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Shyam Narayanan
Shyam Narayanan
PhD Student, MIT
mit.edu의 이메일 확인됨 - 홈페이지
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Robustness implies privacy in statistical estimation
SB Hopkins, G Kamath, M Majid, S Narayanan
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 497-506, 2023
672023
Optimal terminal dimensionality reduction in Euclidean space
S Narayanan, J Nelson
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019
622019
Improved approximations for Euclidean k-means and k-median, via nested quasi-independent sets
V Cohen-Addad, H Esfandiari, V Mirrokni, S Narayanan
Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022
462022
Tight and robust private mean estimation with few users
S Narayanan, V Mirrokni, H Esfandiari
International Conference on Machine Learning, 16383-16412, 2022
36*2022
Learning-based support estimation in sublinear time
T Eden, P Indyk, S Narayanan, R Rubinfeld, S Silwal, T Wagner
arXiv preprint arXiv:2106.08396, 2021
312021
Triangle and four cycle counting with predictions in graph streams
JY Chen, T Eden, P Indyk, H Lin, S Narayanan, R Rubinfeld, S Silwal, ...
arXiv preprint arXiv:2203.09572, 2022
302022
Circular trace reconstruction
S Narayanan, M Ren
arXiv preprint arXiv:2009.01346, 2020
272020
Exponentially improving the complexity of simulating the Weisfeiler-Lehman test with graph neural networks
A Aamand, J Chen, P Indyk, S Narayanan, R Rubinfeld, N Schiefer, ...
Advances in Neural Information Processing Systems 35, 27333-27346, 2022
232022
Almost tight approximation algorithms for explainable clustering
H Esfandiari, V Mirrokni, S Narayanan
Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2022
222022
Private high-dimensional hypothesis testing
S Narayanan
Conference on Learning Theory, 3979-4027, 2022
202022
Improved algorithms for population recovery from the deletion channel
S Narayanan
Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms (SODA …, 2021
20*2021
Differentially private all-pairs shortest path distances: Improved algorithms and lower bounds
JY Chen, B Ghazi, R Kumar, P Manurangsi, S Narayanan, J Nelson, Y Xu
Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2023
19*2023
Better and simpler lower bounds for differentially private statistical estimation
S Narayanan
IEEE Transactions on Information Theory, 2024
132024
Krylov methods are (nearly) optimal for low-rank approximation
A Bakshi, S Narayanan
2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS …, 2023
132023
Query lower bounds for log-concave sampling
S Chewi, J de Dios Pont, J Li, C Lu, S Narayanan
Journal of the ACM 71 (4), 1-42, 2024
112024
Massively parallel algorithms for high-dimensional euclidean minimum spanning tree
R Jayaram, V Mirrokni, S Narayanan, P Zhong
Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2024
112024
Maximum mutational robustness in genotype–phenotype maps follows a self-similar blancmange-like curve
V Mohanty, SF Greenbury, T Sarkany, S Narayanan, K Dingle, SE Ahnert, ...
Journal of The Royal Society Interface 20 (204), 20230169, 2023
112023
Bounds on expected propagation time of probabilistic zero forcing
S Narayanan, A Sun
European Journal of Combinatorics 98, 103405, 2021
102021
Randomized dimensionality reduction for facility location and single-linkage clustering
S Narayanan, S Silwal, P Indyk, O Zamir
International Conference on Machine Learning, 7948-7957, 2021
102021
Near-Optimal Private and Scalable -Clustering
V Cohen-Addad, A Epasto, V Mirrokni, S Narayanan, P Zhong
Advances in Neural Information Processing Systems 35, 10462-10475, 2022
92022
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학술자료 1–20