Samson Zhou

ORCID

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 129

Top Venues

Publications

Chunkai Fu, Jung Hoon Seo, Samson Zhou
Learning-Augmented Skip Lists. CoRR (2024)
Vincent Cohen-Addad, David P. Woodruff, Samson Zhou
Streaming Euclidean k-median and k-means with o(log n) Space. CoRR (2023)
Vladimir Braverman, Joel Manning, Zhiwei Steven Wu, Samson Zhou
Private Data Stream Analysis for Universal Symmetric Norm Estimation. CoRR (2023)
Vladimir Braverman, Joel Manning, Zhiwei Steven Wu, Samson Zhou
Private Data Stream Analysis for Universal Symmetric Norm Estimation. APPROX/RANDOM (2023)
Vincent Cohen-Addad, David P. Woodruff, Samson Zhou
Streaming Euclidean k-median and k-means with o(log n) Space. FOCS (2023)
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. CoRR (2023)
Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou
On Differential Privacy and Adaptive Data Analysis with Bounded Space. CoRR (2023)
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR (2023)
David P. Woodruff, Fred Zhang, Samson Zhou
Streaming Algorithms for Learning with Experts: Deterministic Versus Robust. CoRR (2023)
David P. Woodruff, Peilin Zhong, Samson Zhou
Near-Optimal k-Clustering in the Sliding Window Model. NeurIPS (2023)
Guangyao Zheng, Samson Zhou, Vladimir Braverman, Michael A. Jacobs, Vishwa Sanjay Parekh
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. MIDL (2023)
Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou
Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. CoRR (2023)
Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou
Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. ICML (2023)
Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou
On Differential Privacy and Adaptive Data Analysis with Bounded Space. EUROCRYPT (3) (2023)
Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman
Provable Data Subset Selection For Efficient Neural Network Training. CoRR (2023)
Jeremiah Blocki, Elena Grigorescu, Tamalika Mukherjee, Samson Zhou
How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation Algorithms of Functions with Low Sensitivity. APPROX/RANDOM (2023)
Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou
Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model. ICLR (2023)
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA (2023)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou
Differentially Private Aggregation via Imperfect Shuffling. CoRR (2023)
Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman
Provable Data Subset Selection For Efficient Neural Networks Training. ICML (2023)
David P. Woodruff, Fred Zhang, Samson Zhou
On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds. NeurIPS (2023)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
Polynomial Regression. SODA (2023)
David P. Woodruff, Peilin Zhong, Samson Zhou
Near-Optimal k-Clustering in the Sliding Window Model. CoRR (2023)
Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou
-Heavy Hitters in the Sliding Window Model. CoRR (2023)
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou
Differentially Private Aggregation via Imperfect Shuffling. ITC (2023)
Guangyao Zheng, Samson Zhou, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. CoRR (2023)
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR (2023)
Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou
On Differential Privacy and Adaptive Data Analysis with Bounded Space. IACR Cryptol. ePrint Arch. 2023 (2023)
Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. NeurIPS (2022)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
Fast Regression for Structured Inputs. ICLR (2022)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
Fast Regression for Structured Inputs. CoRR (2022)
Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou
Noisy Boolean Hidden Matching with Applications. ITCS (2022)
Vaidehi Srinivas, David P. Woodruff, Ziyu Xu, Samson Zhou
Memory Bounds for the Experts Problem. CoRR (2022)
Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou
The White-Box Adversarial Data Stream Model. CoRR (2022)
Ben Mussay, Dan Feldman, Samson Zhou, Vladimir Braverman, Margarita Osadchy
