ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2406.03620
  4. Cited By
Private Online Learning via Lazy Algorithms
v1v2 (latest)

Private Online Learning via Lazy Algorithms

5 June 2024
Hilal Asi
Tomer Koren
Daogao Liu
Kunal Talwar
ArXiv (abs)PDFHTML

Papers citing "Private Online Learning via Lazy Algorithms"

17 / 17 papers shown
Title
Private Online Learning against an Adaptive Adversary: Realizable and Agnostic Settings
Private Online Learning against an Adaptive Adversary: Realizable and Agnostic Settings
B. Li
Wei Wang
Peng Ye
159
0
0
01 Oct 2025
Faster Rates for Private Adversarial Bandits
Faster Rates for Private Adversarial Bandits
Hilal Asi
Vinod Raman
Kunal Talwar
PICVFedML
219
0
0
27 May 2025
Improved Differentially Private and Lazy Online Convex Optimization
Improved Differentially Private and Lazy Online Convex Optimization
Naman Agarwal
Satyen Kale
Karan Singh
Abhradeep Thakurta
236
4
0
15 Dec 2023
Near-Optimal Algorithms for Private Online Optimization in the
  Realizable Regime
Near-Optimal Algorithms for Private Online Optimization in the Realizable RegimeInternational Conference on Machine Learning (ICML), 2023
Hilal Asi
Vitaly Feldman
Tomer Koren
Kunal Talwar
134
11
0
27 Feb 2023
Private Online Prediction from Experts: Separations and Faster Rates
Private Online Prediction from Experts: Separations and Faster RatesAnnual Conference Computational Learning Theory (COLT), 2022
Hilal Asi
Vitaly Feldman
Tomer Koren
Kunal Talwar
FedML
216
23
0
24 Oct 2022
Private Convex Optimization via Exponential Mechanism
Private Convex Optimization via Exponential MechanismAnnual Conference Computational Learning Theory (COLT), 2022
Sivakanth Gopi
Y. Lee
Daogao Liu
281
59
0
01 Mar 2022
Adapting to Function Difficulty and Growth Conditions in Private
  Optimization
Adapting to Function Difficulty and Growth Conditions in Private OptimizationNeural Information Processing Systems (NeurIPS), 2021
Hilal Asi
Daniel Levy
John C. Duchi
130
25
0
05 Aug 2021
Private Stochastic Convex Optimization: Optimal Rates in $\ell_1$
  Geometry
Private Stochastic Convex Optimization: Optimal Rates in ℓ1\ell_1ℓ1​ GeometryInternational Conference on Machine Learning (ICML), 2021
Hilal Asi
Vitaly Feldman
Tomer Koren
Kunal Talwar
151
102
0
02 Mar 2021
Lazy OCO: Online Convex Optimization on a Switching Budget
Lazy OCO: Online Convex Optimization on a Switching BudgetAnnual Conference Computational Learning Theory (COLT), 2021
Uri Sherman
Tomer Koren
283
18
0
07 Feb 2021
Private Stochastic Convex Optimization: Optimal Rates in Linear Time
Private Stochastic Convex Optimization: Optimal Rates in Linear Time
Vitaly Feldman
Tomer Koren
Kunal Talwar
215
225
0
10 May 2020
Minimax Regret of Switching-Constrained Online Convex Optimization: No
  Phase Transition
Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase TransitionNeural Information Processing Systems (NeurIPS), 2019
Lin Chen
Qian-long Yu
Hannah Lawrence
Amin Karbasi
273
22
0
24 Oct 2019
Introduction to Online Convex Optimization
Introduction to Online Convex Optimization
Elad Hazan
OffRL
581
2,079
0
07 Sep 2019
Private Stochastic Convex Optimization with Optimal Rates
Private Stochastic Convex Optimization with Optimal RatesNeural Information Processing Systems (NeurIPS), 2019
Raef Bassily
Vitaly Feldman
Kunal Talwar
Abhradeep Thakurta
239
262
0
27 Aug 2019
Online learning over a finite action set with limited switching
Online learning over a finite action set with limited switching
Jason M. Altschuler
Kunal Talwar
170
39
0
05 Mar 2018
The Price of Differential Privacy For Online Learning
The Price of Differential Privacy For Online LearningInternational Conference on Machine Learning (ICML), 2017
Naman Agarwal
Karan Singh
FedML
317
104
0
27 Jan 2017
Concentrated Differential Privacy: Simplifications, Extensions, and
  Lower Bounds
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds
Mark Bun
Thomas Steinke
272
916
0
06 May 2016
The Composition Theorem for Differential Privacy
The Composition Theorem for Differential PrivacyIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2013
Peter Kairouz
Sewoong Oh
Pramod Viswanath
838
749
0
04 Nov 2013
1