Samson Zhou
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
50
Venues
20
Active years
2017–2026
Best venue rank
A*
Where they publish
Papers
50 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | SODA | Online Learning with Limited Information in the Sliding Window Model. | Vladimir Braverman, Sumegha Garg, Chen Wang, David P. Woodruff, Samson Zhou |
| 2026 | SODA | L | Honghao Lin, Zhao Song, David P. Woodruff, Shenghao Xie, Samson Zhou |
| 2026 | STOC | Adversarial Robustness on Insertion-Deletion Streams. | Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou |
| 2025 | FOCS | Perfect Lp Sampling with Polylogarithmic Update Time. | William Swartworth, David P. Woodruff, Samson Zhou |
| 2025 | ICLR | Fair Submodular Cover. | Wenjing Chen, Shuo Xing, Samson Zhou, Victoria G. Crawford |
| 2025 | ICLR | Fair Clustering in the Sliding Window Model. | Vincent Cohen-Addad, Shaofeng H.-C. Jiang, Qiaoyuan Yang, Yubo Zhang, Samson Zhou |
| 2025 | ICLR | On the Price of Differential Privacy for Hierarchical Clustering. | Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang, Samson Zhou |
| 2025 | ICLR | Learning-Augmented Search Data Structures. | Chunkai Fu, Brandon G. Nguyen, Jung Hoon Seo, Ryan S. Zesch, Samson Zhou |
| 2025 | ICML | Relative Error Fair Clustering in the Weak-Strong Oracle Model. | Vladimir Braverman, Prathamesh Dharangutte, Shaofeng H.-C. Jiang, Hoai-An Nguyen, Chen Wang, Yubo Zhang, Samson Zhou |
| 2025 | ICML | Learning-Augmented Hierarchical Clustering. | Vladimir Braverman, Jon C. Ergun, Chen Wang, Samson Zhou |
| 2025 | ICML | On Fine-Grained Distinct Element Estimation. | Ilias Diakonikolas, Daniel Kane, Jasper C. H. Lee, Thanasis Pittas, David P. Woodruff, Samson Zhou |
| 2025 | STOC | Lifting Linear Sketches: Optimal Bounds and Adversarial Robustness. | Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou |
| 2024 | FOCS | A Strong Separation for Adversarially Robust ℓ0 Estimation for Linear Sketches. | Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou |
| 2024 | ICML | Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. | Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou |
| 2023 | EuroCrypt | On Differential Privacy and Adaptive Data Analysis with Bounded Space. | Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou |
| 2023 | FOCS | Streaming Euclidean k-median and k-means with o(log n) Space. | Vincent Cohen-Addad, David P. Woodruff, Samson Zhou |
| 2023 | ICLR | Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. | Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou |
| 2023 | ICLR | Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model. | Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou |
| 2023 | ICLR | Robust Algorithms on Adaptive Inputs from Bounded Adversaries. | Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou |
| 2023 | ICML | Provable Data Subset Selection For Efficient Neural Networks Training. | Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman |
| 2023 | ICML | Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. | Ameya Velingker, Maximilian Vtsch, David P. Woodruff, Samson Zhou |
| 2023 | SODA | Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. | Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou |
| 2023 | SODA | Near-Linear Sample Complexity for | Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou |
| 2022 | AISTATS | New Coresets for Projective Clustering and Applications. | Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman |
| 2022 | ICLR | Learning-Augmented $k$-means Clustering. | Jon C. Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou |
| 2022 | ICLR | Fast Regression for Structured Inputs. | Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou |
| 2022 | ICML | Hardness and Algorithms for Robust and Sparse Optimization. | Eric Price, Sandeep Silwal, Samson Zhou |
| 2022 | PODS | The White-Box Adversarial Data Stream Model. | Mikls Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou |
| 2022 | PODS | Truly Perfect Samplers for Data Streams and Sliding Windows. | Rajesh Jayaram, David P. Woodruff, Samson Zhou |
| 2022 | RECOMB | A Fast, Provably Accurate Approximation Algorithm for Sparse Principal Component Analysis Reveals Human Genetic Variation Across the World. | Agniva Chowdhury, Aritra Bose, Samson Zhou, David P. Woodruff, Petros Drineas |
| 2022 | STOC | Memory bounds for the experts problem. | Vaidehi Srinivas, David P. Woodruff, Ziyu Xu, Samson Zhou |
| 2021 | ACML | Efficient Coreset Constructions via Sensitivity Sampling. | Vladimir Braverman, Dan Feldman, Harry Lang, Adiel Statman, Samson Zhou |
| 2021 | COCOON | Symmetric Norm Estimation and Regression on Sliding Windows. | Vladimir Braverman, Viska Wei, Samson Zhou |
| 2021 | FOCS | Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators. | David P. Woodruff, Samson Zhou |
| 2021 | ICALP | Separations for Estimating Large Frequency Moments on Data Streams. | David P. Woodruff, Samson Zhou |
| 2021 | ICLR | Learning a Latent Simplex in Input Sparsity Time. | Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou |
| 2020 | AISTATS | "Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack. | Grigory Yaroslavtsev, Samson Zhou, Dmitrii Avdiukhin |
| 2020 | FOCS | Near Optimal Linear Algebra in the Online and Sliding Window Models. | Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou |
| 2020 | ICLR | Data-Independent Neural Pruning via Coresets. | Ben Mussay, Margarita Osadchy, Vladimir Braverman, Samson Zhou, Dan Feldman |
| 2020 | SODA | Fast Fourier Sparsity Testing. | Grigory Yaroslavtsev, Samson Zhou |
| 2020 | STOC | Non-adaptive adaptive sampling on turnstile streams. | Sepideh Mahabadi, Ilya P. Razenshteyn, David P. Woodruff, Samson Zhou |
| 2019 | CRYPTO | Data-Independent Memory Hard Functions: New Attacks and Stronger Constructions. | Jeremiah Blocki, Benjamin Harsha, Siteng Kang, Seunghoon Lee, Lu Xing, Samson Zhou |
| 2019 | ISIT | Relaxed Locally Correctable Codes in Computationally Bounded Channels. | Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou |
| 2019 | KDD | Adversarially Robust Submodular Maximization under Knapsack Constraints. | Dmitrii Avdiukhin, Slobodan Mitrovic, Grigory Yaroslavtsev, Samson Zhou |
| 2018 | CCS | Bandwidth-Hard Functions: Reductions and Lower Bounds. | Jeremiah Blocki, Ling Ren, Samson Zhou |
| 2018 | CSR | Periodicity in Data Streams with Wildcards. | Funda Ergn, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou |
| 2018 | FC | On the Computational Complexity of Minimal Cumulative Cost Graph Pebbling. | Jeremiah Blocki, Samson Zhou |
| 2018 | ICALP | Brief Announcement: Relaxed Locally Correctable Codes in Computationally Bounded Channels. | Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou |
| 2018 | SP | On the Economics of Offline Password Cracking. | Jeremiah Blocki, Benjamin Harsha, Samson Zhou |
| 2017 | TCC | On the Depth-Robustness and Cumulative Pebbling Cost of Argon2i. | Jeremiah Blocki, Samson Zhou |