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Anqi Mao

23 papers · 2021–2025 · 5 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+6 more ↓ πŸ—ΊοΈ Taxonomy Completionist (20) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot Β· Silver πŸŒ‰ Interdisciplinary Bridge Β· Bronze πŸ”¬ Deep Specialist (18)
🀝 Dynamic Duo (22) πŸ”¬ Deep Specialist (18) ⚑ Prolific Year Β· Prolific πŸ”₯ Unstoppable Β· Bronze πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (76)

Venues

ICML (9) NeurIPS (9) AISTATS (2) ALT (2) ICLR (1)

Top co-authors

Mehryar Mohri (22) Yutao Zhong (22) Pranjal Awasthi (4) Corinna Cortes (3) Christopher Mohri (3) Daniel Andor (1) Raef Bassily (1) Natalie Frank (1) Michael Collins (1) Eunsol Choi (1)

Research topics

Machine Learning (23) Core Methods (21) Optimization & Theory (20) Learning Types Β· Machine Learning (7) Artificial Intelligence (3) Core AI (3) Deep Learning (2) Mathematics & Optimization (2) Learning Types Β· Deep Learning (2) Optimization (2) Application Areas (1)

Keywords

surrogate loss (19) h-consistency bound (8) consistency bound (7) multi-class classification (6) bayes consistency (4) adversarial robustness (3) hypothesis set (3) regression (3) h-consistency (2) deferral (2) learning to defer (2) consistency guarantee (2) excess error bound (2) neural network (2) abstention learning (2) learning theory (2) bipartite ranking (2) loss function (2) adversarial loss (2) classification loss (1)

Papers

Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data ICML 2025 Enhanced H-Consistency Bounds ALT 2025 Mastering Multiple-Expert Routing: Realizable H-Consistency and Strong Guarantees for Learning to Defer ICML 2025 Principled Algorithms for Optimizing Generalized Metrics in Binary Classification ICML 2025 H-Consistency Guarantees for Regression ICML 2024 A Universal Growth Rate for Learning with Smooth Surrogate Losses NeurIPS 2024 Cardinality-Aware Set Prediction and Top-k Classification NeurIPS 2024 Differentially Private Domain Adaptation with Theoretical Guarantees ICML 2024 Learning to Reject with a Fixed Predictor: Application to Decontextualization ICLR 2024 Multi-Label Learning with Stronger Consistency Guarantees NeurIPS 2024 Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms ALT 2024 Realizable H-Consistent and Bayes-Consistent Loss Functions for Learning to Defer NeurIPS 2024 Regression with Multi-Expert Deferral ICML 2024 Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention AISTATS 2024 H-Consistency Bounds: Characterization and Extensions NeurIPS 2023 H-Consistency Bounds for Pairwise Misranking Loss Surrogates ICML 2023 Cross-Entropy Loss Functions: Theoretical Analysis and Applications ICML 2023 Structured Prediction with Stronger Consistency Guarantees NeurIPS 2023 Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness AISTATS 2023 Two-Stage Learning to Defer with Multiple Experts NeurIPS 2023 H-Consistency Bounds for Surrogate Loss Minimizers ICML 2022 Multi-Class H-Consistency Bounds NeurIPS 2022 Calibration and Consistency of Adversarial Surrogate Losses NeurIPS 2021