Samson Zhou - RankMe

176 papers A* 45A 12B 2C 1Misc 2Journal 99Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Accelerating Scientific Research with Gemini: Case Studies and Common Techniques. CoRR David P. Woodruff, Vincent Cohen-Addad, Lalit Jain, Jieming Mao, Song Zuo, MohammadHossein Bateni, Simina Brânzei, Michael P. Brenner, Lin Chen, Ying Feng, Lance Fortnow, Gang Fu, Ziyi Guan, Zahra Hadizadeh, Mohammad T. Hajiaghayi, Mahdi JafariRaviz, Adel Javanmard, Karthik C. S., Ken-ichi Kawarabayashi, Ravi Kumar, Silvio Lattanzi, Euiwoong Lee, Yi Li, Ioannis Panageas, Dimitris Paparas, Benjamin Przybocki, Bernardo Subercaseaux, Ola Svensson, Shayan Taherijam, Xuan Wu, Eylon Yogev, Morteza Zadimoghaddam, Samson Zhou, Yossi Matias, James Manyika, Vahab Mirrokni
2026	J	`jnl`	Adversarial Robustness on Insertion-Deletion Streams. CoRR Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou
2026	J	`jnl`	Better Bounds for the Distributed Experts Problem. CoRR David P. Woodruff, Samson Zhou
2026	J	`jnl`	Consistent Low-Rank Approximation. CoRR David P. Woodruff, Samson Zhou
2026	J	`jnl`	Distributed Algorithms for Euclidean Clustering. CoRR Vincent Cohen-Addad, Liudeng Wang, David P. Woodruff, Samson Zhou
2026	A*	`conf`	L SODA Honghao Lin, Zhao Song, David P. Woodruff, Shenghao Xie, Samson Zhou
2026	J	`jnl`	Learning-Augmented Moment Estimation on Time-Decay Models. CoRR Soham Nagawanshi, Shalini Panthangi, Chen Wang, David P. Woodruff, Samson Zhou
2026	A*	`conf`	Online Learning with Limited Information in the Sliding Window Model. SODA Vladimir Braverman, Sumegha Garg, Chen Wang, David P. Woodruff, Samson Zhou
2026	J	`jnl`	Online Learning with Limited Information in the Sliding Window Model. CoRR Vladimir Braverman, Sumegha Garg, Chen Wang, David P. Woodruff, Samson Zhou
2025	A*	`conf`	Fair Clustering in the Sliding Window Model. ICLR Vincent Cohen-Addad, Shaofeng H.-C. Jiang, Qiaoyuan Yang, Yubo Zhang, Samson Zhou
2025	J	`jnl`	Fair Clustering in the Sliding Window Model. CoRR Vincent Cohen-Addad, Shaofeng H.-C. Jiang, Qiaoyuan Yang, Yubo Zhang, Samson Zhou
2025	A*	`conf`	Fair Submodular Cover. ICLR Wenjing Chen, Shuo Xing, Samson Zhou, Victoria G. Crawford
2025	J	`jnl`	Fast, Space-Optimal Streaming Algorithms for Clustering and Subspace Embeddings. CoRR Vincent Cohen-Addad, Liudeng Wang, David P. Woodruff, Samson Zhou
2025	J	`jnl`	L CoRR Honghao Lin, Zhao Song, David P. Woodruff, Shenghao Xie, Samson Zhou
2025	A*	`conf`	Learning-Augmented Hierarchical Clustering. ICML Vladimir Braverman, Jon C. Ergun, Chen Wang, Samson Zhou
2025	J	`jnl`	Learning-Augmented Hierarchical Clustering. CoRR Vladimir Braverman, Jon C. Ergun, Chen Wang, Samson Zhou
2025	A*	`conf`	Learning-Augmented Search Data Structures. ICLR Chunkai Fu, Brandon G. Nguyen, Jung Hoon Seo, Ryan S. Zesch, Samson Zhou
2025	A*	`conf`	Lifting Linear Sketches: Optimal Bounds and Adversarial Robustness. STOC Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou
2025	J	`jnl`	Lifting Linear Sketches: Optimal Bounds and Adversarial Robustness. CoRR Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou
2025	J	`jnl`	Nearly Space-Optimal Graph and Hypergraph Sparsification in Insertion-Only Data Streams. CoRR Vincent Cohen-Addad, David P. Woodruff, Shenghao Xie, Samson Zhou
2025	A*	`conf`	On Approximability of ℓ₂² Min-Sum Clustering. SoCG Karthik C. S., Euiwoong Lee, Yuval Rabani, Chris Schwiegelshohn, Samson Zhou
