Vladimir Braverman

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Rafail OstrovskyNorman E. Friedman Chair in Knowledge Sciences, Distinguished Prof. of CS & MATHVerified email at cs.ucla.edu
Zaoxing LiuAssistant Professor, Boston UniversityVerified email at bu.edu
Nikita IvkinAmazon.comVerified email at amazon.com
Lin F. Yang (杨林)Assistant Professor, Department of Electrical and Computer Engineering @ UCLAVerified email at ee.ucla.edu
Samson ZhouUC Berkeley and Rice UniversityVerified email at alum.mit.edu
Jingfeng WuJohns Hopkins UniversityVerified email at jhu.edu
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
Xin JinPeking UniversityVerified email at pku.edu.cn
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
Enayat UllahJohns Hopkins UniversityVerified email at jhu.edu
Xuan WuJohns Hopkins UniversityVerified email at jh.edu
Difan ZouThe University of Hong KongVerified email at cs.hku.hk
Quanquan GuAssociate Professor of Computer Science, UCLAVerified email at cs.ucla.edu
Daniel RothchildUC BerkeleyVerified email at berkeley.edu
Zhuolong YuJohns Hopkins UniversityVerified email at jh.edu
Antonis ManousisMeta PlatformsVerified email at cmu.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	481	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	209	2020
Methods for effective processing of time series G Shaked, V Braverman, V Belyaev, G Rubin, M Sadetsky US Patent 9,047,349, 2015	206	2015
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	156	2019
Optimal sampling from sliding windows V Braverman, R Ostrovsky, C Zaniolo Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on …, 2009	152	2009
Communication-efficient distributed SGD with sketching N Ivkin, D Rothchild, E Ullah, I Stoica, R Arora Advances in Neural Information Processing Systems 32, 2019	146	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	139	2016
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 FAST 19, 143-157, 2019	121	2019
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	98	2011
Smooth histograms for sliding windows V Braverman, R Ostrovsky 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07), 283-293, 2007	91	2007
Zero-one frequency laws V Braverman, R Ostrovsky Proceedings of the forty-second ACM symposium on Theory of computing, 281-290, 2010	78	2010
ASAP: Fast, Approximate Graph Pattern Mining at Scale. AP Iyer, Z Liu, X Jin, S Venkataraman, V Braverman, I Stoica OSDI 18, 745-761, 2018	70	2018
How hard is counting triangles in the streaming model? V Braverman, R Ostrovsky, D Vilenchik Automata, Languages, and Programming: 40th International Colloquium, ICALP …, 2013	66	2013
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	65	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	63	2017
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, ... USENIX Security Symposium, 3829-3846, 2021	59	2021
Beating countsketch for heavy hitters in insertion streams V Braverman, SR Chestnut, N Ivkin, DP Woodruff Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016	53	2016
Data-independent neural pruning via coresets B Mussay, M Osadchy, V Braverman, S Zhou, D Feldman arXiv preprint arXiv:1907.04018, 2019	50	2019
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	48	2020
Clustering high dimensional dynamic data streams V Braverman, G Frahling, H Lang, C Sohler, LF Yang International Conference on Machine Learning, 576-585, 2017	48	2017

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