Samson Zhou
29 papers · 2020–2025 · 6 venues · across top CS/AI venues
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Achievements
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(11)
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Research topics
Machine Learning
(25)
Optimization & Theory
(18)
Mathematics & Optimization
(16)
Optimization
(15)
Computer Science
(12)
Foundations
(11)
Core Methods
(8)
Data Science & Analytics
(7)
Applications
(7)
Artificial Intelligence
(6)
Application Areas
(6)
Learning Types
(6)
Core AI
(4)
Mathematics
(4)
Learning Paradigms
(2)
Keywords
streaming algorithm
(7)
approximation algorithm
(7)
coreset construction
(5)
differential privacy
(4)
low-rank approximation
(4)
learning-augmented algorithm
(3)
sliding window model
(3)
bicriteria approximation
(3)
approximation
(2)
heavy hitter
(2)
adversarial robustness
(2)
robust regression
(2)
projective clustering
(2)
approximation error
(2)
k-means clustering
(2)
matrix factorization
(2)
hierarchical clustering
(2)
kernel density estimation
(2)
semidefinite programming
(1)
online learning
(1)
Papers
Fair Clustering in the Sliding Window Model
ICLR 2025
Fair Submodular Cover
ICLR 2025
Learning-Augmented Hierarchical Clustering
ICML 2025
Learning-Augmented Search Data Structures
ICLR 2025
On Fine-Grained Distinct Element Estimation
ICML 2025
On the Price of Differential Privacy for Hierarchical Clustering
ICLR 2025
Relative Error Fair Clustering in the Weak-Strong Oracle Model
ICML 2025
Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters
NeurIPS 2024
On Socially Fair Low-Rank Approximation and Column Subset Selection
NeurIPS 2024
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages
ICML 2024
Differentially Private L_2-Heavy Hitters in the Sliding Window Model
ICLR 2023
Fast (1+Ξ΅)-Approximation Algorithms for Binary Matrix Factorization
ICML 2023
Near-Optimal k-Clustering in the Sliding Window Model
NeurIPS 2023
On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds
NeurIPS 2023
Provable Data Subset Selection For Efficient Neural Networks Training
ICML 2023
Robust Algorithms on Adaptive Inputs from Bounded Adversaries
ICLR 2023
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging
MIDL 2023
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation
ICLR 2023
Fast Regression for Structured Inputs
ICLR 2022
Hardness and Algorithms for Robust and Sparse Optimization
ICML 2022
Learning-Augmented k-means Clustering
ICLR 2022
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming
NeurIPS 2022
New Coresets for Projective Clustering and Applications
AISTATS 2022
Adversarial Robustness of Streaming Algorithms through Importance Sampling
NeurIPS 2021
Dimensionality Reduction for Wasserstein Barycenter
NeurIPS 2021
Efficient Coreset Constructions via Sensitivity Sampling
ACML 2021
Learning a Latent Simplex in Input Sparsity Time
ICLR 2021
βBring Your Own Greedyβ+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack
AISTATS 2020
Data-Independent Neural Pruning via Coresets
ICLR 2020