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Near-Linear Sample Complexity for Lp Polynomial Regression.
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou: Near-Linear Sample Complexity for Lp Polynomial Regression. CoRR abs/2211.06790 (2022)
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How to Make Your Approximation Algorithm Private: A Black-Box...
Jeremiah Blocki, Elena Grigorescu, Tamalika Mukherjee, Samson Zhou: How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation...
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Learning-Augmented Algorithms for Online Linear and Semidefinite Programming.
Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou: Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. CoRR abs/2209.10614 (2022)
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Adaptive Sketches for Robust Regression with Importance Sampling.
Sepideh Mahabadi, David P. Woodruff, Samson Zhou: Adaptive Sketches for Robust Regression with Importance Sampling. CoRR abs/2207.07822 (2022)
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Hardness and Algorithms for Robust and Sparse Optimization.
Eric Price, Sandeep Silwal, Samson Zhou: Hardness and Algorithms for Robust and Sparse Optimization. CoRR abs/2206.14354 (2022)
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Memory Bounds for the Experts Problem.
Vaidehi Srinivas, David P. Woodruff, Ziyu Xu, Samson Zhou: Memory Bounds for the Experts Problem. CoRR abs/2204.09837 (2022)
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The White-Box Adversarial Data Stream Model.
Miklós Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou: The White-Box Adversarial Data Stream Model. CoRR abs/2204.09136 (2022)
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Fast Regression for Structured Inputs.
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou: Fast Regression for Structured Inputs. CoRR abs/2203.07557 (2022)
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New Coresets for Projective Clustering and Applications.
Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman: New Coresets for Projective Clustering and Applications. CoRR abs/2203.04370 (2022)
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Memory bounds for the experts problem.
Vaidehi Srinivas, David P. Woodruff, Ziyu Xu, Samson Zhou: Memory bounds for the experts problem. STOC 2022: 1158-1171
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A Fast, Provably Accurate Approximation Algorithm for Sparse Principal...
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...
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Truly Perfect Samplers for Data Streams and Sliding Windows.
Rajesh Jayaram, David P. Woodruff, Samson Zhou: Truly Perfect Samplers for Data Streams and Sliding Windows. PODS 2022: 29-40
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The White-Box Adversarial Data Stream Model.
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: 15-27
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Learning-Augmented Algorithms for Online Linear and Semidefinite Programming.
Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou: Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. NeurIPS 2022
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Noisy Boolean Hidden Matching with Applications.
Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou: Noisy Boolean Hidden Matching with Applications. ITCS 2022: 91:1-91:19
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Hardness and Algorithms for Robust and Sparse Optimization.
Eric Price, Sandeep Silwal, Samson Zhou: Hardness and Algorithms for Robust and Sparse Optimization. ICML 2022: 17926-17944
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Fast Regression for Structured Inputs.
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou: Fast Regression for Structured Inputs. ICLR 2022
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Learning-Augmented $k$-means Clustering.
Jon C. Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou: Learning-Augmented $k$-means Clustering. ICLR 2022
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Adaptive Sketches for Robust Regression with Importance Sampling.
Sepideh Mahabadi, David P. Woodruff, Samson Zhou: Adaptive Sketches for Robust Regression with Importance Sampling. APPROX/RANDOM 2022: 31:1-31:21
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New Coresets for Projective Clustering and Applications.
Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman: New Coresets for Projective Clustering and Applications. AISTATS 2022: 5391-5415
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Data-Independent Structured Pruning of Neural Networks via Coresets.
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):...
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On Differential Privacy and Adaptive Data Analysis with Bounded Space.
Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou: On Differential Privacy and Adaptive Data Analysis with Bounded Space. IACR Cryptol. ePrint Arch. 2023: 171 (2023)
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Near-Optimal k-Clustering in the Sliding Window Model.
David P. Woodruff, Peilin Zhong, Samson Zhou: Near-Optimal k-Clustering in the Sliding Window Model. CoRR abs/2311.00642 (2023)
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Streaming Euclidean k-median and k-means with o(log n) Space.
Vincent Cohen-Addad, David P. Woodruff, Samson Zhou: Streaming Euclidean k-median and k-means with o(log n) Space. CoRR abs/2310.02882 (2023)
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Differentially Private Aggregation via Imperfect Shuffling.
