Vladimir Braverman

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Nikita IvkinAmazon.comVerified email at amazon.com
Zaoxing LiuAssistant Professor of Computer Science, University of MarylandVerified email at cs.umd.edu
Rafail OstrovskyNorman E. Friedman Chair in Knowledge Sciences, Distinguished Prof. of CS & MATHVerified email at cs.ucla.edu
Jingfeng WuUniversity of California, BerkeleyVerified email at berkeley.edu
Samson ZhouTexas A&M UniversityVerified email at alum.mit.edu
Lin F. Yang (杨林)Assistant Professor, Department of Electrical and Computer Engineering @ UCLAVerified email at ee.ucla.edu
Xin JinPeking UniversityVerified email at pku.edu.cn
Vyas SekarTan Family Chair in Electrical and Computer Engineering, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Robert KrauthgamerWeizmann Institute of ScienceVerified email at weizmann.ac.il
Ion StoicaProfessor of Computer Science, UC BerkeleyVerified email at cs.berkeley.edu
Dan FeldmanUniversity of HaifaVerified email at csail.mit.edu
David WoodruffProfessor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Raman AroraDepartment of Computer Science, Johns Hopkins UniversityVerified email at cs.jhu.edu
Difan ZouThe University of Hong KongVerified email at cs.hku.hk
Quanquan GuAssociate Professor of Computer Science, UCLAVerified email at cs.ucla.edu
Enayat UllahResearch Scientist, MetaVerified email at jhu.edu
Michael A. Jacobs, Ph.D., DABRUT-Health and (Adjunct) The Johns Hopkins University School of Medicine and CS-Rice UniversityVerified email at mri.jhu.edu
Xuan WuJohns Hopkins UniversityVerified email at jh.edu
Zhuolong YuMicrosoftVerified email at microsoft.com
Sham M KakadeHarvard UniversityVerified email at seas.harvard.edu

Vladimir Braverman

Victor E. Cameron Professor of Computer Science, Rice University

Verified email at rice.edu - Homepage

Algorithms Machine Learning Computational Medicine Computer Networks


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One sketch to rule them all: Rethinking network flow monitoring with univmon Z Liu, A Manousis, G Vorsanger, V Sekar, V Braverman Proceedings of the 2016 ACM SIGCOMM Conference, 101-114, 2016	630	2016
Fetchsgd: Communication-efficient federated learning with sketching D Rothchild, A Panda, E Ullah, N Ivkin, I Stoica, V Braverman, J Gonzalez, ... International Conference on Machine Learning, 8253-8265, 2020	416	2020
Communication-efficient distributed SGD with sketching N Ivkin, D Rothchild, E Ullah, I Stoica, R Arora Advances in Neural Information Processing Systems 32, 2019	224	2019
Nitrosketch: Robust and general sketch-based monitoring in software switches Z Liu, R Ben-Basat, G Einziger, Y Kassner, V Braverman, R Friedman, ... Proceedings of the ACM Special Interest Group on Data Communication, 334-350, 2019	220	2019
Methods for effective processing of time series G Shaked, V Braverman, V Belyaev, G Rubin, M Sadetsky US Patent 9,047,349, 2015	207	2015
{DistCache}: Provable load balancing for {Large-Scale} storage systems with distributed caching Z Liu, Z Bai, Z Liu, X Li, C Kim, V Braverman, X Jin, I Stoica 17th USENIX Conference on File and Storage Technologies (FAST 19), 143-157, 2019	177	2019
New frameworks for offline and streaming coreset constructions V Braverman, D Feldman, H Lang, A Statman, S Zhou arXiv preprint arXiv:1612.00889, 2016	175	2016
Optimal sampling from sliding windows V Braverman, R Ostrovsky, C Zaniolo Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on …, 2009	165	2009
Jaqen: A {High-Performance}{Switch-Native} approach for detecting and mitigating volumetric {DDoS} attacks with programmable switches Z Liu, H Namkung, G Nikolaidis, J Lee, C Kim, X Jin, V Braverman, M Yu, ... 30th USENIX Security Symposium (USENIX Security 21), 3829-3846, 2021	159	2021
On the noisy gradient descent that generalizes as sgd J Wu, W Hu, H Xiong, J Huan, V Braverman, Z Zhu International Conference on Machine Learning, 10367-10376, 2020	111	2020
Streaming k-means on Well-Clusterable Data V Braverman, A Meyerson, R Ostrovsky, A Roytman, M Shindler, B Tagiku Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete …, 2011	106	2011
Smooth histograms for sliding windows V Braverman, R Ostrovsky 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07), 283-293, 2007	100	2007
{ASAP}: Fast, approximate graph pattern mining at scale AP Iyer, Z Liu, X Jin, S Venkataraman, V Braverman, I Stoica 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2018	96	2018
Zero-one frequency laws V Braverman, R Ostrovsky Proceedings of the forty-second ACM symposium on Theory of computing, 281-290, 2010	89	2010
Programmable packet scheduling with a single queue Z Yu, C Hu, J Wu, X Sun, V Braverman, M Chowdhury, Z Liu, X Jin Proceedings of the 2021 ACM SIGCOMM 2021 Conference, 179-193, 2021	88	2021
Netlock: Fast, centralized lock management using programmable switches Z Yu, Y Zhang, V Braverman, M Chowdhury, X Jin Proceedings of the Annual conference of the ACM Special Interest Group on …, 2020	84	2020
BPTree: An ℓ₂ Heavy Hitters Algorithm Using Constant Memory V Braverman, SR Chestnut, N Ivkin, J Nelson, Z Wang, DP Woodruff Proceedings of the 36th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of …, 2017	74	2017
How hard is counting triangles in the streaming model? V Braverman, R Ostrovsky, D Vilenchik Automata, Languages, and Programming: 40th International Colloquium, ICALP …, 2013	70	2013
Benign overfitting of constant-stepsize sgd for linear regression D Zou, J Wu, V Braverman, Q Gu, S Kakade Conference on Learning Theory, 4633-4635, 2021	68	2021
Data-independent neural pruning via coresets B Mussay, M Osadchy, V Braverman, S Zhou, D Feldman arXiv preprint arXiv:1907.04018, 2019	68	2019

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