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Optimal Learners for Realizable Regression: PAC Learning and Online
  Learning

Optimal Learners for Realizable Regression: PAC Learning and Online Learning

7 July 2023
Idan Attias
Steve Hanneke
Alkis Kalavasis
Amin Karbasi
Grigoris Velegkas
ArXivPDFHTML

Papers citing "Optimal Learners for Realizable Regression: PAC Learning and Online Learning"

17 / 17 papers shown
Title
Kolmogorov-Arnold Networks: Approximation and Learning Guarantees for Functions and their Derivatives
Kolmogorov-Arnold Networks: Approximation and Learning Guarantees for Functions and their Derivatives
Anastasis Kratsios
Takashi Furuya
22
0
0
21 Apr 2025
Logical perspectives on learning statistical objects
Logical perspectives on learning statistical objects
Aaron Anderson
Michael Benedikt
49
0
0
01 Apr 2025
On The Statistical Complexity of Offline Decision-Making
On The Statistical Complexity of Offline Decision-Making
Thanh Nguyen-Tang
R. Arora
OffRL
31
1
0
10 Jan 2025
Multiclass Transductive Online Learning
Multiclass Transductive Online Learning
Steve Hanneke
Vinod Raman
Amirreza Shaeiri
Unique Subedi
26
0
0
03 Nov 2024
Sample Compression Scheme Reductions
Sample Compression Scheme Reductions
Idan Attias
Steve Hanneke
Arvind Ramaswami
MQ
21
1
0
16 Oct 2024
Sequential Probability Assignment with Contexts: Minimax Regret,
  Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood
Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood
Ziyi Liu
Idan Attias
Daniel M. Roy
16
1
0
04 Oct 2024
A Characterization of List Regression
A Characterization of List Regression
Chirag Pabbaraju
Sahasrajit Sarmasarkar
15
1
0
28 Sep 2024
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses
Mathieu Bazinet
Valentina Zantedeschi
Pascal Germain
MLT
AI4CE
26
2
0
26 Sep 2024
Is Transductive Learning Equivalent to PAC Learning?
Is Transductive Learning Equivalent to PAC Learning?
S. Dughmi
Y. Kalayci
Grayson York
24
3
0
08 May 2024
Transfer Learning Beyond Bounded Density Ratios
Transfer Learning Beyond Bounded Density Ratios
Alkis Kalavasis
Ilias Zadik
Manolis Zampetakis
31
4
0
18 Mar 2024
Information Complexity of Stochastic Convex Optimization: Applications
  to Generalization and Memorization
Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization
Idan Attias
Gintare Karolina Dziugaite
Mahdi Haghifam
Roi Livni
Daniel M. Roy
25
6
0
14 Feb 2024
Regularization and Optimal Multiclass Learning
Regularization and Optimal Multiclass Learning
Julian Asilis
Siddartha Devic
S. Dughmi
Vatsal Sharan
S. Teng
17
7
0
24 Sep 2023
A Combinatorial Characterization of Supervised Online Learnability
A Combinatorial Characterization of Supervised Online Learnability
Vinod Raman
Unique Subedi
Ambuj Tewari
11
0
0
07 Jul 2023
Adversarially Robust Learning: A Generic Minimax Optimal Learner and
  Characterization
Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization
Omar Montasser
Steve Hanneke
Nathan Srebro
16
17
0
15 Sep 2022
Realizable Learning is All You Need
Realizable Learning is All You Need
Max Hopkins
D. Kane
Shachar Lovett
G. Mahajan
91
22
0
08 Nov 2021
Adversarial Laws of Large Numbers and Optimal Regret in Online
  Classification
Adversarial Laws of Large Numbers and Optimal Regret in Online Classification
N. Alon
Omri Ben-Eliezer
Y. Dagan
Shay Moran
M. Naor
E. Yogev
73
51
0
22 Jan 2021
Agnostic Sample Compression Schemes for Regression
Agnostic Sample Compression Schemes for Regression
Idan Attias
Steve Hanneke
A. Kontorovich
Menachem Sadigurschi
17
4
0
03 Oct 2018
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