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou: Differentially Private Aggregation via Imperfect Shuffling. CoRR abs/2308.14733 (2023)
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Private Data Stream Analysis for Universal Symmetric Norm Estimation.
Vladimir Braverman, Joel Manning, Zhiwei Steven Wu, Samson Zhou: Private Data Stream Analysis for Universal Symmetric Norm Estimation. CoRR abs/2307.04249 (2023)
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Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization.
Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou: Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. CoRR abs/2306.01869 (2023)
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Robust Algorithms on Adaptive Inputs from Bounded Adversaries.
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou: Robust Algorithms on Adaptive Inputs from Bounded Adversaries. CoRR abs/2304.07413 (2023)
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Provable Data Subset Selection For Efficient Neural Network Training.
Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman: Provable Data Subset Selection For Efficient Neural Network Training. CoRR abs/2303.05151 (2023)
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Streaming Algorithms for Learning with Experts: Deterministic Versus Robust.
David P. Woodruff, Fred Zhang, Samson Zhou: Streaming Algorithms for Learning with Experts: Deterministic Versus Robust. CoRR abs/2303.01709 (2023)
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Selective experience replay compression using coresets for lifelong deep...
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....
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Differentially Private L2-Heavy Hitters in the Sliding Window Model.
Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou: Differentially Private L2-Heavy Hitters in the Sliding Window Model. CoRR abs/2302.11081 (2023)
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On Differential Privacy and Adaptive Data Analysis with Bounded Space.
Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou: On Differential Privacy and Adaptive Data Analysis with Bounded Space. CoRR abs/2302.05707 (2023)
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Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time.
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou: Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA 2023: 4026-4049
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Near-Linear Sample Complexity for Lp Polynomial Regression.
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou: Near-Linear Sample Complexity for Lp Polynomial Regression. SODA 2023: 3959-4025
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Selective experience replay compression using coresets for lifelong deep...
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...
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Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization.
Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou: Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. ICML 2023: 34952-34977
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Provable Data Subset Selection For Efficient Neural Networks Training.
Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman: Provable Data Subset Selection For Efficient Neural Networks Training. ICML 2023: 34533-34555
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Robust Algorithms on Adaptive Inputs from Bounded Adversaries.
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou: Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR 2023
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Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model.
Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee, Samson Zhou: Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model. ICLR 2023
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Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation.
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou: Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR 2023
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Streaming Euclidean k-median and k-means with o(log n) Space.
Vincent Cohen-Addad, David P. Woodruff, Samson Zhou: Streaming Euclidean k-median and k-means with o(log n) Space. FOCS 2023: 883-908
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On Differential Privacy and Adaptive Data Analysis with Bounded Space.
Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou: On Differential Privacy and Adaptive Data Analysis with Bounded Space. EUROCRYPT (3) 2023: 35-65
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Differentially Private Aggregation via Imperfect Shuffling.
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Jelani Nelson, Samson Zhou: Differentially Private Aggregation via Imperfect Shuffling. ITC 2023: 17:1-17:22
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How to Make Your Approximation Algorithm Private: A Black-Box...
Jeremiah Blocki, Elena Grigorescu, Tamalika Mukherjee, Samson Zhou: How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation...
View ArticleClik here to view.
Private Data Stream Analysis for Universal Symmetric Norm Estimation.
Vladimir Braverman, Joel Manning, Zhiwei Steven Wu, Samson Zhou: Private Data Stream Analysis for Universal Symmetric Norm Estimation. APPROX/RANDOM 2023: 45:1-45:24
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Near-Optimal k-Clustering in the Sliding Window Model.
David P. Woodruff, Peilin Zhong, Samson Zhou: Near-Optimal k-Clustering in the Sliding Window Model. NeurIPS 2023
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Learning-Augmented Skip Lists.
Chunkai Fu, Jung Hoon Seo, Samson Zhou: Learning-Augmented Skip Lists. CoRR abs/2402.10457 (2024)
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On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds.
David P. Woodruff, Fred Zhang, Samson Zhou: On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds. NeurIPS 2023
View ArticleBandwidth-Hard Functions: Reductions and Lower Bounds.
Jeremiah Blocki, Peiyuan Liu, Ling Ren, Samson Zhou: Bandwidth-Hard Functions: Reductions and Lower Bounds. J. Cryptol. 37(2): 16 (2024)
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