| Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... Foundations and trends® in machine learning 14 (1–2), 1-210, 2021 | 7235 | 2021 |
| Can you really backdoor federated learning? Z Sun, P Kairouz, AT Suresh, HB McMahan arXiv preprint arXiv:1911.07963, 2019 | 728 | 2019 |
| 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 | 206* | 2019 |
| Learning with user-level privacy D Levy, Z Sun, K Amin, S Kale, A Kulesza, M Mohri, AT Suresh Advances in Neural Information Processing Systems 34, 12466-12479, 2021 | 103 | 2021 |
| Differentially private testing of identity and closeness of discrete distributions J Acharya, Z Sun, H Zhang Advances in Neural Information Processing Systems 31, 2018 | 97 | 2018 |
| Spectr: Fast speculative decoding via optimal transport Z Sun, AT Suresh, JH Ro, A Beirami, H Jain, F Yu Advances in Neural Information Processing Systems 36, 30222-30242, 2023 | 80 | 2023 |
| Differentially private assouad, fano, and le cam J Acharya, Z Sun, H Zhang Algorithmic Learning Theory, 48-78, 2021 | 79 | 2021 |
| Communication complexity in locally private distribution estimation and heavy hitters J Acharya, Z Sun International Conference on Machine Learning, 51-60, 2019 | 68 | 2019 |
| Interactive inference under information constraints J Acharya, CL Canonne, Y Liu, Z Sun, H Tyagi IEEE Transactions on Information Theory 68 (1), 502-516, 2021 | 55 | 2021 |
| Inference under information constraints III: Local privacy constraints J Acharya, CL Canonne, C Freitag, Z Sun, H Tyagi IEEE Journal on Selected Areas in Information Theory 2 (1), 253-267, 2021 | 54 | 2021 |
| Context aware local differential privacy J Acharya, K Bonawitz, P Kairouz, D Ramage, Z Sun International Conference on Machine Learning, 52-62, 2020 | 54 | 2020 |
| Unified lower bounds for interactive high-dimensional estimation under information constraints J Acharya, CL Canonne, Z Sun, H Tyagi Advances in Neural Information Processing Systems 36, 51133-51165, 2023 | 44 | 2023 |
| Social distancing has merely stabilized COVID-19 in the US AB Wagner, EL Hill, SE Ryan, Z Sun, G Deng, S Bhadane, VH Martinez, ... Stat, 2020 | 33* | 2020 |
| Domain compression and its application to randomness-optimal distributed goodness-of-fit J Acharya, CL Canonne, Y Han, Z Sun, H Tyagi Conference on Learning Theory, 3-40, 2020 | 28 | 2020 |
| Improved bounds for minimax risk of estimating missing mass J Acharya, Y Bao, Y Kang, Z Sun 2018 IEEE International Symposium on Information Theory (ISIT), 326-330, 2018 | 28 | 2018 |
| Discrete distribution estimation under user-level local differential privacy J Acharya, Y Liu, Z Sun International Conference on Artificial Intelligence and Statistics, 8561-8585, 2023 | 26 | 2023 |
| Inspectre: Privately estimating the unseen J Acharya, G Kamath, Z Sun, H Zhang International Conference on Machine Learning, 30-39, 2018 | 26 | 2018 |
| Estimating sparse discrete distributions under privacy and communication constraints J Acharya, P Kairouz, Y Liu, Z Sun Algorithmic Learning Theory, 79-98, 2021 | 25* | 2021 |
| The role of interactivity in structured estimation J Acharya, CL Canonne, Z Sun, H Tyagi Conference on Learning Theory, 1328-1355, 2022 | 17 | 2022 |
| Estimating entropy of distributions in constant space J Acharya, S Bhadane, P Indyk, Z Sun Advances in Neural Information Processing Systems 32, 2019 | 17 | 2019 |
Jayadev AcharyaAssistant Professor, Cornell University在 cornell.edu 的电子邮件经过验证
