| 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 | 739 | 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 | 526 | 2020 |
| Kivi: A tuning-free asymmetric 2bit quantization for kv cache Z Liu, J Yuan, H Jin, S Zhong, Z Xu, V Braverman, B Chen, X Hu arXiv preprint arXiv:2402.02750, 2024 | 345 | 2024 |
| 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 | 278 | 2019 |
| 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 | 266 | 2021 |
| Communication-efficient distributed SGD with sketching N Ivkin, D Rothchild, E Ullah, I Stoica, R Arora Advances in Neural Information Processing Systems 32, 2019 | 266 | 2019 |
| {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 | 230 | 2019 |
| Methods for effective processing of time series G Shaked, V Braverman, V Belyaev, G Rubin, M Sadetsky US Patent 9,047,349, 2015 | 219 | 2015 |
| New frameworks for offline and streaming coreset constructions V Braverman, D Feldman, H Lang, A Statman, S Zhou arXiv preprint arXiv:1612.00889, 2016 | 186 | 2016 |
| Optimal sampling from sliding windows V Braverman, R Ostrovsky, C Zaniolo Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on …, 2009 | 181 | 2009 |
| 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 | 135 | 2020 |
| 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 | 133 | 2021 |
| 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 | 112 | 2011 |
| Smooth histograms for sliding windows V Braverman, R Ostrovsky 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07), 283-293, 2007 | 111 | 2007 |
| 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 | 109 | 2020 |
| How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression? J Wu, D Zou, Z Chen, V Braverman, Q Gu, PL Bartlett arXiv preprint arXiv:2310.08391, 2023 | 108 | 2023 |
| {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 | 107 | 2018 |
| 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 | 98 | 2021 |
| Zero-one frequency laws V Braverman, R Ostrovsky Proceedings of the forty-second ACM symposium on Theory of computing, 281-290, 2010 | 97 | 2010 |
| {SketchLib}: Enabling efficient sketch-based monitoring on programmable switches H Namkung, Z Liu, D Kim, V Sekar, P Steenkiste 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2022 | 80 | 2022 |
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