| Multilevel thresholding for image segmentation through a fast statistical recursive algorithm S Arora, J Acharya, A Verma, PK Panigrahi Pattern Recognition Letters 29 (2), 119-125, 2008 | 379 | 2008 |
| Remember what you want to forget: Algorithms for machine unlearning A Sekhari, J Acharya, G Kamath, AT Suresh Advances in Neural Information Processing Systems 34, 18075-18086, 2021 | 226 | 2021 |
| Hadamard response: Estimating distributions privately, efficiently, and with little communication J Acharya, Z Sun, H Zhang The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 191 | 2019 |
| Optimal testing for properties of distributions J Acharya, C Daskalakis, G Kamath Advances in Neural Information Processing Systems 28, 2015 | 172 | 2015 |
| Inference under information constraints I: Lower bounds from chi-square contraction J Acharya, CL Canonne, H Tyagi IEEE Transactions on Information Theory 66 (12), 7835-7855, 2020 | 122 | 2020 |
| Sample-optimal density estimation in nearly-linear time J Acharya, I Diakonikolas, J Li, L Schmidt Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017 | 99 | 2017 |
| Near-optimal-sample estimators for spherical gaussian mixtures AT Suresh, A Orlitsky, J Acharya, A Jafarpour Advances in Neural Information Processing Systems 27, 2014 | 99 | 2014 |
| Differentially private testing of identity and closeness of discrete distributions J Acharya, Z Sun, H Zhang Advances in Neural Information Processing Systems 31, 2018 | 88 | 2018 |
| Estimating Renyi Entropy of Discrete Distributions J Acharya, A Orlitsky, AT Suresh, H Tyagi IEEE Transactions on Information Theory 63 (1), 38-56, 2017 | 88 | 2017 |
| A unified maximum likelihood approach for estimating symmetric properties of discrete distributions J Acharya, H Das, A Orlitsky, AT Suresh International Conference on Machine Learning, 11-21, 2017 | 87* | 2017 |
| The complexity of estimating Rényi entropy J Acharya, A Orlitsky, AT Suresh, H Tyagi Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete …, 2014 | 83 | 2014 |
| Test without trust: Optimal locally private distribution testing J Acharya, C Canonne, C Freitag, H Tyagi The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 69 | 2019 |
| Competitive closeness testing J Acharya, H Das, A Jafarpour, A Orlitsky, S Pan Proceedings of the 24th Annual Conference on Learning Theory, 47-68, 2011 | 65 | 2011 |
| Differentially private assouad, fano, and le cam J Acharya, Z Sun, H Zhang Algorithmic Learning Theory, 48-78, 2021 | 64 | 2021 |
| Inference under information constraints II: Communication constraints and shared randomness J Acharya, CL Canonne, H Tyagi IEEE Transactions on Information Theory 66 (12), 7856-7877, 2020 | 64 | 2020 |
| Communication complexity in locally private distribution estimation and heavy hitters J Acharya, Z Sun International Conference on Machine Learning, 51-60, 2019 | 64 | 2019 |
| String Reconstruction from Substring Compositions J Acharya, H Das, O Milenkovic, A Orlitsky, S Pan SIAM Journal on Discrete Mathematics 29 (3), 1340-1371, 2015 | 62* | 2015 |
| Fast and near-optimal algorithms for approximating distributions by histograms J Acharya, I Diakonikolas, C Hegde, JZ Li, L Schmidt Proceedings of the 34th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of …, 2015 | 61 | 2015 |
| Learning and testing causal models with interventions J Acharya, A Bhattacharyya, C Daskalakis, S Kandasamy Advances in Neural Information Processing Systems 31, 2018 | 60 | 2018 |
| Context aware local differential privacy J Acharya, K Bonawitz, P Kairouz, D Ramage, Z Sun International Conference on Machine Learning, 52-62, 2020 | 50 | 2020 |
Ziteng SunResearch Scientist at GoogleVerified email at cornell.edu
