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ORCIDDavid P. Woodruff
- > Home > Persons > David P. Woodruff
Publications
- 2024
[j42]Rajesh Jayaram
, David P. Woodruff, Samson Zhou:
Streaming Algorithms with Few State Changes. Proc. ACM Manag. Data 2(2): 82 (2024)- [c278]Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh:
HyperAttention: Long-context Attention in Near-Linear Time. ICLR 2024 - [i220]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Streaming Algorithms with Few State Changes. CoRR abs/2406.06821 (2024) - 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) - [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) - 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) - [c215]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Truly Perfect Samplers for Data Streams and Sliding Windows. PODS 2022: 29-40 - 2021
- [j32]Rajesh Jayaram, David P. Woodruff:
Perfect Lp Sampling in a Data Stream. SIAM J. Comput. 50(2): 382-439 (2021) - [j30]Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev:
A Framework for Adversarially Robust Streaming Algorithms. SIGMOD Rec. 50(1): 6-13 (2021) - [c198]Rajesh Jayaram, Alireza Samadian, David P. Woodruff, Peng Ye:
In-Database Regression in Input Sparsity Time. ICML 2021: 4797-4806 - [i149]Rajesh Jayaram, Alireza Samadian, David P. Woodruff, Peng Ye:
In-Database Regression in Input Sparsity Time. CoRR abs/2107.05672 (2021) - [i141]Rajesh Jayaram, David P. Woodruff, Samson Zhou:
Truly Perfect Samplers for Data Streams and Sliding Windows. CoRR abs/2108.12017 (2021) - 2020
- [c177]Rajesh Jayaram, David P. Woodruff, Qiuyi Zhang:
Span Recovery for Deep Neural Networks with Applications to Input Obfuscation. ICLR 2020 - [c169]Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev:
A Framework for Adversarially Robust Streaming Algorithms. PODS 2020: 63-80 - [i135]Rajesh Jayaram, David P. Woodruff, Qiuyi Zhang:
Span Recovery for Deep Neural Networks with Applications to Input Obfuscation. CoRR abs/2002.08202 (2020) - [i133]Omri Ben-Eliezer, Rajesh Jayaram, David P. Woodruff, Eylon Yogev:
A Framework for Adversarially Robust Streaming Algorithms. CoRR abs/2003.14265 (2020) - 2019
- [c159]Rajesh Jayaram, David P. Woodruff:
Towards Optimal Moment Estimation in Streaming and Distributed Models. APPROX-RANDOM 2019: 29:1-29:21 - [c158]Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff:
Learning Two Layer Rectified Neural Networks in Polynomial Time. COLT 2019: 195-268 - [c145]Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff:
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation. NeurIPS 2019: 4739-4750 - [c140]Rajesh Jayaram, Gokarna Sharma, Srikanta Tirthapura, David P. Woodruff:
Weighted Reservoir Sampling from Distributed Streams. PODS 2019: 218-235 - [i113]Rajesh Jayaram, Gokarna Sharma, Srikanta Tirthapura, David P. Woodruff:
Weighted Reservoir Sampling from Distributed Streams. CoRR abs/1904.04126 (2019) - [i103]Rajesh Jayaram, David P. Woodruff:
Towards Optimal Moment Estimation in Streaming and Distributed Models. CoRR abs/1907.05816 (2019) - [i99]Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff:
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation. CoRR abs/1909.13384 (2019) - 2018
- [c130]Rajesh Jayaram, David P. Woodruff:
Perfect Lp Sampling in a Data Stream. FOCS 2018: 544-555 - [c117]Rajesh Jayaram, David P. Woodruff:
Data Streams with Bounded Deletions. PODS 2018: 341-354 - [i89]Rajesh Jayaram, David P. Woodruff:
Data Streams with Bounded Deletions. CoRR abs/1803.08777 (2018) - [i78]Rajesh Jayaram, David P. Woodruff:
Perfect Lp Sampling in a Data Stream. CoRR abs/1808.05497 (2018) - [i73]Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff:
Learning Two Layer Rectified Neural Networks in Polynomial Time. CoRR abs/1811.01885 (2018)
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