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2204.07196
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Testing distributional assumptions of learning algorithms
Symposium on the Theory of Computing (STOC), 2022
14 April 2022
R. Rubinfeld
Arsen Vasilyan
OOD
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Papers citing
"Testing distributional assumptions of learning algorithms"
17 / 17 papers shown
Limitations of Membership Queries in Testable Learning
Information Technology Convergence and Services (ITCS), 2025
Jane Lange
Mingda Qiao
91
0
0
01 Dec 2025
The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination
Adam R. Klivans
Konstantinos Stavropoulos
Kevin Tian
Arsen Vasilyan
255
2
0
26 May 2025
Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees
International Conference on Learning Representations (ICLR), 2025
Gautam Chandrasekaran
Adam R. Klivans
Lin Lin Lee
Konstantinos Stavropoulos
OOD
260
2
0
22 Feb 2025
Optimal Algorithms for Augmented Testing of Discrete Distributions
Neural Information Processing Systems (NeurIPS), 2024
Maryam Aliakbarpour
Piotr Indyk
R. Rubinfeld
Sandeep Silwal
319
3
0
01 Dec 2024
Oblivious Defense in ML Models: Backdoor Removal without Detection
Symposium on the Theory of Computing (STOC), 2024
S. Goldwasser
Jonathan Shafer
Neekon Vafa
Vinod Vaikuntanathan
AAML
225
4
0
05 Nov 2024
Efficient Testable Learning of General Halfspaces with Adversarial Label Noise
Ilias Diakonikolas
Daniel M. Kane
Sihan Liu
Nikos Zarifis
198
0
0
30 Aug 2024
Efficient Discrepancy Testing for Learning with Distribution Shift
Gautam Chandrasekaran
Adam R. Klivans
Vasilis Kontonis
Konstantinos Stavropoulos
Arsen Vasilyan
259
7
0
13 Jun 2024
Tolerant Algorithms for Learning with Arbitrary Covariate Shift
Surbhi Goel
Abhishek Shetty
Konstantinos Stavropoulos
Arsen Vasilyan
OOD
288
12
0
04 Jun 2024
Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds
Annual Conference Computational Learning Theory (COLT), 2024
Adam R. Klivans
Konstantinos Stavropoulos
Arsen Vasilyan
284
13
0
02 Apr 2024
Distribution-Specific Auditing For Subgroup Fairness
Symposium on Foundations of Responsible Computing (FRC), 2024
Daniel Hsu
Jizhou Huang
Brendan Juba
293
3
0
27 Jan 2024
Adversarial Resilience in Sequential Prediction via Abstention
Neural Information Processing Systems (NeurIPS), 2023
Surbhi Goel
Steve Hanneke
Shay Moran
Abhishek Shetty
352
14
0
22 Jun 2023
Classical Verification of Quantum Learning
Information Technology Convergence and Services (ITCS), 2023
Matthias C. Caro
M. Hinsche
M. Ioannou
A. Nietner
R. Sweke
283
9
0
08 Jun 2023
Tester-Learners for Halfspaces: Universal Algorithms
Neural Information Processing Systems (NeurIPS), 2023
Aravind Gollakota
Adam R. Klivans
Konstantinos Stavropoulos
Arsen Vasilyan
272
15
0
19 May 2023
Efficient Testable Learning of Halfspaces with Adversarial Label Noise
Neural Information Processing Systems (NeurIPS), 2023
Ilias Diakonikolas
D. Kane
Vasilis Kontonis
Sihan Liu
Nikos Zarifis
AAML
267
20
0
09 Mar 2023
An Efficient Tester-Learner for Halfspaces
International Conference on Learning Representations (ICLR), 2023
Aravind Gollakota
Adam R. Klivans
Konstantinos Stavropoulos
Arsen Vasilyan
215
16
0
28 Feb 2023
PAC Verification of Statistical Algorithms
Annual Conference Computational Learning Theory (COLT), 2022
Saachi Mutreja
Jonathan Shafer
224
7
0
28 Nov 2022
A Moment-Matching Approach to Testable Learning and a New Characterization of Rademacher Complexity
Symposium on the Theory of Computing (STOC), 2022
Aravind Gollakota
Adam R. Klivans
Pravesh Kothari
CoGe
191
22
0
23 Nov 2022
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