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ORCIDDavid P. Woodruff
Person information
- affiliation: Carnegie Mellon University, PA, USA
- affiliation (former): IBM Almaden Research Center, San Jose, CA, USA
- affiliation (PhD 2007): Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
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2020 – today
- 2024
[j42]Rajesh Jayaram
, David P. Woodruff, Samson Zhou:
Streaming Algorithms with Few State Changes. Proc. ACM Manag. Data 2(2): 82 (2024)- [j41]Yu Cheng, Max Li, Honghao Lin, Zi-Yi Tai, David P. Woodruff, Jason Zhang:
Tight Lower Bounds for Directed Cut Sparsification and Distributed Min-Cut. Proc. ACM Manag. Data 2(2): 85 (2024) - [c276]Praneeth Kacham, David P. Woodruff:
Faster Algorithms for Schatten-p Low Rank Approximation. APPROX/RANDOM 2024: 55:1-55:19 - [c275]Aashiq Muhamed, Oscar Li, David P. Woodruff, Mona Diab, Virginia Smith:
GRASS: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients. EMNLP 2024: 14978-15003 - [c274]Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou:
A Strong Separation for Adversarially Robust ℓ0 Estimation for Linear Sketches. FOCS 2024: 2318-2343 - [c273]Yi Li, Honghao Lin, David P. Woodruff:
Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms. ICLR 2024 - [c272]Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh:
HyperAttention: Long-context Attention in Near-Linear Time. ICLR 2024 - [c271]Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David P. Woodruff, Elad Hazan:
Adaptive Regret for Bandits Made Possible: Two Queries Suffice. ICLR 2024 - [c270]Kyriakos Axiotis, Vincent Cohen-Addad, Monika Henzinger, Sammy Jerome, Vahab Mirrokni, David Saulpic, David P. Woodruff, Michael Wunder:
Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond. ICML 2024 - [c269]Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong:
High-Dimensional Geometric Streaming for Nearly Low Rank Data. ICML 2024 - [c268]Ying Feng, Aayush Jain, David P. Woodruff:
Fast White-Box Adversarial Streaming Without a Random Oracle. ICML 2024 - [c267]Milind Prabhu, David P. Woodruff:
Learning Multiple Secrets in Mastermind. ICML 2024 - [c266]William J. Swartworth, David P. Woodruff:
Fast Sampling-Based Sketches for Tensors. ICML 2024 - [c265]David P. Woodruff, Taisuke Yasuda:
Reweighted Solutions for Weighted Low Rank Approximation. ICML 2024 - [c264]David P. Woodruff, Taisuke Yasuda:
Coresets for Multiple ℓp Regression. ICML 2024 - [c263]Rajarshi Bhattacharjee, Gregory Dexter, Cameron Musco, Archan Ray, Sushant Sachdeva, David P. Woodruff:
Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra. ITCS 2024: 13:1-13:24 - [c262]Justin Y. Chen, Piotr Indyk, David P. Woodruff:
Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions. ITCS 2024: 32:1-32:22 - [c261]Arvind V. Mahankali, David P. Woodruff, Ziyu Zhang:
Near-Linear Time and Fixed-Parameter Tractable Algorithms for Tensor Decompositions. ITCS 2024: 79:1-79:23 - [c260]David P. Woodruff:
Approximation Algorithms on Matrices - With Some Database Applications! PODS Companion 2024: 5-6 - [c259]Mehrdad Ghadiri, Yin Tat Lee, Swati Padmanabhan, William Swartworth, David P. Woodruff, Guanghao Ye:
Improving the Bit Complexity of Communication for Distributed Convex Optimization. STOC 2024: 1130-1140 - [c258]Mark Braverman, Sumegha Garg, Qian Li, Shuo Wang, David P. Woodruff, Jiapeng Zhang:
A New Information Complexity Measure for Multi-pass Streaming with Applications. STOC 2024: 1781-1792 - [c257]Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong:
Optimal Communication Bounds for Classic Functions in the Coordinator Model and Beyond. STOC 2024: 1911-1922 - [e2]David P. Woodruff:
Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, SODA 2024, Alexandria, VA, USA, January 7-10, 2024. SIAM 2024, ISBN 978-1-61197-791-2 [contents] - [i230]Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David P. Woodruff, Elad Hazan:
Adaptive Regret for Bandits Made Possible: Two Queries Suffice. CoRR abs/2401.09278 (2024) - [i229]Kyriakos Axiotis, Vincent Cohen-Addad, Monika Henzinger, Sammy Jerome, Vahab Mirrokni, David Saulpic, David P. Woodruff, Michael Wunder:
Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond. CoRR abs/2402.17327 (2024) - [i228]Mehrdad Ghadiri, Yin Tat Lee, Swati Padmanabhan, William Swartworth, David P. Woodruff, Guanghao Ye:
Improving the Bit Complexity of Communication for Distributed Convex Optimization. CoRR abs/2403.19146 (2024) - [i227]Mark Braverman, Sumegha Garg, Qian Li, Shuo Wang, David P. Woodruff, Jiapeng Zhang:
A New Information Complexity Measure for Multi-pass Streaming with Applications. CoRR abs/2403.20283 (2024) - [i226]Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong:
Optimal Communication for Classic Functions in the Coordinator Model and Beyond. CoRR abs/2403.20307 (2024) - [i225]David P. Woodruff, Taisuke Yasuda:
Reweighted Solutions for Weighted Low Rank Approximation. CoRR abs/2406.02431 (2024) - [i224]David P. Woodruff, Taisuke Yasuda:
Coresets for Multiple ℓp Regression. CoRR abs/2406.02432 (2024) - [i223]Hossein Esfandiari, Vahab Mirrokni, Praneeth Kacham, David P. Woodruff, Peilin Zhong:
High-Dimensional Geometric Streaming for Nearly Low Rank Data. CoRR abs/2406.02910 (2024) - [i222]William Swartworth, David P. Woodruff:
Fast Sampling Based Sketches for Tensors. CoRR abs/2406.06735 (2024) - [i221]Ying Feng, Aayush Jain, David P. Woodruff:
Fast White-Box Adversarial Streaming Without a Random Oracle. CoRR abs/2406.06808 (2024) - [i220]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Streaming Algorithms with Few State Changes. CoRR abs/2406.06821 (2024) - [i219]Yu Cheng, Max Li, Honghao Lin, Zi-Yi Tai, David P. Woodruff, Jason Zhang:
Tight Lower Bounds for Directed Cut Sparsification and Distributed Min-Cut. CoRR abs/2406.13231 (2024) - [i218]Aashiq Muhamed, Oscar Li, David P. Woodruff, Mona Diab, Virginia Smith:
Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients. CoRR abs/2406.17660 (2024) - [i217]David P. Woodruff, Taisuke Yasuda:
Nearly Linear Sparsification of ℓp Subspace Approximation. CoRR abs/2407.03262 (2024) - [i216]Praneeth Kacham, David P. Woodruff:
Faster Algorithms for Schatten-p Low Rank Approximation. CoRR abs/2407.11959 (2024) - [i215]Yi Li, Honghao Lin, David P. Woodruff:
Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms. CoRR abs/2408.08494 (2024) - [i214]Milind Prabhu, David P. Woodruff:
Learning Multiple Secrets in Mastermind. CoRR abs/2409.06453 (2024) - [i213]Elena Gribelyuk, Honghao Lin, David P. Woodruff, Huacheng Yu, Samson Zhou:
A Strong Separation for Adversarially Robust ℓ0 Estimation for Linear Sketches. CoRR abs/2409.16153 (2024) - [i212]Ravindran Kannan, Chiranjib Bhattacharyya, Praneeth Kacham, David P. Woodruff:
LevAttention: Time, Space, and Streaming Efficient Algorithm for Heavy Attentions. CoRR abs/2410.05462 (2024) - [i211]William Swartworth, David P. Woodruff:
Tight Sampling Bounds for Eigenvalue Approximation. CoRR abs/2411.03227 (2024) - [i210]Hamed Shirzad, Honghao Lin, Ameya Velingker, Balaji Venkatachalam, David P. Woodruff, Danica J. Sutherland:
A Theory for Compressibility of Graph Transformers for Transductive Learning. CoRR abs/2411.13028 (2024) - [i209]Hamed Shirzad, Honghao Lin, Balaji Venkatachalam, Ameya Velingker, David P. Woodruff, Danica J. Sutherland:
