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A Computational Separation between Private Learning and Online Learning

A Computational Separation between Private Learning and Online Learning

11 July 2020
Mark Bun
    FedML
ArXiv (abs)PDFHTML

Papers citing "A Computational Separation between Private Learning and Online Learning"

6 / 6 papers shown
Title
On the Computational Landscape of Replicable Learning
On the Computational Landscape of Replicable Learning
Alkis Kalavasis
Amin Karbasi
Grigoris Velegkas
Felix Y. Zhou
101
4
0
24 May 2024
Exploration is Harder than Prediction: Cryptographically Separating
  Reinforcement Learning from Supervised Learning
Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning
Noah Golowich
Ankur Moitra
Dhruv Rohatgi
OffRL
92
4
0
04 Apr 2024
Private PAC Learning May be Harder than Online Learning
Private PAC Learning May be Harder than Online Learning
Mark Bun
Aloni Cohen
Rathin Desai
73
2
0
16 Feb 2024
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean
  Estimation
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation
Kristian Georgiev
Samuel B. Hopkins
FedML
136
26
0
01 Nov 2022
Differentially Private Nonparametric Regression Under a Growth Condition
Differentially Private Nonparametric Regression Under a Growth Condition
Noah Golowich
97
6
0
24 Nov 2021
Private learning implies quantum stability
Private learning implies quantum stability
Srinivasan Arunachalam
Yihui Quek
J. Smolin
92
19
0
14 Feb 2021
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