Data-Independent Structured Pruning of Neural Networks via Coresets. IEEE Trans. Neural Networks Learn. Syst. 33 (12) (2022)
Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman
New Coresets for Projective Clustering and Applications. AISTATS (2022)
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. CoRR (2022)
Jeremiah Blocki, Elena Grigorescu, Tamalika Mukherjee, Samson Zhou
How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation Algorithms of Functions with Low Sensitivity. CoRR (2022)
Sepideh Mahabadi, David P. Woodruff, Samson Zhou
Adaptive Sketches for Robust Regression with Importance Sampling. CoRR (2022)
Jon C. Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou
Learning-Augmented $k$-means Clustering. ICLR (2022)
Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou
Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. CoRR (2022)
Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman
New Coresets for Projective Clustering and Applications. CoRR (2022)
Sepideh Mahabadi, David P. Woodruff, Samson Zhou
Adaptive Sketches for Robust Regression with Importance Sampling. APPROX/RANDOM (2022)
Eric Price, Sandeep Silwal, Samson Zhou
Hardness and Algorithms for Robust and Sparse Optimization. CoRR (2022)
Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou
The White-Box Adversarial Data Stream Model. PODS (2022)
Vaidehi Srinivas, David P. Woodruff, Ziyu Xu, Samson Zhou
Memory bounds for the experts problem. STOC (2022)
David P. Woodruff, Samson Zhou
Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators. FOCS (2022)
Agniva Chowdhury, Aritra Bose, Samson Zhou, David P. Woodruff, Petros Drineas
A Fast, Provably Accurate Approximation Algorithm for Sparse Principal Component Analysis Reveals Human Genetic Variation Across the World. RECOMB (2022)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
Polynomial Regression. CoRR (2022)
Eric Price, Sandeep Silwal, Samson Zhou
Hardness and Algorithms for Robust and Sparse Optimization. ICML (2022)
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR (2022)
Rajesh Jayaram, David P. Woodruff, Samson Zhou
Truly Perfect Samplers for Data Streams and Sliding Windows. PODS (2022)
Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou
Adversarial Robustness of Streaming Algorithms through Importance Sampling. NeurIPS (2021)
David P. Woodruff, Samson Zhou
Separations for Estimating Large Frequency Moments on Data Streams. CoRR (2021)
Vladimir Braverman, Viska Wei, Samson Zhou
Symmetric Norm Estimation and Regression on Sliding Windows. COCOON (2021)
Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou
Adversarial Robustness of Streaming Algorithms through Importance Sampling. CoRR (2021)
Rajesh Jayaram, David P. Woodruff, Samson Zhou
Truly Perfect Samplers for Data Streams and Sliding Windows. CoRR (2021)
David P. Woodruff, Samson Zhou
Separations for Estimating Large Frequency Moments on Data Streams. ICALP (2021)
Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou
Noisy Boolean Hidden Matching with Applications. CoRR (2021)
Yuichi Yoshida, Samson Zhou
Sensitivity Analysis of the Maximum Matching Problem. ITCS (2021)
Vladimir Braverman, Viska Wei, Samson Zhou
Symmetric Norm Estimation and Regression on Sliding Windows. CoRR (2021)
Zachary Izzo, Sandeep Silwal, Samson Zhou
Dimensionality Reduction for Wasserstein Barycenter. CoRR (2021)
Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou
Learning a Latent Simplex in Input-Sparsity Time. CoRR (2021)
Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou
Relaxed Locally Correctable Codes in Computationally Bounded Channels. IEEE Trans. Inf. Theory 67 (7) (2021)
Jon Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou
Learning-Augmented k-means Clustering. CoRR (2021)
Zachary Izzo, Sandeep Silwal, Samson Zhou
Dimensionality Reduction for Wasserstein Barycenter. NeurIPS (2021)
Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou
Learning a Latent Simplex in Input Sparsity Time. ICLR (2021)
Jeremiah Blocki, Seunghoon Lee, Samson Zhou
On the Security of Proofs of Sequential Work in a Post-Quantum World. ITC (2021)
