Huy L. Nguyen

Orcid: 0000-0001-5128-6545

Affiliations:
  • Princeton University, USA


According to our database1, Huy L. Nguyen authored at least 93 papers between 2009 and 2024.

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Bibliography

2024
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Improved Group Robustness via Classifier Retraining on Independent Splits.
Trans. Mach. Learn. Res., 2023

Identification of Negative Transfers in Multitask Learning Using Surrogate Models.
Trans. Mach. Learn. Res., 2023

Fair and Useful Cohort Selection.
Trans. Mach. Learn. Res., 2023

Online and Streaming Algorithms for Constrained k-Submodular Maximization.
CoRR, 2023

High Probability Convergence of Stochastic Gradient Methods.
CoRR, 2023

Fast Optimal Locally Private Mean Estimation via Random Projections.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Streaming Submodular Maximization with Differential Privacy.
Proceedings of the International Conference on Machine Learning, 2023

Improved Learning-augmented Algorithms for k-means and k-medians Clustering.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

On the Convergence of AdaGrad(Norm) on ℝ<sup>d</sup>: Beyond Convexity, Non-Asymptotic Rate and Acceleration.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

An Efficient Algorithm for Fair Multi-Agent Multi-Armed Bandit with Low Regret.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
An Optimal Streaming Algorithm for Submodular Maximization with a Cardinality Constraint.
Math. Oper. Res., November, 2022

Real-Time Weather Monitoring and IoT-Based Palmtop Device for Smart Agriculture.
SN Comput. Sci., 2022

High Probability Convergence for Accelerated Stochastic Mirror Descent.
CoRR, 2022

META-STORM: Generalized Fully-Adaptive Variance Reduced SGD for Unbounded Functions.
CoRR, 2022

On the Convergence of AdaGrad on $\R^{d}$: Beyond Convexity, Non-Asymptotic Rate and Acceleration.
CoRR, 2022

Fair Range k-center.
CoRR, 2022

Improved Worst-Group Robustness via Classifier Retraining on Independent Splits.
CoRR, 2022

Incremental Neural Synthesis for Spiking Neural Networks.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction.
Proceedings of the International Conference on Machine Learning, 2022

Private frequency estimation via projective geometry.
Proceedings of the International Conference on Machine Learning, 2022

Streaming Algorithm for Monotone k-Submodular Maximization with Cardinality Constraints.
Proceedings of the International Conference on Machine Learning, 2022

Adaptive and Universal Algorithms for Variational Inequalities with Optimal Convergence.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Locally Private k-Means Clustering with Constant Multiplicative Approximation and Near-Optimal Additive Error.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Constraints on Hebbian and STDP learned weights of a spiking neuron.
Neural Networks, 2021

Linear Constraints Learning for Spiking Neurons.
CoRR, 2021

Multi-View Audio And Music Classification.
Proceedings of the IEEE International Conference on Acoustics, 2021

Self-Attention Generative Adversarial Network for Speech Enhancement.
Proceedings of the IEEE International Conference on Acoustics, 2021

Differentially Private k-Means via Exponential Mechanism and Max Cover.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Differentially Private Clustering via Maximum Coverage.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Projection-Free Bandit Optimization with Privacy Guarantees.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Differentially Private Decomposable Submodular Maximization.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Adaptive and Universal Single-gradient Algorithms for Variational Inequalities.
CoRR, 2020

A note on differentially private clustering with large additive error.
CoRR, 2020

Fair and Useful Cohort Selection.
CoRR, 2020

Differentially private k-means clustering via exponential mechanism and max cover.
CoRR, 2020

Adaptive Gradient Methods for Constrained Convex Optimization.
CoRR, 2020

Fair k-Centers via Maximum Matching.
Proceedings of the 37th International Conference on Machine Learning, 2020

Parallel Algorithm for Non-Monotone DR-Submodular Maximization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Optimal Streaming Algorithms for Submodular Maximization with Cardinality Constraints.
Proceedings of the 47th International Colloquium on Automata, Languages, and Programming, 2020

Efficient Private Algorithms for Learning Large-Margin Halfspaces.
Proceedings of the Algorithmic Learning Theory, 2020

2019
On Approximating Matrix Norms in Data Streams.
SIAM J. Comput., 2019

An Optimal Streaming Algorithm for Non-monotone Submodular Maximization.
CoRR, 2019

