. STOC 2015: 803-812
[i12]Rafael da Ponte Barbosa, Alina Ene, Huy L. Nguyen, Justin Ward:
The Power of Randomization: Distributed Submodular Maximization on Massive Datasets. CoRR abs/1502.02606 (2015)
[i11]Alina Ene, Huy L. Nguyen:
Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions. CoRR abs/1502.02643 (2015)
[i10]Mark Braverman, Ankit Garg, Tengyu Ma, Huy L. Nguyen, David P. Woodruff:
Communication Lower Bounds for Statistical Estimation Problems via a Distributed Data Processing Inequality. CoRR abs/1506.07216 (2015)
[i9]Rafael da Ponte Barbosa, Alina Ene, Huy L. Nguyen, Justin Ward:
A New Framework for Distributed Submodular Maximization. CoRR abs/1507.03719 (2015)- 2014
[b1]Huy Le Nguyen:
Algorithms for High Dimensional Data. Princeton University, USA, 2014
[c12]Moses Charikar
, Monika Henzinger, Huy L. Nguyen:
Online Bipartite Matching with Decomposable Weights. ESA 2014: 260-271
[c11]Alina Ene, Huy L. Nguyên:
From Graph to Hypergraph Multiway Partition: Is the Single Threshold the Only Route? ESA 2014: 382-393
[c10]Jelani Nelson, Huy L. Nguyên:
Lower Bounds for Oblivious Subspace Embeddings. ICALP (1) 2014: 883-894
[c9]Haim Avron, Huy L. Nguyen, David P. Woodruff:
Subspace Embeddings for the Polynomial Kernel. NIPS 2014: 2258-2266
[c8]Alexandr Andoni, Piotr Indyk, Huy L. Nguyen, Ilya P. Razenshteyn:
Beyond Locality-Sensitive Hashing. SODA 2014: 1018-1028
[c7]Yi Li, Huy L. Nguyen, David P. Woodruff:
On Sketching Matrix Norms and the Top Singular Vector. SODA 2014: 1562-1581
[c6]Yi Li
, Huy L. Nguyen, David P. Woodruff:
Turnstile streaming algorithms might as well be linear sketches. STOC 2014: 174-183
[i8]Kasper Green Larsen, Jelani Nelson, Huy L. Nguyen:
Time lower bounds for nonadaptive turnstile streaming algorithms. CoRR abs/1407.2151 (2014)
[i7]Moses Charikar, Monika Henzinger, Huy L. Nguyen:
Online Bipartite Matching with Decomposable Weights. CoRR abs/1409.2139 (2014)- 2013
[c5]Jelani Nelson, Huy L. Nguyen:
OSNAP: Faster Numerical Linear Algebra Algorithms via Sparser Subspace Embeddings. FOCS 2013: 117-126
[c4]Arnab Bhattacharyya, Mark Braverman, Bernard Chazelle, Huy L. Nguyen:
On the convergence of the Hegselmann-Krause system. ITCS 2013: 61-66
[c3]Jelani Nelson, Huy L. Nguyen:
Sparsity lower bounds for dimensionality reducing maps. STOC 2013: 101-110
[i6]Alexandr Andoni, Piotr Indyk, Huy L. Nguyen, Ilya P. Razenshteyn:
Beyond Locality-Sensitive Hashing. CoRR abs/1306.1547 (2013)
[i5]Jelani Nelson, Huy L. Nguyen:
Lower bounds for oblivious subspace embeddings. CoRR abs/1308.3280 (2013)- 2012
[c2]Jelani Nelson, Huy L. Nguyên, David P. Woodruff:
On Deterministic Sketching and Streaming for Sparse Recovery and Norm Estimation. APPROX-RANDOM 2012: 627-638
[c1]Kasper Green Larsen
, Huy Le Nguyen:
Improved range searching lower bounds. SCG 2012: 171-178
[i4]Jelani Nelson, Huy L. Nguyên, David P. Woodruff:
On Deterministic Sketching and Streaming for Sparse Recovery and Norm Estimation. CoRR abs/1206.5725 (2012)
[i3]Jelani Nelson, Huy L. Nguyen:
Sparsity Lower Bounds for Dimensionality Reducing Maps. CoRR abs/1211.0995 (2012)
[i2]Jelani Nelson, Huy L. Nguyen:
OSNAP: Faster numerical linear algebra algorithms via sparser subspace embeddings. CoRR abs/1211.1002 (2012)
[i1]Arnab Bhattacharyya, Mark Braverman, Bernard Chazelle, Huy L. Nguyen:
On the Convergence of the Hegselmann-Krause System. CoRR abs/1211.1909 (2012)
Coauthor Index

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