Even Sparser Graph Transformers. CoRR abs/2411.16278 (2024) - [i208]Matthew Ding, Alexandro Garces, Jason Li, Honghao Lin, Jelani Nelson, Vihan Shah, David P. Woodruff:
Space Complexity of Minimum Cut Problems in Single-Pass Streams. CoRR abs/2412.01143 (2024) - [i207]David P. Woodruff, Samson Zhou:
Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters. CoRR abs/2412.05807 (2024) - [i206]Zhao Song, Ali Vakilian, David P. Woodruff, Samson Zhou:
On Socially Fair Low-Rank Approximation and Column Subset Selection. CoRR abs/2412.06063 (2024) - [i205]Praneeth Kacham, David P. Woodruff:
Approximating the Top Eigenvector in Random Order Streams. CoRR abs/2412.11963 (2024) - 2023
- [j40]David P. Woodruff:
Technical Perspective: Tapping the Link between Algorithmic Model Counting and Streaming. Commun. ACM 66(9): 94 (2023) - [j39]Rajesh Jayaram, David P. Woodruff:
Towards Optimal Moment Estimation in Streaming and Distributed Models. ACM Trans. Algorithms 19(3): 27:1-27:35 (2023) - [j38]Zhuangfei Hu, Xinda Li, David P. Woodruff, Hongyang Zhang, Shufan Zhang:
Recovery From Non-Decomposable Distance Oracles. IEEE Trans. Inf. Theory 69(10): 6443-6469 (2023) - [j37]Elbert Du, Michael Mitzenmacher, David P. Woodruff, Guang Yang:
Separating k-Player from t-Player One-Way Communication, with Applications to Data Streams. Theory Comput. 19: 1-44 (2023) - [c256]Tung Mai, Alexander Munteanu, Cameron Musco, Anup Rao, Chris Schwiegelshohn, David P. Woodruff:
Optimal Sketching Bounds for Sparse Linear Regression. AISTATS 2023: 11288-11316 - [c255]Yi Li, Honghao Lin, David P. Woodruff:
ℓp-Regression in the Arbitrary Partition Model of Communication. COLT 2023: 4902-4928 - [c254]Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou:
On Differential Privacy and Adaptive Data Analysis with Bounded Space. EUROCRYPT (3) 2023: 35-65 - [c253]Vincent Cohen-Addad, David P. Woodruff, Samson Zhou:
Streaming Euclidean k-median and k-means with o(log n) Space. FOCS 2023: 883-908 - [c252]Praneeth Kacham, Rasmus Pagh, Mikkel Thorup, David P. Woodruff:
Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming. FOCS 2023: 1515-1550 - [c251]Yi Li, Honghao Lin, Simin Liu, Ali Vakilian, David P. Woodruff:
Learning the Positions in CountSketch. ICLR 2023 - [c250]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou:
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR 2023 - [c249]Alexander Munteanu, Simon Omlor, David P. Woodruff:
Almost Linear Constant-Factor Sketching for $\ell_1$ and Logistic Regression. ICLR 2023 - [c248]Ying Feng, David P. Woodruff:
Improved Algorithms for White-Box Adversarial Streams. ICML 2023: 9962-9975 - [c247]Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou:
Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. ICML 2023: 34952-34977 - [c246]David P. Woodruff, Taisuke Yasuda:
Sharper Bounds for ℓp Sensitivity Sampling. ICML 2023: 37238-37272 - [c245]Zhuangfei Hu, Xinda Li, David P. Woodruff, Hongyang Zhang, Shufan Zhang:
Recovery from Non-Decomposable Distance Oracles. ITCS 2023: 73:1-73:22 - [c244]Gregory Dexter, Petros Drineas, David P. Woodruff, Taisuke Yasuda:
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming. NeurIPS 2023 - [c243]Praneeth Kacham, David P. Woodruff:
Lower Bounds on Adaptive Sensing for Matrix Recovery. NeurIPS 2023 - [c242]Swati Padmanabhan, David P. Woodruff, Richard Zhang:
Computing Approximate 𝓁p Sensitivities. NeurIPS 2023 - [c241]Tamás Sarlós, Xingyou Song, David P. Woodruff, Richard Zhang:
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. NeurIPS 2023 - [c240]David P. Woodruff, Peilin Zhong, Samson Zhou:
Near-Optimal k-Clustering in the Sliding Window Model. NeurIPS 2023 - [c239]David P. Woodruff, Fred Zhang, Samson Zhou:
On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds. NeurIPS 2023 - [c238]Yi Li, Honghao Lin, David P. Woodruff:
The ℓp-Subspace Sketch Problem in Small Dimensions with Applications to Support Vector Machines. SODA 2023: 850-877 - [c237]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Near-Linear Sample Complexity for Lp Polynomial Regression. SODA 2023: 3959-4025 - [c236]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou:
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA 2023: 4026-4049 - [c235]David P. Woodruff, Taisuke Yasuda:
Online Lewis Weight Sampling. SODA 2023: 4622-4666 - [c234]William Swartworth, David P. Woodruff:
Optimal Eigenvalue Approximation via Sketching. STOC 2023: 145-155 - [c233]David P. Woodruff, Taisuke Yasuda:
New Subset Selection Algorithms for Low Rank Approximation: Offline and Online. STOC 2023: 1802-1813 - [i204]Itai Dinur, Uri Stemmer, David P. Woodruff, Samson Zhou:
On Differential Privacy and Adaptive Data Analysis with Bounded Space. CoRR abs/2302.05707 (2023) - [i203]David P. Woodruff, Fred Zhang, Samson Zhou:
Streaming Algorithms for Learning with Experts: Deterministic Versus Robust. CoRR abs/2303.01709 (2023) - [i202]Alexander Munteanu, Simon Omlor, David P. Woodruff:
Almost Linear Constant-Factor Sketching for 𝓁1 and Logistic Regression. CoRR abs/2304.00051 (2023) - [i201]Tung Mai, Alexander Munteanu, Cameron Musco, Anup B. Rao, Chris Schwiegelshohn, David P. Woodruff:
Optimal Sketching Bounds for Sparse Linear Regression. CoRR abs/2304.02261 (2023) - [i200]Praneeth Kacham, Rasmus Pagh, Mikkel Thorup, David P. Woodruff:
Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming. CoRR abs/2304.06853 (2023) - [i199]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) - [i198]David P. Woodruff, Taisuke Yasuda:
New Subset Selection Algorithms for Low Rank Approximation: Offline and Online. CoRR abs/2304.09217 (2023) - [i197]William Swartworth, David P. Woodruff:
Optimal Eigenvalue Approximation via Sketching. CoRR abs/2304.09281 (2023) - [i196]Rajarshi Bhattacharjee, Gregory Dexter, Cameron Musco, Archan Ray, Sushant Sachdeva, David P. Woodruff:
Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra. CoRR abs/2305.05826 (2023) - [i195]David P. Woodruff, Taisuke Yasuda:
Sharper Bounds for 𝓁p Sensitivity Sampling. CoRR abs/2306.00732 (2023) - [i194]Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou:
Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization. CoRR abs/2306.01869 (2023) - [i193]Yi Li, Honghao Lin, Simin Liu, Ali Vakilian, David P. Woodruff:
Learning the Positions in CountSketch. CoRR abs/2306.06611 (2023) - [i192]Ying Feng, David P. Woodruff:
Improved Algorithms for White-Box Adversarial Streams. CoRR abs/2307.03529 (2023) - [i191]Yi Li, Honghao Lin, David P. Woodruff:
𝓁p-Regression in the Arbitrary Partition Model of Communication. CoRR abs/2307.05117 (2023) - [i190]Hai Pham, Young Jin Kim, Subhabrata Mukherjee, David P. Woodruff, Barnabás Póczos, Hany Hassan Awadalla:
Task-Based MoE for Multitask Multilingual Machine Translation. CoRR abs/2308.15772 (2023) - [i189]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) - [i188]Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh:
HyperAttention: Long-context Attention in Near-Linear Time. CoRR abs/2310.05869 (2023) - [i187]Gregory Dexter, Petros Drineas, David P. Woodruff, Taisuke Yasuda:
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming. CoRR abs/2310.19068 (2023) - [i186]David P. Woodruff, Peilin Zhong, Samson Zhou:
Near-Optimal k-Clustering in the Sliding Window Model. CoRR abs/2311.00642 (2023) - [i185]Tamás Sarlós, Xingyou Song, David P. Woodruff, Qiuyi Zhang:
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products. CoRR abs/2311.01960 (2023) - [i184]Swati Padmanabhan, David P. Woodruff, Qiuyi (Richard) Zhang:
Computing Approximate 𝓁p Sensitivities. CoRR abs/2311.04158 (2023) - [i183]Praneeth Kacham, David P. Woodruff:
Lower Bounds on Adaptive Sensing for Matrix Recovery. CoRR abs/2311.17281 (2023) - [i182]Justin Y. Chen, Piotr Indyk, David P. Woodruff:
Space-Optimal Profile Estimation in Data Streams with Applications to Symmetric Functions. CoRR abs/2311.17868 (2023) - [i181]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) - 2022
- [j36]Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev:
A Framework for Adversarially Robust Streaming Algorithms. J. ACM 69(2): 17:1-17:33 (2022) - [j35]David P. Woodruff:
Technical Perspective: Model Counting Meets Distinct Elements in a Data Stream. SIGMOD Rec. 51(1): 86 (2022) - [j34]Ruosong Wang, David P. Woodruff:
Tight Bounds for ℓ1 Oblivious Subspace Embeddings. ACM Trans. Algorithms 18(1): 8:1-8:32 (2022) - [c232]Yi Li, Honghao Lin, David P. Woodruff, Yuheng Zhang:
Streaming Algorithms with Large Approximation Factors. APPROX/RANDOM 2022: 13:1-13:23 - [c231]Sepideh Mahabadi, David P. Woodruff, Samson Zhou:
Adaptive Sketches for Robust Regression with Importance Sampling. APPROX/RANDOM 2022: 31:1-31:21 - [c230]Deanna Needell, William Swartworth, David P. Woodruff:
Testing Positive Semidefiniteness Using Linear Measurements. FOCS 2022: 87-97 - [c229]David P. Woodruff, Taisuke Yasuda:
High-Dimensional Geometric Streaming in Polynomial Space. FOCS 2022: 732-743 - [c228]Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda:
Active Linear Regression for ℓp Norms and Beyond. FOCS 2022: 744-753 - [c227]Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang:
Triangle and Four Cycle Counting with Predictions in Graph Streams. ICLR 2022 - [c226]Jon C. Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou:
Learning-Augmented $k$-means Clustering. ICLR 2022 - [c225]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Fast Regression for Structured Inputs. ICLR 2022 - [c224]Nadiia Chepurko, Kenneth L. Clarkson, Lior Horesh, Honghao Lin, David P. Woodruff:
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra. ICML 2022: 3879-3900 - [c223]Praneeth Kacham, David P. Woodruff:
Sketching Algorithms and Lower Bounds for Ridge Regression. ICML 2022: 10539-10556 - [c222]Honghao Lin, Tian Luo, David P. Woodruff:
Learning Augmented Binary Search Trees. ICML 2022: 13431-13440 - [c221]Alexander Munteanu, Simon Omlor, Zhao Song, David P. Woodruff:
Bounding the Width of Neural Networks via Coupled Initialization A Worst Case Analysis. ICML 2022: 16083-16122 - [c220]David P. Woodruff, Amir Zandieh:
Leverage Score Sampling for Tensor Product Matrices in Input Sparsity Time. ICML 2022: 23933-23964 - [c219]Anubhav Baweja, Justin Jia, David P. Woodruff:
An Efficient Semi-Streaming PTAS for Tournament Feedback Arc Set with Few Passes. ITCS 2022: 16:1-16:23 - [c218]Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou:
Noisy Boolean Hidden Matching with Applications. ITCS 2022: 91:1-91:19 - [c217]David P. Woodruff, Fred Zhang, Richard Zhang:
Optimal Query Complexities for Dynamic Trace Estimation. NeurIPS 2022 - [c216]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 - [c215]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Truly Perfect Samplers for Data Streams and Sliding Windows. PODS 2022: 29-40 - [c214]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: 86-106 - [c213]Piotr Indyk, Shyam Narayanan, David P. Woodruff:
Frequency Estimation with One-Sided Error. SODA 2022: 695-707 - [c212]