2025	A*	`conf`	On Fine-Grained Distinct Element Estimation. ICML Ilias Diakonikolas, Daniel Kane, Jasper C. H. Lee, Thanasis Pittas, David P. Woodruff, Samson Zhou
2025	J	`jnl`	On Fine-Grained Distinct Element Estimation. CoRR Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Thanasis Pittas, David P. Woodruff, Samson Zhou
2025	A*	`conf`	On the Price of Differential Privacy for Hierarchical Clustering. ICLR Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang, Samson Zhou
2025	J	`jnl`	On the Price of Differential Privacy for Hierarchical Clustering. CoRR Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang, Samson Zhou
2025	J	`jnl`	Perfect L CoRR William Swartworth, David P. Woodruff, Samson Zhou
2025	A*	`conf`	Perfect Lp Sampling with Polylogarithmic Update Time. FOCS William Swartworth, David P. Woodruff, Samson Zhou
2025	J	`jnl`	Perfect Sampling in Turnstile Streams Beyond Small Moments. CoRR David P. Woodruff, Shenghao Xie, Samson Zhou
2025	J	`jnl`	Perfect Sampling in Turnstile Streams Beyond Small Moments. Proc. ACM Manag. Data David P. Woodruff, Shenghao Xie, Samson Zhou
2025	J	`jnl`	Private Training & Data Generation by Clustering Embeddings. CoRR Felix Zhou, Samson Zhou, Vahab Mirrokni, Alessandro Epasto, Vincent Cohen-Addad
2025	A*	`conf`	Relative Error Fair Clustering in the Weak-Strong Oracle Model. ICML Vladimir Braverman, Prathamesh Dharangutte, Shaofeng H.-C. Jiang, Hoai-An Nguyen, Chen Wang, Yubo Zhang, Samson Zhou
2025	J	`jnl`	Relative Error Fair Clustering in the Weak-Strong Oracle Model. CoRR Vladimir Braverman, Prathamesh Dharangutte, Shaofeng H.-C. Jiang, Hoai-An Nguyen, Chen Wang, Yubo Zhang, Samson Zhou
2025	J	`jnl`	Towards Sampling Data Structures for Tensor Products in Turnstile Streams. CoRR Zhao Song, Shenghao Xie, Samson Zhou
2025	J	`jnl`	Transductive and Learning-Augmented Online Regression. CoRR Vinod Raman, Shenghao Xie, Samson Zhou
2024	J	`jnl`	A Strong Separation for Adversarially Robust ℓ CoRR Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou
2024	A*	`conf`	A Strong Separation for Adversarially Robust ℓ0 Estimation for Linear Sketches. FOCS Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou
2024	A*	`conf`	Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters. NeurIPS David P. Woodruff, Samson Zhou
2024	J	`jnl`	Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters. CoRR David P. Woodruff, Samson Zhou
2024	J	`jnl`	Bandwidth-Hard Functions: Reductions and Lower Bounds. J. Cryptol. Jeremiah Blocki, Peiyuan Liu, Ling Ren, Samson Zhou
2024	J	`jnl`	Fair Submodular Cover. CoRR Wenjing Chen, Shuo Xing, Samson Zhou, Victoria G. Crawford
2024	J	`jnl`	Learning-Augmented Skip Lists. CoRR Chunkai Fu, Jung Hoon Seo, Samson Zhou
2024	J	`jnl`	On Approximability of ℓ CoRR Karthik C. S., Euiwoong Lee, Yuval Rabani, Chris Schwiegelshohn, Samson Zhou
2024	A*	`conf`	On Socially Fair Low-Rank Approximation and Column Subset Selection. NeurIPS Zhao Song, Ali Vakilian, David P. Woodruff, Samson Zhou
2024	J	`jnl`	On Socially Fair Low-Rank Approximation and Column Subset Selection. CoRR Zhao Song, Ali Vakilian, David P. Woodruff, Samson Zhou
2024	A*	`conf`	Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. ICML Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou
2024	J	`jnl`	Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages. CoRR Hilal Asi, Vitaly Feldman, Jelani Nelson, Huy L. Nguyen, Kunal Talwar, Samson Zhou
2024	J	`jnl`	Streaming Algorithms with Few State Changes. CoRR Rajesh Jayaram, David P. Woodruff, Samson Zhou
2024	J	`jnl`	Streaming Algorithms with Few State Changes. Proc. ACM Manag. Data Rajesh Jayaram, David P. Woodruff, Samson Zhou
2023	A*	`conf`	Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model. ICLR Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou
2023	A	`conf`	Differentially Private Aggregation via Imperfect Shuffling. ITC Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou
2023	J	`jnl`	Differentially Private Aggregation via Imperfect Shuffling. CoRR Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou
2023	J	`jnl`	Differentially Private L CoRR Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou
2023	A*	`conf`	Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. ICML Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou
2023	J	`jnl`	Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. CoRR Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou
2023	A	`conf`	How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation Algorithms of Functions with Low Sensitivity. APPROX/RANDOM Jeremiah Blocki, Elena Grigorescu, Tamalika Mukherjee, Samson Zhou
2023	A*	`conf`	Near-Linear Sample Complexity for SODA Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2023	A*	`conf`	Near-Optimal k-Clustering in the Sliding Window Model. NeurIPS David P. Woodruff, Peilin Zhong, Samson Zhou
2023	J	`jnl`	Near-Optimal k-Clustering in the Sliding Window Model. CoRR David P. Woodruff, Peilin Zhong, Samson Zhou
2023	—	`conf`	On Differential Privacy and Adaptive Data Analysis with Bounded Space. EUROCRYPT (3) Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou
2023	J	`jnl`	On Differential Privacy and Adaptive Data Analysis with Bounded Space. CoRR Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou
2023	J	`jnl`	On Differential Privacy and Adaptive Data Analysis with Bounded Space. IACR Cryptol. ePrint Arch. Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou
2023	A*	`conf`	On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds. NeurIPS David P. Woodruff, Fred Zhang, Samson Zhou
2023	A*	`conf`	Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
2023	A	`conf`	Private Data Stream Analysis for Universal Symmetric Norm Estimation. APPROX/RANDOM Vladimir Braverman, Joel Manning, Zhiwei Steven Wu, Samson Zhou
2023	J	`jnl`	Private Data Stream Analysis for Universal Symmetric Norm Estimation. CoRR Vladimir Braverman, Joel Manning, Zhiwei Steven Wu, Samson Zhou
2023	J	`jnl`	Provable Data Subset Selection For Efficient Neural Network Training. CoRR Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman
2023	A*	`conf`	Provable Data Subset Selection For Efficient Neural Networks Training. ICML Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman
2023	A*	`conf`	Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
2023	J	`jnl`	Robust Algorithms on Adaptive Inputs from Bounded Adversaries. CoRR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
2023	—	`conf`	Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. MIDL Guangyao Zheng, Samson Zhou, Vladimir Braverman, Michael A. Jacobs, Vishwa Sanjay Parekh
2023	J	`jnl`	Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. CoRR Guangyao Zheng, Samson Zhou, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh
2023	J	`jnl`	Streaming Algorithms for Learning with Experts: Deterministic Versus Robust. CoRR David P. Woodruff, Fred Zhang, Samson Zhou
