| Efficient Coreset Constructions via Sensitivity Sampling V Braverman, D Feldman, H Lang, A Statman, S Zhou Asian Conference on Machine Learning (ACML) 2021, 948-963, 2021 | 183* | 2021 |
| On the Economics of Offline Password Cracking J Blocki, B Harsha, S Zhou IEEE Security and Privacy (Oakland S&P) 2018, 2018 | 108 | 2018 |
| Data-independent neural pruning via coresets B Mussay, M Osadchy, V Braverman, S Zhou, D Feldman International Conference on Learning Representations (ICLR) 2020, 2020 | 87* | 2020 |
| Near Optimal Linear Algebra in the Online and Sliding Window Models V Braverman, P Drineas, C Musco, C Musco, J Upadhyay, DP Woodruff, ... Symposium on Foundations of Computer Science (FOCS) 2020, 2020 | 65 | 2020 |
| Tight Bounds for Adversarially Robust Streams and Sliding Windows via Difference Estimators DP Woodruff, S Zhou Symposium on Foundations of Computer Science (FOCS) 2021, 2021 | 58 | 2021 |
| Nearly Optimal Sparse Group Testing V Gandikota, E Grigorescu, S Jaggi, S Zhou Communication, Control, and Computing (Allerton), 2016 54th Annual Allerton …, 2016 | 45 | 2016 |
| Adversarial Robustness of Streaming Algorithms through Importance Sampling V Braverman, A Hassidim, Y Matias, M Schain, S Silwal, S Zhou Advances in Neural Information Processing Systems 34, 2021 | 40 | 2021 |
| Learning-Augmented -means Clustering JC Ergun, Z Feng, S Silwal, DP Woodruff, S Zhou 10th International Conference on Learning Representations (ICLR) 2022, 2021 | 35 | 2021 |
| On the Depth-Robustness and Cumulative Pebbling Cost of Argon2i J Blocki, S Zhou Theory of Cryptography Conference (TCC) 2017, 445-465, 2017 | 32 | 2017 |
| Adversarially Robust Submodular Maximization under Knapsack Constraints D Avdiukhin, S Mitrović, G Yaroslavtsev, S Zhou Conference on Knowledge Discovery and Data Mining (KDD) 2019, 2019 | 31 | 2019 |
| Nearly optimal distinct elements and heavy hitters on sliding windows V Braverman, E Grigorescu, H Lang, DP Woodruff, S Zhou APPROX 2018, 2018 | 31 | 2018 |
| Memory-Efficient Performance Monitoring on Programmable Switches with Lean Algorithms Z Liu, S Zhou, O Rottenstreich, V Braverman, J Rexford Symposium on Algorithmic Principles of Computer Systems (APoCS) 2020, 2020 | 29 | 2020 |
| Data-Independent Memory Hard Functions: New Attacks and Stronger Constructions J Blocki, B Harsha, S Kang, S Lee, L Xing, S Zhou CRYPTO 2019, 2019 | 26 | 2019 |
| Memory bounds for the experts problem V Srinivas, DP Woodruff, Z Xu, S Zhou Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022 | 25 | 2022 |
| Non-Adaptive Adaptive Sampling on Turnstile Streams S Mahabadi, I Razenshteyn, DP Woodruff, S Zhou Symposium on Theory of Computing (STOC) 2020, 2020 | 25 | 2020 |
| “Bring Your Own Greedy”+ Max: Near-Optimal 1/2-Approximations for Submodular Knapsack G Yaroslavtsev, S Zhou, D Avdiukhin International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020 | 24 | 2020 |
| Bandwidth-hard functions: Reductions and lower bounds J Blocki, L Ren, S Zhou Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications …, 2018 | 24 | 2018 |
| Structural results on matching estimation with applications to streaming M Bury, E Grigorescu, A McGregor, M Monemizadeh, C Schwiegelshohn, ... Algorithmica 81 (1), 367-392, 2019 | 22 | 2019 |
| Relaxed locally correctable codes in computationally bounded channels J Blocki, V Gandikota, E Grigorescu, S Zhou ISIT 2019, ICALP 2018 (Brief Announcement), 2018 | 22 | 2018 |
| New coresets for projective clustering and applications M Tukan, X Wu, S Zhou, V Braverman, D Feldman International Conference on Artificial Intelligence and Statistics, 5391-5415, 2022 | 20 | 2022 |
David WoodruffProfessor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
