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Private Online Prediction from Experts: Separations and Faster Rates

Private Online Prediction from Experts: Separations and Faster Rates

24 October 2022
Hilal Asi
Vitaly Feldman
Tomer Koren
Kunal Talwar
    FedML
ArXivPDFHTML

Papers citing "Private Online Prediction from Experts: Separations and Faster Rates"

13 / 13 papers shown
Title
Federated Online Prediction from Experts with Differential Privacy:
  Separations and Regret Speed-ups
Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups
Fengyu Gao
Ruiquan Huang
Jing Yang
FedML
32
0
0
27 Sep 2024
Private Online Learning via Lazy Algorithms
Private Online Learning via Lazy Algorithms
Hilal Asi
Tomer Koren
Daogao Liu
Kunal Talwar
101
0
0
05 Jun 2024
DP-Dueling: Learning from Preference Feedback without Compromising User
  Privacy
DP-Dueling: Learning from Preference Feedback without Compromising User Privacy
Aadirupa Saha
Hilal Asi
36
1
0
22 Mar 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
22
2
0
16 Feb 2024
Online Distribution Learning with Local Private Constraints
Online Distribution Learning with Local Private Constraints
Jin Sima
Changlong Wu
O. Milenkovic
Wojtek Szpankowski
22
0
0
01 Feb 2024
Improved Differentially Private and Lazy Online Convex Optimization
Improved Differentially Private and Lazy Online Convex Optimization
Naman Agarwal
Satyen Kale
Karan Singh
Abhradeep Thakurta
12
2
0
15 Dec 2023
(Amplified) Banded Matrix Factorization: A unified approach to private
  training
(Amplified) Banded Matrix Factorization: A unified approach to private training
Christopher A. Choquette-Choo
Arun Ganesh
Ryan McKenna
H. B. McMahan
Keith Rush
Abhradeep Thakurta
Zheng Xu
FedML
23
35
0
13 Jun 2023
Near-Optimal Algorithms for Private Online Optimization in the
  Realizable Regime
Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime
Hilal Asi
Vitaly Feldman
Tomer Koren
Kunal Talwar
28
9
0
27 Feb 2023
On Differentially Private Online Predictions
On Differentially Private Online Predictions
Haim Kaplan
Yishay Mansour
Shay Moran
Kobbi Nissim
Uri Stemmer
23
5
0
27 Feb 2023
Constant matters: Fine-grained Complexity of Differentially Private
  Continual Observation
Constant matters: Fine-grained Complexity of Differentially Private Continual Observation
Hendrik Fichtenberger
Monika Henzinger
Jalaj Upadhyay
29
20
0
23 Feb 2022
Practical and Private (Deep) Learning without Sampling or Shuffling
Practical and Private (Deep) Learning without Sampling or Shuffling
Peter Kairouz
Brendan McMahan
Shuang Song
Om Thakkar
Abhradeep Thakurta
Zheng Xu
FedML
180
154
0
26 Feb 2021
Near-Optimal Algorithms for Differentially Private Online Learning in a
  Stochastic Environment
Near-Optimal Algorithms for Differentially Private Online Learning in a Stochastic Environment
Bingshan Hu
Zhiming Huang
Nishant A. Mehta
Nidhi Hegde
FedML
20
1
0
16 Feb 2021
Lazy OCO: Online Convex Optimization on a Switching Budget
Lazy OCO: Online Convex Optimization on a Switching Budget
Uri Sherman
Tomer Koren
11
15
0
07 Feb 2021
1