2023	A*	`conf`	Streaming Euclidean k-median and k-means with o(log n) Space. FOCS Vincent Cohen-Addad, David P. Woodruff, Samson Zhou
2023	J	`jnl`	Streaming Euclidean k-median and k-means with o(log n) Space. CoRR Vincent Cohen-Addad, David P. Woodruff, Samson Zhou
2023	A*	`conf`	Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
2022	B	`conf`	A Fast, Provably Accurate Approximation Algorithm for Sparse Principal Component Analysis Reveals Human Genetic Variation Across the World. RECOMB Agniva Chowdhury, Aritra Bose, Samson Zhou, David P. Woodruff, Petros Drineas
2022	A	`conf`	Adaptive Sketches for Robust Regression with Importance Sampling. APPROX/RANDOM Sepideh Mahabadi, David P. Woodruff, Samson Zhou
2022	J	`jnl`	Adaptive Sketches for Robust Regression with Importance Sampling. CoRR Sepideh Mahabadi, David P. Woodruff, Samson Zhou
2022	J	`jnl`	Data-Independent Structured Pruning of Neural Networks via Coresets. IEEE Trans. Neural Networks Learn. Syst. Ben Mussay, Dan Feldman, Samson Zhou, Vladimir Braverman, Margarita Osadchy
2022	A*	`conf`	Fast Regression for Structured Inputs. ICLR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2022	J	`jnl`	Fast Regression for Structured Inputs. CoRR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2022	A*	`conf`	Hardness and Algorithms for Robust and Sparse Optimization. ICML Eric Price, Sandeep Silwal, Samson Zhou
2022	J	`jnl`	Hardness and Algorithms for Robust and Sparse Optimization. CoRR Eric Price, Sandeep Silwal, Samson Zhou
2022	J	`jnl`	How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation Algorithms of Functions with Low Sensitivity. CoRR Jeremiah Blocki, Elena Grigorescu, Tamalika Mukherjee, Samson Zhou
2022	A*	`conf`	Learning-Augmented $k$-means Clustering. ICLR Jon C. Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou
2022	A*	`conf`	Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. NeurIPS Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou
2022	J	`jnl`	Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. CoRR Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou
2022	J	`jnl`	Memory Bounds for the Experts Problem. CoRR Vaidehi Srinivas, David P. Woodruff, Ziyu Xu, Samson Zhou
2022	A*	`conf`	Memory bounds for the experts problem. STOC Vaidehi Srinivas, David P. Woodruff, Ziyu Xu, Samson Zhou
2022	J	`jnl`	Near-Linear Sample Complexity for L CoRR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2022	A	`conf`	New Coresets for Projective Clustering and Applications. AISTATS Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman
2022	J	`jnl`	New Coresets for Projective Clustering and Applications. CoRR Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman
2022	A	`conf`	Noisy Boolean Hidden Matching with Applications. ITCS Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou
2022	J	`jnl`	Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. CoRR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
2022	J	`jnl`	Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
2022	A*	`conf`	The White-Box Adversarial Data Stream Model. PODS Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou
2022	J	`jnl`	The White-Box Adversarial Data Stream Model. CoRR Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou
2022	A*	`conf`	Truly Perfect Samplers for Data Streams and Sliding Windows. PODS Rajesh Jayaram, David P. Woodruff, Samson Zhou