Vladimir Braverman, Dan Feldman, Harry Lang, Adiel Statman, Samson Zhou
Efficient Coreset Constructions via Sensitivity Sampling. ACML (2021)
David P. Woodruff, Samson Zhou
Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators. FOCS (2021)
Jeremiah Blocki, Benjamin Harsha, Samson Zhou
On the Economics of Offline Password Cracking. CoRR (2020)
Jeremiah Blocki, Seunghoon Lee, Samson Zhou
On the Security of Proofs of Sequential Work in a Post-Quantum World. CoRR (2020)
Grigory Yaroslavtsev, Samson Zhou
Fast Fourier Sparsity Testing. SOSA (2020)
Ben Mussay, Margarita Osadchy, Vladimir Braverman, Samson Zhou, Dan Feldman
Data-Independent Neural Pruning via Coresets. ICLR (2020)
Jeremiah Blocki, Shubhang Kulkarni, Samson Zhou
On Locally Decodable Codes in Resource Bounded Channels. ITC (2020)
David P. Woodruff, Samson Zhou
Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators. CoRR (2020)
Mohammad Hassan Ameri, Jeremiah Blocki, Samson Zhou
Computationally Data-Independent Memory Hard Functions. ITCS (2020)
Agniva Chowdhury, Petros Drineas, David P. Woodruff, Samson Zhou
Approximation Algorithms for Sparse Principal Component Analysis. CoRR (2020)
Zaoxing Liu, Samson Zhou, Ori Rottenstreich, Vladimir Braverman, Jennifer Rexford
Memory-Efficient Performance Monitoring on Programmable Switches with Lean Algorithms. APOCS (2020)
Grigory Yaroslavtsev, Samson Zhou, Dmitrii Avdiukhin
"Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack. AISTATS (2020)
Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou
Periodicity in Data Streams with Wildcards. Theory Comput. Syst. 64 (1) (2020)
Ben Mussay, Dan Feldman, Samson Zhou, Vladimir Braverman, Margarita Osadchy
Data-Independent Structured Pruning of Neural Networks via Coresets. CoRR (2020)
Jeremiah Blocki, Seunghoon Lee, Samson Zhou
Approximating Cumulative Pebbling Cost Is Unique Games Hard. ITCS (2020)
Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou
Near Optimal Linear Algebra in the Online and Sliding Window Models. FOCS (2020)
Yuichi Yoshida, Samson Zhou
Sensitivity Analysis of the Maximum Matching Problem. CoRR (2020)
Sepideh Mahabadi, Ilya P. Razenshteyn, David P. Woodruff, Samson Zhou
Non-adaptive adaptive sampling on turnstile streams. STOC (2020)
Sepideh Mahabadi, Ilya P. Razenshteyn, David P. Woodruff, Samson Zhou
Non-Adaptive Adaptive Sampling on Turnstile Streams. CoRR (2020)
Jeremiah Blocki, Shubhang Kulkarni, Samson Zhou
On Locally Decodable Codes in Resource Bounded Channels. CoRR (2019)
Vladimir Braverman, Harry Lang, Enayat Ullah, Samson Zhou
Improved Algorithms for Time Decay Streams. APPROX-RANDOM (2019)
Ben Mussay, Samson Zhou, Vladimir Braverman, Dan Feldman
On Activation Function Coresets for Network Pruning. CoRR (2019)
Dmitrii Avdiukhin, Grigory Yaroslavtsev, Samson Zhou
"Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack. CoRR (2019)
Grigory Yaroslavtsev, Samson Zhou
Fast Fourier Sparsity Testing. CoRR (2019)
Dmitrii Avdiukhin, Slobodan Mitrovic, Grigory Yaroslavtsev, Samson Zhou
Adversarially Robust Submodular Maximization under Knapsack Constraints. KDD (2019)
Marc Bury, Elena Grigorescu, Andrew McGregor, Morteza Monemizadeh, Chris Schwiegelshohn, Sofya Vorotnikova, Samson Zhou
Structural Results on Matching Estimation with Applications to Streaming. Algorithmica 81 (1) (2019)
Jeremiah Blocki, Benjamin Harsha, Siteng Kang, Seunghoon Lee, Lu Xing, Samson Zhou
Data-Independent Memory Hard Functions: New Attacks and Stronger Constructions. CRYPTO (2) (2019)
Grigory Yaroslavtsev, Samson Zhou
-Sketching of Valuation Functions. CoRR (2019)
Vladimir Braverman, Harry Lang, Enayat Ullah, Samson Zhou
Improved Algorithms for Time Decay Streams. CoRR (2019)
Zaoxing Liu, Samson Zhou, Ori Rottenstreich, Vladimir Braverman, Jennifer Rexford
Memory-Efficient Performance Monitoring on Programmable Switches with Lean Algorithms. CoRR (2019)
Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou
Relaxed Locally Correctable Codes in Computationally Bounded Channels. ISIT (2019)
Grigory Yaroslavtsev, Samson Zhou
-Sketching of Valuation Functions. APPROX-RANDOM (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Samson Zhou