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Online prediction from experts is a fundamental problem in machine learning and several works have studied this problem under privacy constraints.
“Fingerprinting Codes and the Price of Approximate Differential Privacy”
Mark Bun, Jonathan Ullman and Salil Vadhan · 1938
Earlier work this paper cites.
“Efficient algorithms for online decision problems”
A. Kalai and S. Vempala · 2005
Earlier work this paper cites.
“Probability and computing: Randomized algorithms and probabilistic analysis”
Michael Mitzenmacher and Eli Upfal · 2005
Earlier work this paper cites.
“Prediction, learning, and games”
Nicolo Cesa-Bianchi and G“’abor Lugosi · 2006
Earlier work this paper cites.
“Our Data, Ourselves: Privacy Via Distributed Noise Generation”
Cynthia Dwork, Krishnaram Kenthapadi, Frank McSherry, Ilya Mironov and Moni Naor · 2006
Earlier work this paper cites.
“Calibrating noise to sensitivity in private data analysis”
Cynthia Dwork, Frank McSherry, Kobbi Nissim and Adam Smith · 2006
Earlier work this paper cites.
“Differential privacy under continual observation”
Cynthia Dwork, Moni Naor, Toniann Pitassi and Guy Rothblum · 2010
Earlier work this paper cites.
“Regret Minimization for Online Buffering Problems Using the Weighted Majority Algorithm.”
Sascha Geulen, Berthold V“”ocking and Melanie Winkler · 2010
Earlier work this paper cites.
“The multiplicative weights update method: a meta algorithm and applications”
Sanjeev Arora, Elad Hazan and Satyen Kale · 2012
Earlier work this paper cites.
“Differentially private online learning”
Prateek Jain, Pravesh Kothari and Abhradeep Thakurta · 2012
Cited alongside, same era.
“(Nearly) optimal algorithms for private online learning in full-information and bandit settings”
Adam Smith and Abhradeep Thakurta · 2013
Cited alongside, same era.
“Private empirical risk minimization: Efficient algorithms and tight error bounds”
Raef Bassily, Adam Smith and Abhradeep Thakurta · 2014
Cited alongside, same era.
“The Algorithmic Foundations of Differential Privacy”
Cynthia Dwork and Aaron Roth · 2014
Cited alongside, same era.
“(Near) dimension independent risk bounds for differentially private learning”
Prateek Jain and Abhradeep Thakurta · 2014
Cited alongside, same era.
“The price of differential privacy for online learning”
Naman Agarwal and Karan Singh · 2017
“Minimax regret of switching-constrained online convex optimization: No phase transition”
Lin Chen, Qian Yu, Hannah Lawrence and Amin Karbasi · 2020
Later among the works it cites.
“Private stochastic convex optimization: optimal rates in linear time”
Vitaly Feldman, Tomer Koren and Kunal Talwar · 2020
Later among the works it cites.
“Private Adaptive Gradient Methods for Convex Optimization”
Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht and Kunal Talwar · 2021
Later among the works it cites.
“Private Stochastic Convex Optimization: Optimal Rates in ℓ 1 \ell_{1} Geometry”
Hilal Asi, Vitaly Feldman, Tomer Koren and Kunal Talwar · 2021
Later among the works it cites.
“Adapting to function difficulty and growth conditions in private optimization”
Hilal Asi, Daniel Levy and John Duchi · 2021
Later among the works it cites.
“The Price of Differential Privacy under Continual Observation”
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Cited alongside, same era.
“Tight lower bounds for differentially private selection”
Thomas Steinke and Jonathan Ullman · 2017
Cited alongside, same era.
“Online learning over a finite action set with limited switching”
Jason Altschuler and Kunal Talwar · 2018
Cited alongside, same era.
“Private stochastic convex optimization with optimal rates”
Raef Bassily, Vitaly Feldman, Kunal Talwar and Abhradeep Thakurta · 2019
Cited alongside, same era.
Palak Jain, Sofya Raskhodnikova, Satchit Sivakumar and Adam Smith · 2021
Later among the works it cites.
“Practical and Private (Deep) Learning without Sampling or Shuffling”
Peter Kairouz, Brendan McMahan, Shuang Song, Om Thakkar, Abhradeep Thakurta and Zheng Xu · 2021
Later among the works it cites.
“Lazy oco: Online convex optimization on a switching budget”
Uri Sherman and Tomer Koren · 2021
Later among the works it cites.
“Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime”
Hilal Asi, Vitaly Feldman, Tomer Koren and Kunal Talwar · 2023
Closest in time.