2021	A*	`conf`	Adversarial Robustness of Streaming Algorithms through Importance Sampling. NeurIPS Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou
2021	J	`jnl`	Adversarial Robustness of Streaming Algorithms through Importance Sampling. CoRR Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou
2021	A*	`conf`	Dimensionality Reduction for Wasserstein Barycenter. NeurIPS Zachary Izzo, Sandeep Silwal, Samson Zhou
2021	J	`jnl`	Dimensionality Reduction for Wasserstein Barycenter. CoRR Zachary Izzo, Sandeep Silwal, Samson Zhou
2021	C	`conf`	Efficient Coreset Constructions via Sensitivity Sampling. ACML Vladimir Braverman, Dan Feldman, Harry Lang, Adiel Statman, Samson Zhou
2021	A*	`conf`	Learning a Latent Simplex in Input Sparsity Time. ICLR Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou
2021	J	`jnl`	Learning a Latent Simplex in Input-Sparsity Time. CoRR Ainesh Bakshi, Chiranjib Bhattacharyya, Ravi Kannan, David P. Woodruff, Samson Zhou
2021	J	`jnl`	Learning-Augmented k-means Clustering. CoRR Jon Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou
2021	J	`jnl`	Noisy Boolean Hidden Matching with Applications. CoRR Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou
2021	A	`conf`	On the Security of Proofs of Sequential Work in a Post-Quantum World. ITC Jeremiah Blocki, Seunghoon Lee, Samson Zhou
2021	J	`jnl`	Relaxed Locally Correctable Codes in Computationally Bounded Channels. IEEE Trans. Inf. Theory Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou
2021	A	`conf`	Sensitivity Analysis of the Maximum Matching Problem. ITCS Yuichi Yoshida, Samson Zhou
2021	A*	`conf`	Separations for Estimating Large Frequency Moments on Data Streams. ICALP David P. Woodruff, Samson Zhou
2021	J	`jnl`	Separations for Estimating Large Frequency Moments on Data Streams. CoRR David P. Woodruff, Samson Zhou
2021	Misc	`conf`	Symmetric Norm Estimation and Regression on Sliding Windows. COCOON Vladimir Braverman, Viska Wei, Samson Zhou
2021	J	`jnl`	Symmetric Norm Estimation and Regression on Sliding Windows. CoRR Vladimir Braverman, Viska Wei, Samson Zhou
2021	A*	`conf`	Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators. FOCS David P. Woodruff, Samson Zhou
2021	J	`jnl`	Truly Perfect Samplers for Data Streams and Sliding Windows. CoRR Rajesh Jayaram, David P. Woodruff, Samson Zhou
2020	A	`conf`	"Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack. AISTATS Grigory Yaroslavtsev, Samson Zhou, Dmitrii Avdiukhin
2020	A	`conf`	Approximating Cumulative Pebbling Cost Is Unique Games Hard. ITCS Jeremiah Blocki, Seunghoon Lee, Samson Zhou
2020	J	`jnl`	Approximation Algorithms for Sparse Principal Component Analysis. CoRR Agniva Chowdhury, Petros Drineas, David P. Woodruff, Samson Zhou
2020	A	`conf`	Computationally Data-Independent Memory Hard Functions. ITCS Mohammad Hassan Ameri, Jeremiah Blocki, Samson Zhou
2020	A*	`conf`	Data-Independent Neural Pruning via Coresets. ICLR Ben Mussay, Margarita Osadchy, Vladimir Braverman, Samson Zhou, Dan Feldman
2020	J	`jnl`	Data-Independent Structured Pruning of Neural Networks via Coresets. CoRR Ben Mussay, Dan Feldman, Samson Zhou, Vladimir Braverman, Margarita Osadchy
2020	—	`conf`	Fast Fourier Sparsity Testing. SOSA Grigory Yaroslavtsev, Samson Zhou
2020	—	`conf`	Memory-Efficient Performance Monitoring on Programmable Switches with Lean Algorithms. APOCS Zaoxing Liu, Samson Zhou, Ori Rottenstreich, Vladimir Braverman, Jennifer Rexford
