Stochastic (approximate) proximal point methods: Convergence, optimality, and adaptivity H Asi, JC Duchi
SIAM Journal on Optimization 29 (3), 2257-2290, 2019
101 2019 The importance of better models in stochastic optimization H Asi, JC Duchi
Proceedings of the National Academy of Sciences 116 (46), 22924-22930, 2019
71 2019 Private Stochastic Convex Optimization: Optimal Rates in H Asi, V Feldman, T Koren, K Talwar
ICML 2021 (Oral), 2021
56 2021 Nearly optimal constructions of PIR and batch codes H Asi, E Yaakobi
IEEE Transactions on Information Theory 65 (2), 947-964, 2018
34 2018 Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms H Asi, JC Duchi
Advances in neural information processing systems 33, 14106-14117, 2020
32 2020 Private adaptive gradient methods for convex optimization H Asi, J Duchi, A Fallah, O Javidbakht, K Talwar
International Conference on Machine Learning, 383-392, 2021
31 2021 Near instance-optimality in differential privacy H Asi, JC Duchi
arXiv preprint arXiv:2005.10630, 2020
22 2020 Element level differential privacy: The right granularity of privacy H Asi, J Duchi, O Javidbakht
arXiv preprint arXiv:1912.04042, 2019
16 2019 Stochastic bias-reduced gradient methods H Asi, Y Carmon, A Jambulapati, Y Jin, A Sidford
Advances in Neural Information Processing Systems 34, 10810-10822, 2021
14 2021 Minibatch stochastic approximate proximal point methods H Asi, K Chadha, G Cheng, JC Duchi
Advances in neural information processing systems 33, 21958-21968, 2020
12 2020 Optimal algorithms for mean estimation under local differential privacy H Asi, V Feldman, K Talwar
International Conference on Machine Learning, 1046-1056, 2022
10 2022 Adapting to function difficulty and growth conditions in private optimization H Asi, D Lévy, JC Duchi
Advances in Neural Information Processing Systems 34, 19069-19081, 2021
7 2021 Finding planted cliques in sublinear time J Mardia, H Asi, KA Chandrasekher
arXiv preprint arXiv:2004.12002, 2020
6 2020 Modeling simple structures and geometry for better stochastic optimization algorithms H Asi, JC Duchi
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
6 2019 Private Online Prediction from Experts: Separations and Faster Rates H Asi, V Feldman, T Koren, K Talwar
arXiv preprint arXiv:2210.13537, 2022
3 2022 Private optimization in the interpolation regime: faster rates and hardness results H Asi, K Chadha, G Cheng, J Duchi
International Conference on Machine Learning, 1025-1045, 2022
3 2022 How many labelers do you have? A closer look at gold-standard labels C Cheng, H Asi, J Duchi
arXiv preprint arXiv:2206.12041, 2022
3 2022 From robustness to privacy and back H Asi, J Ullman, L Zakynthinou
arXiv preprint arXiv:2302.01855, 2023
2 2023 Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime H Asi, V Feldman, T Koren, K Talwar
arXiv preprint arXiv:2302.14154, 2023
2023 Private Data Analysis Beyond the Worst Case H Asi
Stanford University, 2022
2022 
John DuchiAssociate Professor of Statistics and Electrical Engineering, Stanford UniversityGeverifieerd e-mailadres voor stanford.edu
