Cross-entropy loss functions: Theoretical analysis and applications A Mao, M Mohri, Y Zhong
International Conference on Machine Learning, 23803-23828, 2023
397 2023 Calibration and consistency of adversarial surrogate losses P Awasthi, N Frank, A Mao, M Mohri, Y Zhong
Advances in Neural Information Processing Systems 34, 9804-9815, 2021
54 2021 Two-stage learning to defer with multiple experts A Mao, C Mohri, M Mohri, Y Zhong
Advances in neural information processing systems 36, 2023
40 2023 H-consistency bounds for surrogate loss minimizers P Awasthi, A Mao, M Mohri, Y Zhong
International Conference on Machine Learning, 1117-1174, 2022
39 2022 Theoretically grounded loss functions and algorithms for adversarial robustness P Awasthi, A Mao, M Mohri, Y Zhong
International Conference on Artificial Intelligence and Statistics, 10077-10094, 2023
37 2023 Multi-Class -Consistency Bounds P Awasthi, A Mao, M Mohri, Y Zhong
Advances in neural information processing systems 35, 782-795, 2022
35 2022 A finer calibration analysis for adversarial robustness P Awasthi, A Mao, M Mohri, Y Zhong
arXiv preprint arXiv:2105.01550, 2021
34 2021 DC-programming for neural network optimizations P Awasthi, A Mao, M Mohri, Y Zhong
Journal of Global Optimization, 1-17, 2024
29 2024 Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms A Mao, M Mohri, Y Zhong
International Conference on Algorithmic Learning Theory, 822-867, 2024
27 2024 Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention A Mao, M Mohri, Y Zhong
International Conference on Artificial Intelligence and Statistics, 4753-4761, 2024
26 2024 Principled Approaches for Learning to Defer with Multiple Experts A Mao, M Mohri, Y Zhong
International Symposium on Artificial Intelligence and Mathematics, 2024
25 2024 Ranking with Abstention A Mao, M Mohri, Y Zhong
ICML Workshop on the Many Facets of Preference-Based Learning, 2023
22 2023 -Consistency Bounds for Pairwise Misranking Loss SurrogatesA Mao, M Mohri, Y Zhong
International Conference on Machine Learning, 23743-23802, 2023
22 2023 Learning to reject with a fixed predictor: Application to decontextualization C Mohri, D Andor, E Choi, M Collins, A Mao, Y Zhong
International Conference on Learning Representations, 2024
20 2024 -Consistency Bounds: Characterization and ExtensionsA Mao, M Mohri, Y Zhong
Advances in Neural Information Processing Systems 36, 4470-4508, 2023
20 2023 Structured prediction with stronger consistency guarantees A Mao, M Mohri, Y Zhong
Advances in Neural Information Processing Systems 36, 46903-46937, 2023
18 2023 Regression with Multi-Expert Deferral A Mao, M Mohri, Y Zhong
International Conference on Machine Learning, 34738-34759, 2024
13 2024 -Consistency Guarantees for RegressionA Mao, M Mohri, Y Zhong
International Conference on Machine Learning, 34712-34737, 2024
10 2024 Top- Classification and Cardinality-Aware Prediction A Mao, M Mohri, Y Zhong
arXiv preprint arXiv:2403.19625, 2024
9 2024 A Universal Growth Rate for Learning with Smooth Surrogate Losses A Mao, M Mohri, Y Zhong
Advances in Neural Information Processing Systems 37, 2024
7 2024