A note on Cunningham's algorithm for matroid intersection.
CoRR, 2019

Efficient Private Algorithms for Learning Halfspaces.
CoRR, 2019

Heavy hitters via cluster-preserving clustering.
Commun. ACM, 2019

Submodular maximization with matroid and packing constraints in parallel.
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Fast greedy for linear matroids.
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Submodular Maximization with Nearly-optimal Approximation and Adaptivity in Nearly-linear Time.
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Towards Nearly-Linear Time Algorithms for Submodular Maximization with a Matroid Constraint.
Proceedings of the 46th International Colloquium on Automata, Languages, and Programming, 2019

A Nearly-Linear Time Algorithm for Submodular Maximization with a Knapsack Constraint.
Proceedings of the 46th International Colloquium on Automata, Languages, and Programming, 2019

2018
A Parallel Double Greedy Algorithm for Submodular Maximization.
CoRR, 2018

Submodular Maximization with Packing Constraints in Parallel.
CoRR, 2018

Improved Algorithms for Collaborative PAC Learning.
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.
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

Decomposable Submodular Function Minimization: Discrete and Continuous.
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.
ACM Trans. Algorithms, 2016

A Reduction for Optimizing Lattice Submodular Functions with Diminishing Returns.
CoRR, 2016

Submodular Maximization over Sliding Windows.
CoRR, 2016

Communication lower bounds for statistical estimation problems via a distributed data processing inequality.
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

Constrained Submodular Maximization: Beyond 1/e.
Proceedings of the IEEE 57th Annual Symposium on Foundations of Computer Science, 2016

A New Framework for Distributed Submodular Maximization.
Proceedings of the IEEE 57th Annual Symposium on Foundations of Computer Science, 2016

The Problem of the Optimal Packing of the Equal Circles for Special Non-Euclidean Metric.
Proceedings of the Analysis of Images, Social Networks and Texts, 2016

2015
Cutting Corners Cheaply, or How to Remove Steiner Points.
SIAM J. Comput., 2015

Approximate k-flat Nearest Neighbor Search.
Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, 2015

Time Lower Bounds for Nonadaptive Turnstile Streaming Algorithms.
Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, 2015

Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions.
Proceedings of the 32nd International Conference on Machine Learning, 2015

The Power of Randomization: Distributed Submodular Maximization on Massive Datasets.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Algorithms for High Dimensional Data
PhD thesis, 2014

Preserving Terminal Distances Using Minors.
SIAM J. Discret. Math., 2014

Lower Bound for High-Dimensional Statistical Learning Problem via Direct-Sum Theorem.
CoRR, 2014

Turnstile streaming algorithms might as well be linear sketches.
Proceedings of the Symposium on Theory of Computing, 2014

On Sketching Matrix Norms and the Top Singular Vector.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Beyond Locality-Sensitive Hashing.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

On Communication Cost of Distributed Statistical Estimation and Dimensionality.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Subspace Embeddings for the Polynomial Kernel.
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.
Proceedings of the Automata, Languages, and Programming - 41st International Colloquium, 2014

From Graph to Hypergraph Multiway Partition: Is the Single Threshold the Only Route?
Proceedings of the Algorithms - ESA 2014, 2014

Online Bipartite Matching with Decomposable Weights.
Proceedings of the Algorithms - ESA 2014, 2014

2013
Approximate Nearest Neighbor Search in ℓ<sub>p</sub>.
CoRR, 2013

Sparsity lower bounds for dimensionality reducing maps.
Proceedings of the Symposium on Theory of Computing Conference, 2013

Eigenvalues of a matrix in the streaming model.
Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, 2013

On the convergence of the Hegselmann-Krause system.
Proceedings of the Innovations in Theoretical Computer Science, 2013

Tight Lower Bound for Linear Sketches of Moments.
Proceedings of the Automata, Languages, and Programming - 40th International Colloquium, 2013

OSNAP: Faster Numerical Linear Algebra Algorithms via Sparser Subspace Embeddings.
Proceedings of the 54th Annual IEEE Symposium on Foundations of Computer Science, 2013

2012
Big data.
XRDS, 2012

Improved range searching lower bounds.
Proceedings of the 28th ACM Symposium on Computational Geometry, 2012

On Deterministic Sketching and Streaming for Sparse Recovery and Norm Estimation.
Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 2012

2011
Sublinear Time Algorithms for Earth Mover's Distance.
Theory Comput. Syst., 2011

Near Linear Lower Bound for Dimension Reduction in L1.
Proceedings of the IEEE 52nd Annual Symposium on Foundations of Computer Science, 2011

2010
Near-Optimal Sublinear Time Algorithms for Ulam Distance.
Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

2009
Approximate line nearest neighbor in high dimensions.
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009


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