Qiao, Mingda

17 publications

NeurIPS 2025 Online Prediction with Limited Selectivity Licheng Liu, Mingda Qiao

NeurIPS 2025 Sample-Adaptivity Tradeoff in On-Demand Sampling Nika Haghtalab, Omar Montasser, Mingda Qiao

COLT 2025 Truthfulness of Decision-Theoretic Calibration Measures Mingda Qiao, Eric Zhao

ICML 2024 Collaborative Learning with Different Labeling Functions Yuyang Deng, Mingda Qiao

COLT 2024 On the Distance from Calibration in Sequential Prediction Mingda Qiao, Letian Zheng

NeurIPS 2024 Truthfulness of Calibration Measures Nika Haghtalab, Mingda Qiao, Kunhe Yang, Eric Zhao

NeurIPS 2022 A Fourier Approach to Mixture Learning Mingda Qiao, Guru Guruganesh, Ankit Rawat, Kumar Avinava Dubey, Manzil Zaheer

COLT 2022 Open Problem: Properly Learning Decision Trees in Polynomial Time? Guy Blanc, Jane Lange, Mingda Qiao, Li-Yang Tan

COLT 2021 Exponential Weights Algorithms for Selective Learning Mingda Qiao, Gregory Valiant

ICLR 2020 On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning Jian Li, Xuanyuan Luo, Mingda Qiao

COLT 2019 A Theory of Selective Prediction Mingda Qiao, Gregory Valiant

AAAI 2019 Low-Distortion Social Welfare Functions Gerdus Benadè, Ariel D. Procaccia, Mingda Qiao

ICML 2018 Do Outliers Ruin Collaboration? Mingda Qiao

NeurIPS 2017 Collaborative PAC Learning Avrim Blum, Nika Haghtalab, Ariel D Procaccia, Mingda Qiao

AISTATS 2017 Nearly Instance Optimal Sample Complexity Bounds for Top-K Arm Selection Lijie Chen, Jian Li, Mingda Qiao

COLT 2017 Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang

COLT 2017 Towards Instance Optimal Bounds for Best Arm Identification Lijie Chen, Jian Li, Mingda Qiao