2020	A*	`conf`	Near Optimal Linear Algebra in the Online and Sliding Window Models. FOCS Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou
2020	J	`jnl`	Non-Adaptive Adaptive Sampling on Turnstile Streams. CoRR Sepideh Mahabadi, Ilya P. Razenshteyn, David P. Woodruff, Samson Zhou
2020	A*	`conf`	Non-adaptive adaptive sampling on turnstile streams. STOC Sepideh Mahabadi, Ilya P. Razenshteyn, David P. Woodruff, Samson Zhou
2020	A	`conf`	On Locally Decodable Codes in Resource Bounded Channels. ITC Jeremiah Blocki, Shubhang Kulkarni, Samson Zhou
2020	J	`jnl`	On the Economics of Offline Password Cracking. CoRR Jeremiah Blocki, Benjamin Harsha, Samson Zhou
2020	J	`jnl`	On the Security of Proofs of Sequential Work in a Post-Quantum World. CoRR Jeremiah Blocki, Seunghoon Lee, Samson Zhou
2020	J	`jnl`	Periodicity in Data Streams with Wildcards. Theory Comput. Syst. Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou
2020	J	`jnl`	Sensitivity Analysis of the Maximum Matching Problem. CoRR Yuichi Yoshida, Samson Zhou
2020	J	`jnl`	Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators. CoRR David P. Woodruff, Samson Zhou
2019	J	`jnl`	"Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack. CoRR Dmitrii Avdiukhin, Grigory Yaroslavtsev, Samson Zhou
2019	A*	`conf`	Adversarially Robust Submodular Maximization under Knapsack Constraints. KDD Dmitrii Avdiukhin, Slobodan Mitrovic, Grigory Yaroslavtsev, Samson Zhou
2019	J	`jnl`	Adversarially Robust Submodular Maximization under Knapsack Constraints. CoRR Dmitrii Avdiukhin, Slobodan Mitrovic, Grigory Yaroslavtsev, Samson Zhou
2019	—	`conf`	Approximate F APPROX-RANDOM Grigory Yaroslavtsev, Samson Zhou
2019	J	`jnl`	Approximate F CoRR Grigory Yaroslavtsev, Samson Zhou
2019	J	`jnl`	Approximating Cumulative Pebbling Cost is Unique Games Hard. CoRR Jeremiah Blocki, Seunghoon Lee, Samson Zhou
2019	J	`jnl`	Computationally Data-Independent Memory Hard Functions. CoRR Mohammad Hassan Ameri, Jeremiah Blocki, Samson Zhou
2019	—	`conf`	Data-Independent Memory Hard Functions: New Attacks and Stronger Constructions. CRYPTO (2) Jeremiah Blocki, Benjamin Harsha, Siteng Kang, Seunghoon Lee, Lu Xing, Samson Zhou
2019	J	`jnl`	Fast Fourier Sparsity Testing. CoRR Grigory Yaroslavtsev, Samson Zhou
2019	—	`conf`	Improved Algorithms for Time Decay Streams. APPROX-RANDOM Vladimir Braverman, Harry Lang, Enayat Ullah, Samson Zhou
2019	J	`jnl`	Improved Algorithms for Time Decay Streams. CoRR Vladimir Braverman, Harry Lang, Enayat Ullah, Samson Zhou
2019	J	`jnl`	Memory-Efficient Performance Monitoring on Programmable Switches with Lean Algorithms. CoRR Zaoxing Liu, Samson Zhou, Ori Rottenstreich, Vladimir Braverman, Jennifer Rexford
2019	J	`jnl`	Nearly Optimal Sparse Group Testing. IEEE Trans. Inf. Theory Venkata Gandikota, Elena Grigorescu, Sidharth Jaggi, Samson Zhou
2019	J	`jnl`	On Activation Function Coresets for Network Pruning. CoRR Ben Mussay, Samson Zhou, Vladimir Braverman, Dan Feldman
2019	J	`jnl`	On Locally Decodable Codes in Resource Bounded Channels. CoRR Jeremiah Blocki, Shubhang Kulkarni, Samson Zhou
2019	B	`conf`	Relaxed Locally Correctable Codes in Computationally Bounded Channels. ISIT Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou
2019	J	`jnl`	Structural Results on Matching Estimation with Applications to Streaming. Algorithmica Marc Bury, Elena Grigorescu, Andrew McGregor, Morteza Monemizadeh, Chris Schwiegelshohn, Sofya Vorotnikova, Samson Zhou
2018	—	`—`	Approximating Properties of Data Streams Samson Zhou
2018	A*	`conf`	Bandwidth-Hard Functions: Reductions and Lower Bounds. CCS Jeremiah Blocki, Ling Ren, Samson Zhou
2018	J	`jnl`	Bandwidth-Hard Functions: Reductions and Lower Bounds. IACR Cryptol. ePrint Arch. Jeremiah Blocki, Ling Ren, Samson Zhou
2018	A*	`conf`	Brief Announcement: Relaxed Locally Correctable Codes in Computationally Bounded Channels. ICALP Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou
2018	J	`jnl`	Data-Independent Memory Hard Functions: New Attacks and Stronger Constructions. IACR Cryptol. ePrint Arch. Jeremiah Blocki, Benjamin Harsha, Siteng Kang, Seunghoon Lee, Lu Xing, Samson Zhou
2018	J	`jnl`	Near Optimal Linear Algebra in the Online and Sliding Window Models CoRR Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou
2018	—	`conf`	Nearly Optimal Distinct Elements and Heavy Hitters on Sliding Windows. APPROX-RANDOM Vladimir Braverman, Elena Grigorescu, Harry Lang, David P. Woodruff, Samson Zhou
2018	J	`jnl`	Nearly Optimal Distinct Elements and Heavy Hitters on Sliding Windows. CoRR Vladimir Braverman, Elena Grigorescu, Harry Lang, David P. Woodruff, Samson Zhou
2018	—	`conf`	On the Computational Complexity of Minimal Cumulative Cost Graph Pebbling. Financial Cryptography Jeremiah Blocki, Samson Zhou
2018	A*	`conf`	On the Economics of Offline Password Cracking. IEEE Symposium on Security and Privacy Jeremiah Blocki, Benjamin Harsha, Samson Zhou
2018	Misc	`conf`	Periodicity in Data Streams with Wildcards. CSR Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou
2018	J	`jnl`	Periodicity in Data Streams with Wildcards. CoRR Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou
2018	J	`jnl`	Relaxed Locally Correctable Codes in Computationally Bounded Channels. CoRR Jeremiah Blocki, Venkata Gandikota, Elena Grigorescu, Samson Zhou
2017	J	`jnl`	Longest Alignment with Edits in Data Streams. CoRR Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou
2017	—	`conf`	Longest alignment with edits in data streams. Allerton Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou
2017	J	`jnl`	Nearly Optimal Sparse Group Testing. CoRR Venkata Gandikota, Elena Grigorescu, Sidharth Jaggi, Samson Zhou
2017	—	`conf`	On the Depth-Robustness and Cumulative Pebbling Cost of Argon2i. TCC (1) Jeremiah Blocki, Samson Zhou
2017	J	`jnl`	On the Depth-Robustness and Cumulative Pebbling Cost of Argon2i. IACR Cryptol. ePrint Arch. Jeremiah Blocki, Samson Zhou
2017	J	`jnl`	Optimal Parametric Search for Path and Tree Partitioning. CoRR Greg N. Frederickson, Samson Zhou
2017	—	`conf`	Streaming Periodicity with Mismatches. APPROX-RANDOM Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou
2017	J	`jnl`	Streaming Periodicity with Mismatches. CoRR Funda Ergün, Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou
2017	—	`conf`	Streaming for Aibohphobes: Longest Palindrome with Mismatches. FSTTCS Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou
2017	J	`jnl`	Streaming for Aibohphobes: Longest Palindrome with Mismatches. CoRR Elena Grigorescu, Erfan Sadeqi Azer, Samson Zhou
2016	J	`jnl`	Estimating Weighted Matchings in o(n) Space. CoRR Elena Grigorescu, Morteza Monemizadeh, Samson Zhou
2016	—	`conf`	Nearly optimal sparse group testing. Allerton Venkata Gandikota, Elena Grigorescu, Sidharth Jaggi, Samson Zhou
2016	J	`jnl`	On the Computational Complexity of Minimal Cumulative Cost Graph Pebbling. CoRR Jeremiah Blocki, Samson Zhou