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2003.04509
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Closure Properties for Private Classification and Online Prediction
Annual Conference Computational Learning Theory (COLT), 2020
10 March 2020
N. Alon
A. Beimel
Shay Moran
Uri Stemmer
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Papers citing
"Closure Properties for Private Classification and Online Prediction"
17 / 17 papers shown
Private Realizable-to-Agnostic Transformation with Near-Optimal Sample Complexity
Annual Conference Computational Learning Theory (COLT), 2025
B. Li
Wei Wang
Peng Ye
394
1
0
01 Oct 2025
Private Online Learning against an Adaptive Adversary: Realizable and Agnostic Settings
B. Li
Wei Wang
Peng Ye
307
1
0
01 Oct 2025
Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy
International Conference on Machine Learning (ICML), 2024
Bo Li
Wei Wang
Peng Ye
FedML
287
1
0
30 Jul 2024
Private Everlasting Prediction
Neural Information Processing Systems (NeurIPS), 2023
M. Naor
Kobbi Nissim
Uri Stemmer
Chao Yan
321
5
0
16 May 2023
On the Learnability of Multilabel Ranking
Neural Information Processing Systems (NeurIPS), 2023
Vinod Raman
Unique Subedi
Ambuj Tewari
264
2
0
06 Apr 2023
Stability is Stable: Connections between Replicability, Privacy, and Adaptive Generalization
Symposium on the Theory of Computing (STOC), 2023
Mark Bun
Marco Gaboardi
Max Hopkins
R. Impagliazzo
Rex Lei
T. Pitassi
Satchit Sivakumar
Jessica Sorrell
281
45
0
22 Mar 2023
Õptimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization
Symposium on the Theory of Computing (STOC), 2022
E. Cohen
Xin Lyu
Jelani Nelson
Tamas Sarlos
Uri Stemmer
177
23
0
11 Nov 2022
Realizable Learning is All You Need
Max Hopkins
D. Kane
Shachar Lovett
G. Mahajan
648
28
0
08 Nov 2021
Fat-Shattering Dimension of
k
k
k
-fold Aggregations
Journal of machine learning research (JMLR), 2021
Idan Attias
A. Kontorovich
300
3
0
10 Oct 2021
Agnostic Online Learning and Excellent Sets
M. Malliaris
Shay Moran
CLL
230
0
0
12 Aug 2021
On the Sample Complexity of Privately Learning Axis-Aligned Rectangles
Neural Information Processing Systems (NeurIPS), 2021
Menachem Sadigurschi
Uri Stemmer
218
6
0
24 Jul 2021
Private learning implies quantum stability
Neural Information Processing Systems (NeurIPS), 2021
Srinivasan Arunachalam
Yihui Quek
J. Smolin
232
20
0
14 Feb 2021
Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games
Annual Conference Computational Learning Theory (COLT), 2021
Steve Hanneke
Roi Livni
Shay Moran
212
22
0
02 Feb 2021
Near-tight closure bounds for Littlestone and threshold dimensions
Badih Ghazi
Noah Golowich
Ravi Kumar
Pasin Manurangsi
AI4CE
231
10
0
07 Jul 2020
On the Equivalence between Online and Private Learnability beyond Binary Classification
Neural Information Processing Systems (NeurIPS), 2020
Young Hun Jung
Baekjin Kim
Ambuj Tewari
342
17
0
02 Jun 2020
An Equivalence Between Private Classification and Online Prediction
IEEE Annual Symposium on Foundations of Computer Science (FOCS), 2020
Mark Bun
Roi Livni
Shay Moran
383
88
0
01 Mar 2020
Learning Privately with Labeled and Unlabeled Examples
A. Beimel
Kobbi Nissim
Uri Stemmer
404
26
0
10 Jul 2014
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