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Calibration and Consistency of Adversarial Surrogate Losses
Neural Information Processing Systems (NeurIPS), 2021
19 April 2021
Pranjal Awasthi
Natalie Frank
Anqi Mao
M. Mohri
Yutao Zhong
AAML
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Papers citing
"Calibration and Consistency of Adversarial Surrogate Losses"
28 / 28 papers shown
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Adversarial Surrogate Risk Bounds for Binary Classification
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Uniform Convergence of Adversarially Robust Classifiers
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A Universal Growth Rate for Learning with Smooth Surrogate Losses
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In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer
Neural Information Processing Systems (NeurIPS), 2023
Yuzhou Cao
Hussein Mozannar
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Jianguo Huang
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02 Nov 2023
Outlier Robust Adversarial Training
Asian Conference on Machine Learning (ACML), 2023
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Zhenhuan Yang
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Yiming Ying
Siwei Lyu
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05 Jul 2023
Adversarial Training Should Be Cast as a Non-Zero-Sum Game
International Conference on Learning Representations (ICLR), 2023
Avi Schwarzschild
Fabian Latorre
George J. Pappas
Hamed Hassani
Volkan Cevher
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416
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19 Jun 2023
On Achieving Optimal Adversarial Test Error
International Conference on Learning Representations (ICLR), 2023
Justin D. Li
Matus Telgarsky
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306
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13 Jun 2023
The Adversarial Consistency of Surrogate Risks for Binary Classification
Neural Information Processing Systems (NeurIPS), 2023
Natalie Frank
Jonathan Niles-Weed
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402
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17 May 2023
Cross-Entropy Loss Functions: Theoretical Analysis and Applications
International Conference on Machine Learning (ICML), 2023
Anqi Mao
M. Mohri
Yutao Zhong
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367
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14 Apr 2023
On Classification-Calibration of Gamma-Phi Losses
Annual Conference Computational Learning Theory (COLT), 2023
Yutong Wang
Clayton D. Scott
184
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14 Feb 2023
Learning to Reject with a Fixed Predictor: Application to Decontextualization
International Conference on Learning Representations (ICLR), 2023
Christopher Mohri
D. Andor
Eunsol Choi
Michael Collins
BDL
231
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22 Jan 2023
Gamma-convergence of a nonlocal perimeter arising in adversarial machine learning
Calculus of Variations and Partial Differential Equations (CVPDE), 2022
Leon Bungert
Kerrek Stinson
358
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28 Nov 2022
Rank-based Decomposable Losses in Machine Learning: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Shu Hu
Xin Wang
Siwei Lyu
391
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18 Jul 2022
The Consistency of Adversarial Training for Binary Classification
Natalie Frank
Jonathan Niles-Weed
AAML
295
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18 Jun 2022
Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification
Journal of machine learning research (JMLR), 2022
Natalie Frank
Jonathan Niles-Weed
AAML
390
17
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18 Jun 2022
Towards Consistency in Adversarial Classification
Neural Information Processing Systems (NeurIPS), 2022
Laurent Meunier
Raphael Ettedgui
Rafael Pinot
Y. Chevaleyre
Jamal Atif
AAML
185
12
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20 May 2022
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability
Neural Information Processing Systems (NeurIPS), 2022
Idan Attias
Steve Hanneke
Yishay Mansour
362
17
0
11 Feb 2022
On the Existence of the Adversarial Bayes Classifier (Extended Version)
Pranjal Awasthi
Natalie Frank
M. Mohri
473
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03 Dec 2021
A Finer Calibration Analysis for Adversarial Robustness
Pranjal Awasthi
Anqi Mao
M. Mohri
Yutao Zhong
AAML
272
35
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04 May 2021
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