Yutao Zhong

CoRR, May, 2026

Generalized Distributional Alignment Games for Unbiased Answer-Level Fine-Tuning.

[BibT_eX]

[DOI]

Jon Schneider

CoRR, May, 2026

Linear-Core Surrogates: Smooth Loss Functions with Linear Rates for Classification and Structured Prediction.

[BibT_eX]

[DOI]

CoRR, April, 2026

Mind the Gap: Structure-Aware Consistency in Preference Learning.

[BibT_eX]

[DOI]

CoRR, April, 2026

Optimized Deferral for Imbalanced Settings.

[BibT_eX]

[DOI]

CoRR, April, 2026

A Theoretical Framework for Modular Learning of Robust Generative Models.

[BibT_eX]

[DOI]

Corinna Cortes

CoRR, February, 2026

2025

Fundamental Novel Consistency Theory: <i>H</i>-Consistency Bounds.

[BibT_eX]

[DOI]

CoRR, December, 2025

Beyond Tsybakov: Model Margin Noise and ℋ-Consistency Bounds.

[BibT_eX]

[DOI]

CoRR, November, 2025

Budgeted Multiple-Expert Deferral.

[BibT_eX]

[DOI]

CoRR, October, 2025

Mastering Multiple-Expert Routing: Realizable <i>H</i>-Consistency and Strong Guarantees for Learning to Defer.

[BibT_eX]

[DOI]

CoRR, June, 2025

Improved Balanced Classification with Theoretically Grounded Loss Functions.

[BibT_eX]

[DOI]

Corinna Cortes

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Principled Algorithms for Optimizing Generalized Metrics in Binary Classification.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Mastering Multiple-Expert Routing: Realizable H-Consistency and Strong Guarantees for Learning to Defer.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Enhanced H-Consistency Bounds.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Algorithmic Learning Theory, 2025

2024

Top-k Classification and Cardinality-Aware Prediction.

[BibT_eX]

[DOI]

CoRR, 2024

Realizable H-Consistent and Bayes-Consistent Loss Functions for Learning to Defer.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

A Universal Growth Rate for Learning with Smooth Surrogate Losses.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Multi-Label Learning with Stronger Consistency Guarantees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Cardinality-Aware Set Prediction and Top-$k$ Classification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Principled Approaches for Learning to Defer with Multiple Experts.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence and Image Analysis, 2024

H-Consistency Guarantees for Regression.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Regression with Multi-Expert Deferral.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning to Reject with a Fixed Predictor: Application to Decontextualization.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Ranking with Abstention.

[BibT_eX]

[DOI]

CoRR, 2023

Two-Stage Learning to Defer with Multiple Experts.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Structured Prediction with Stronger Consistency Guarantees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

H-Consistency Bounds: Characterization and Extensions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Cross-Entropy Loss Functions: Theoretical Analysis and Applications.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

H-Consistency Bounds for Pairwise Misranking Loss Surrogates.

[BibT_eX]

[DOI]