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2101.09054
Cited By
Adversarial Laws of Large Numbers and Optimal Regret in Online Classification
Symposium on the Theory of Computing (STOC), 2021
22 January 2021
N. Alon
Omri Ben-Eliezer
Y. Dagan
Shay Moran
M. Naor
E. Yogev
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Papers citing
"Adversarial Laws of Large Numbers and Optimal Regret in Online Classification"
35 / 35 papers shown
Minimizing Human Intervention in Online Classification
William Réveillard
Vasileios Saketos
Alexandre Proutière
Richard Combes
159
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27 Oct 2025
Discriminative Feature Feedback with General Teacher Classes
Omri Bar Oz
Tosca Lechner
Sivan Sabato
247
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08 Oct 2025
Private Online Learning against an Adaptive Adversary: Realizable and Agnostic Settings
B. Li
Wei Wang
Peng Ye
308
1
0
01 Oct 2025
Beyond Worst-Case Online Classification: VC-Based Regret Bounds for Relaxed Benchmarks
Annual Conference Computational Learning Theory (COLT), 2025
Omar Montasser
Abhishek Shetty
Nikita Zhivotovskiy
360
2
0
14 Apr 2025
Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood
Neural Information Processing Systems (NeurIPS), 2024
Ziyi Liu
Idan Attias
Daniel M. Roy
195
1
0
04 Oct 2024
Fast White-Box Adversarial Streaming Without a Random Oracle
Ying Feng
Aayush Jain
David P. Woodruff
AAML
204
3
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10 Jun 2024
The Dimension of Self-Directed Learning
Pramith Devulapalli
Steve Hanneke
170
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20 Feb 2024
Robust Streaming, Sampling, and a Perspective on Online Learning
Evan Dogariu
Jiatong Yu
241
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0
04 Dec 2023
A Trichotomy for Transductive Online Learning
Neural Information Processing Systems (NeurIPS), 2023
Steve Hanneke
Shay Moran
Jonathan Shafer
298
13
0
10 Nov 2023
Apple Tasting: Combinatorial Dimensions and Minimax Rates
Annual Conference Computational Learning Theory (COLT), 2023
Vinod Raman
Unique Subedi
Ananth Raman
Ambuj Tewari
316
4
0
29 Oct 2023
Multiclass Online Learnability under Bandit Feedback
International Conference on Algorithmic Learning Theory (ALT), 2023
A. Raman
Vinod Raman
Unique Subedi
Idan Mehalel
Ambuj Tewari
254
11
0
08 Aug 2023
Optimal Learners for Realizable Regression: PAC Learning and Online Learning
Neural Information Processing Systems (NeurIPS), 2023
Idan Attias
Steve Hanneke
Alkis Kalavasis
Amin Karbasi
Grigoris Velegkas
381
26
0
07 Jul 2023
Online Learning and Solving Infinite Games with an ERM Oracle
Annual Conference Computational Learning Theory (COLT), 2023
A. Assos
Idan Attias
Y. Dagan
C. Daskalakis
Maxwell Fishelson
238
12
0
04 Jul 2023
Multiclass Online Learning and Uniform Convergence
Annual Conference Computational Learning Theory (COLT), 2023
Steve Hanneke
Shay Moran
Vinod Raman
Unique Subedi
Ambuj Tewari
CLL
283
25
0
30 Mar 2023
Clustering large 3D volumes: A sampling-based approach
Thomas Lang
154
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0
07 Mar 2023
Optimal Prediction Using Expert Advice and Randomized Littlestone Dimension
Annual Conference Computational Learning Theory (COLT), 2023
Yuval Filmus
Steve Hanneke
Idan Mehalel
Shay Moran
324
18
0
27 Feb 2023
Quantum Learning Theory Beyond Batch Binary Classification
Quantum (Quantum), 2023
Preetham Mohan
Ambuj Tewari
GNN
561
3
0
15 Feb 2023
The unstable formula theorem revisited via algorithms
M. Malliaris
Shay Moran
244
2
0
09 Dec 2022
Comparative Learning: A Sample Complexity Theory for Two Hypothesis Classes
Information Technology Convergence and Services (ITCS), 2022
Lunjia Hu
Charlotte Peale
246
10
0
16 Nov 2022
On-Demand Sampling: Learning Optimally from Multiple Distributions
Neural Information Processing Systems (NeurIPS), 2022
Nika Haghtalab
Michael I. Jordan
Eric Zhao
FedML
542
48
0
22 Oct 2022
Online Prediction in Sub-linear Space
ACM-SIAM Symposium on Discrete Algorithms (SODA), 2022
Binghui Peng
Fred Zhang
326
18
0
16 Jul 2022
Uniform Approximations for Randomized Hadamard Transforms with Applications
Symposium on the Theory of Computing (STOC), 2022
Yeshwanth Cherapanamjeri
Jelani Nelson
190
12
0
03 Mar 2022
On the power of adaptivity in statistical adversaries
Annual Conference Computational Learning Theory (COLT), 2021
Guy Blanc
Jane Lange
Ali Malik
Li-Yang Tan
AAML
304
12
0
19 Nov 2021
Fast Rates for Nonparametric Online Learning: From Realizability to Learning in Games
C. Daskalakis
Noah Golowich
326
28
0
17 Nov 2021
Realizable Learning is All You Need
Max Hopkins
D. Kane
Shachar Lovett
G. Mahajan
652
28
0
08 Nov 2021
Online Selective Classification with Limited Feedback
Aditya Gangrade
Anil Kag
Ashok Cutkosky
Venkatesh Saligrama
205
10
0
27 Oct 2021
Agnostic Online Learning and Excellent Sets
M. Malliaris
Shay Moran
CLL
232
0
0
12 Aug 2021
A Theory of PAC Learnability of Partial Concept Classes
IEEE Annual Symposium on Foundations of Computer Science (FOCS), 2021
N. Alon
Steve Hanneke
R. Holzman
Shay Moran
398
65
0
18 Jul 2021
Adversarial Robustness of Streaming Algorithms through Importance Sampling
Neural Information Processing Systems (NeurIPS), 2021
Vladimir Braverman
Avinatan Hassidim
Yossi Matias
Mariano Schain
Sandeep Silwal
Samson Zhou
AAML
OOD
216
53
0
28 Jun 2021
Understanding the Eluder Dimension
Neural Information Processing Systems (NeurIPS), 2021
Gen Li
Pritish Kamath
Dylan J. Foster
Nathan Srebro
534
18
0
14 Apr 2021
Smoothed Analysis with Adaptive Adversaries
IEEE Annual Symposium on Foundations of Computer Science (FOCS), 2021
Nika Haghtalab
Tim Roughgarden
Abhishek Shetty
AAML
385
66
0
16 Feb 2021
Majorizing Measures, Sequential Complexities, and Online Learning
Annual Conference Computational Learning Theory (COLT), 2021
Adam Block
Y. Dagan
Alexander Rakhlin
199
18
0
02 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
213
22
0
02 Feb 2021
On Learnability under General Stochastic Processes
A. Dawid
Ambuj Tewari
458
6
0
15 May 2020
A Framework for Adversarially Robust Streaming Algorithms
SIGMOD record (SIGMOD Record), 2020
Omri Ben-Eliezer
Rajesh Jayaram
David P. Woodruff
E. Yogev
AAML
316
109
0
31 Mar 2020
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