| 2025 | ALT | Enhanced H-Consistency Bounds. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2025 | ICML | Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data. | Corinna Cortes, Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2025 | ICML | Mastering Multiple-Expert Routing: Realizable H-Consistency and Strong Guarantees for Learning to Defer. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2025 | ICML | Principled Algorithms for Optimizing Generalized Metrics in Binary Classification. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2024 | AISTATS | Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2024 | ALT | Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2024 | ICLR | Learning to Reject with a Fixed Predictor: Application to Decontextualization. | Christopher Mohri, Daniel Andor, Eunsol Choi, Michael Collins, Anqi Mao, Yutao Zhong |
| 2024 | ICML | Differentially Private Domain Adaptation with Theoretical Guarantees. | Raef Bassily, Corinna Cortes, Anqi Mao, Mehryar Mohri |
| 2024 | ICML | Regression with Multi-Expert Deferral. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2024 | ICML | H-Consistency Guarantees for Regression. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2024 | ISAIM | Principled Approaches for Learning to Defer with Multiple Experts. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2023 | AISTATS | Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness. | Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2023 | ICML | H-Consistency Bounds for Pairwise Misranking Loss Surrogates. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2023 | ICML | Cross-Entropy Loss Functions: Theoretical Analysis and Applications. | Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2022 | ICML | H-Consistency Bounds for Surrogate Loss Minimizers. | Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong |