Private PAC learning implies finite Littlestone dimension

4 June 2018

Papers citing "Private PAC learning implies finite Littlestone dimension"

24 / 24 papers shown

Title
$An \tilde{O}ptimal Differentially Private Learner for Concept Classes with VC Dimension 1$ An \tilde{O}ptimal Differentially Private Learner for Concept Classes with VC Dimension 1 Chao Yan 23 0 0 10 May 2025
Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy Bo Li Wei Wang Peng Ye FedML 36 0 0 30 Jul 2024
Credit Attribution and Stable Compression Roi Livni Shay Moran Kobbi Nissim Chirag Pabbaraju 49 0 0 22 Jun 2024
On the Computational Landscape of Replicable Learning Alkis Kalavasis Amin Karbasi Grigoris Velegkas Felix Y. Zhou 50 2 0 24 May 2024
When is Agnostic Reinforcement Learning Statistically Tractable? Zeyu Jia Gene Li Alexander Rakhlin Ayush Sekhari Nathan Srebro OffRL 27 5 0 09 Oct 2023
Statistical Indistinguishability of Learning Algorithms Alkis Kalavasis Amin Karbasi Shay Moran Grigoris Velegkas 25 16 0 23 May 2023
A Unified Characterization of Private Learnability via Graph Theory N. Alon Shay Moran Hilla Schefler Amir Yehudayoff 31 2 0 08 Apr 2023
List and Certificate Complexities in Replicable Learning P. Dixon A. Pavan Jason Vander Woude N. V. Vinodchandran 26 12 0 05 Apr 2023
Stability is Stable: Connections between Replicability, Privacy, and Adaptive Generalization Mark Bun Marco Gaboardi Max Hopkins R. Impagliazzo Rex Lei T. Pitassi Satchit Sivakumar Jessica Sorrell 28 29 0 22 Mar 2023
On Differential Privacy and Adaptive Data Analysis with Bounded Space Itai Dinur Uri Stemmer David P. Woodruff Samson Zhou 21 12 0 11 Feb 2023
Comparative Learning: A Sample Complexity Theory for Two Hypothesis Classes Lunjia Hu Charlotte Peale 43 6 0 16 Nov 2022
Private Isotonic Regression Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi 21 0 0 27 Oct 2022
Algorithms with More Granular Differential Privacy Guarantees Badih Ghazi Ravi Kumar Pasin Manurangsi Thomas Steinke 59 6 0 08 Sep 2022
Finite Littlestone Dimension Implies Finite Information Complexity Aditya Pradeep Ido Nachum Michael C. Gastpar 11 7 0 27 Jun 2022
User-Level Private Learning via Correlated Sampling Badih Ghazi Ravi Kumar Pasin Manurangsi FedML 40 13 0 21 Oct 2021
A Theory of PAC Learnability of Partial Concept Classes N. Alon Steve Hanneke R. Holzman Shay Moran 14 50 0 18 Jul 2021
Deep Learning with Label Differential Privacy Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Chiyuan Zhang 42 144 0 11 Feb 2021
Smoothed Analysis of Online and Differentially Private Learning Nika Haghtalab Tim Roughgarden Abhishek Shetty 28 47 0 17 Jun 2020
Private Query Release Assisted by Public Data Raef Bassily Albert Cheu Shay Moran Aleksandar Nikolov Jonathan R. Ullman Zhiwei Steven Wu 70 47 0 23 Apr 2020
Online Agnostic Boosting via Regret Minimization Nataly Brukhim Xinyi Chen Elad Hazan Shay Moran 13 13 0 02 Mar 2020
An Equivalence Between Private Classification and Online Prediction Mark Bun Roi Livni Shay Moran 21 75 0 01 Mar 2020
Privately Learning Thresholds: Closing the Exponential Gap Haim Kaplan Katrina Ligett Yishay Mansour M. Naor Uri Stemmer 25 55 0 22 Nov 2019
Learning Privately with Labeled and Unlabeled Examples A. Beimel Kobbi Nissim Uri Stemmer 37 23 0 10 Jul 2014
Sample Complexity Bounds on Differentially Private Learning via Communication Complexity Vitaly Feldman David Xiao 175 71 0 25 Feb 2014