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2020 – today
- 2023
[i14]Hilal Asi, Jonathan R. Ullman, Lydia Zakynthinou:
From Robustness to Privacy and Back. CoRR abs/2302.01855 (2023)- [i13]Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar:
Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime. CoRR abs/2302.14154 (2023) - 2022
- [c10]Hilal Asi, Karan N. Chadha, Gary Cheng, John C. Duchi:
Private optimization in the interpolation regime: faster rates and hardness results. ICML 2022: 1025-1045 - [c9]Hilal Asi, Vitaly Feldman, Kunal Talwar:
Optimal Algorithms for Mean Estimation under Local Differential Privacy. ICML 2022: 1046-1056 - [i12]Hilal Asi, Vitaly Feldman, Kunal Talwar:
Optimal Algorithms for Mean Estimation under Local Differential Privacy. CoRR abs/2205.02466 (2022) - [i11]Chen Cheng, Hilal Asi, John C. Duchi:
How many labelers do you have? A closer look at gold-standard labels. CoRR abs/2206.12041 (2022) - [i10]Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar:
Private Online Prediction from Experts: Separations and Faster Rates. CoRR abs/2210.13537 (2022) - [i9]Hilal Asi, Karan N. Chadha, Gary Cheng, John C. Duchi:
Private optimization in the interpolation regime: faster rates and hardness results. CoRR abs/2210.17070 (2022) - 2021
- [c8]Hilal Asi, John C. Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar:
Private Adaptive Gradient Methods for Convex Optimization. ICML 2021: 383-392 - [c7]Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar:
Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry. ICML 2021: 393-403 - [c6]Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford:
Stochastic Bias-Reduced Gradient Methods. NeurIPS 2021: 10810-10822 - [c5]Hilal Asi, Daniel Levy, John C. Duchi:
Adapting to function difficulty and growth conditions in private optimization. NeurIPS 2021: 19069-19081 - [i8]Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar:
Private Stochastic Convex Optimization: Optimal Rates in 𝓁1 Geometry. CoRR abs/2103.01516 (2021) - [i7]Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford:
Stochastic Bias-Reduced Gradient Methods. CoRR abs/2106.09481 (2021) - [i6]Hilal Asi, John C. Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar:
Private Adaptive Gradient Methods for Convex Optimization. CoRR abs/2106.13756 (2021) - [i5]Hilal Asi, Daniel Levy, John C. Duchi:
Adapting to Function Difficulty and Growth Conditions in Private Optimization. CoRR abs/2108.02391 (2021) - 2020
- [c4]Hilal Asi, Karan N. Chadha, Gary Cheng, John C. Duchi:
Minibatch Stochastic Approximate Proximal Point Methods. NeurIPS 2020 - [c3]Hilal Asi, John C. Duchi:
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms. NeurIPS 2020 - [i4]Jay Mardia, Hilal Asi, Kabir Aladin Chandrasekher:
Finding Planted Cliques in Sublinear Time. CoRR abs/2004.12002 (2020) - [i3]Hilal Asi, John C. Duchi:
Near Instance-Optimality in Differential Privacy. CoRR abs/2005.10630 (2020)
2010 – 2019
- 2019
- [j2]Hilal Asi, John C. Duchi:
Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity. SIAM J. Optim. 29(3): 2257-2290 (2019) - [j1]Hilal Asi
, Eitan Yaakobi:
Nearly Optimal Constructions of PIR and Batch Codes. IEEE Trans. Inf. Theory 65(2): 947-964 (2019) - [c2]Hilal Asi, John C. Duchi:
Modeling simple structures and geometry for better stochastic optimization algorithms. AISTATS 2019: 2425-2434 - [i2]Hilal Asi, John C. Duchi, Omid Javidbakht:
Element Level Differential Privacy: The Right Granularity of Privacy. CoRR abs/1912.04042 (2019) - 2017
- [c1]Hilal Asi, Eitan Yaakobi:
Nearly optimal constructions of PIR and batch codes. ISIT 2017: 151-155 - [i1]Hilal Asi, Eitan Yaakobi:
Nearly Optimal Constructions of PIR and Batch Codes. CoRR abs/1701.07206 (2017)
Coauthor Index
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last updated on 2023-03-03 22:37 CET by the dblp team
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