Samson Zhou

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Vladimir BravermanAssociate Professor of Computer Science, Johns Hopkins UniversityVerified email at cs.jhu.edu
David WoodruffCarnegie Mellon UniversityVerified email at cs.cmu.edu
Jeremiah BlockiPurdue UniversityVerified email at purdue.edu
Elena GrigorescuPurdue UniversityVerified email at purdue.edu
Dan FeldmanUniversity of HaifaVerified email at csail.mit.edu
Grigory YaroslavtsevAssistant Professor, George Mason UniversityVerified email at grigory.us
Adiel StatmanElbit SystemsVerified email at elbitsystems.com
Petros DrineasProfessor, Computer Science Department, Purdue UniversityVerified email at purdue.edu
Ben MussayUniversity of HaifaVerified email at campus.haifa.ac.il
Erfan Sadeqi AzerSoftware Engineer at Google LLCVerified email at indiana.edu
Venkata GandikotaSyracuse UniversityVerified email at syr.edu
Margarita OsadchyComputer Science, University of HaifaVerified email at cs.haifa.ac.il
Dmitrii AvdiukhinIndiana UniversityVerified email at iu.edu
Seunghoon LeePh.D. student, Purdue UniversityVerified email at purdue.edu
Jalaj UpadhyayAssistant Professor, RutgersVerified email at apple.com
Cameron MuscoAssistant Professor, University of Massachusetts AmherstVerified email at cs.umass.edu
Christopher MuscoAssistant Professor, New York UniversityVerified email at nyu.edu
Morteza MonemizadehAssistant Professor at Eindhoven University of Technology, the NetherlandsVerified email at tue.nl
avinatan hassidimVerified email at biu.ac.il
Yossi MatiasGoogleVerified email at tau.ac.il

Samson Zhou

Carnegie Mellon University

Verified email at alum.mit.edu - Homepage

Theoretical Computer Science Machine Learning Sublinear Algorithms


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Efficient Coreset Constructions via Sensitivity Sampling V Braverman, D Feldman, H Lang, A Statman, S Zhou Asian Conference on Machine Learning, 948-963, 2021	119*	2021
On the Economics of Offline Password Cracking J Blocki, B Harsha, S Zhou IEEE Security and Privacy 2018, 2018	63	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	32*	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	30*	2020
Nearly Optimal Sparse Group Testing V Gandikota, E Grigorescu, S Jaggi, S Zhou Communication, Control, and Computing (Allerton), 2016 54th Annual Allerton …, 2016	30	2016
Nearly optimal distinct elements and heavy hitters on sliding windows V Braverman, E Grigorescu, H Lang, DP Woodruff, S Zhou APPROX 2018, 2018	24	2018
On the Depth-Robustness and Cumulative Pebbling Cost of Argon2i J Blocki, S Zhou Theory of Cryptography Conference (TCC) 2017, 445-465, 2017	23	2017
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	21	2021
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	18	2020
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	14	2019
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	13	2019
Bandwidth-hard functions: Reductions and lower bounds J Blocki, L Ren, S Zhou Conference on Computer and Communications Security (CCS) 2018, 1820-1836, 2018	13	2018
Relaxed locally correctable codes in computationally bounded channels J Blocki, V Gandikota, E Grigorescu, S Zhou ISIT 2019, ICALP 2018 (Brief Announcement), 2018	13	2018
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	12	2021
Streaming Periodicity with Mismatches F Ergün, E Grigorescu, ES Azer, S Zhou RANDOM 2017, 2017	12	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	11	2019
On the computational complexity of minimal cumulative cost graph pebbling J Blocki, S Zhou Financial Cryptography and Data Security (FC) 2018, 2016	10	2016
Non-Adaptive Adaptive Sampling on Turnstile Streams S Mahabadi, I Razenshteyn, DP Woodruff, S Zhou Symposium on Theory of Computing (STOC) 2020, 2020	9	2020
Periodicity in data streams with wildcards F Ergün, E Grigorescu, ES Azer, S Zhou Theory of Computing Systems 64 (1), 177-197, 2020	7	2020
Estimating Weighted Matchings in Space E Grigorescu, M Monemizadeh, S Zhou arXiv preprint arXiv:1604.07467, 2016	7	2016

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