Optimal k-Secretary with Logarithmic Memory
Mingda Qiao, Wei Zhang
[arXiv]
Leakage-Robust Bayesian Persuasion. EC 2025
Nika Haghtalab, Mingda Qiao, Kunhe Yang
Truthfulness of Decision-Theoretic Calibration Measures. COLT 2025
Mingda Qiao, Eric Zhao
[arXiv][conference version][Eric's blog post]
Platforms for Efficient and Incentive-Aware Collaboration. SODA 2025
Nika Haghtalab, Mingda Qiao, Kunhe Yang
Truthfulness of Calibration Measures. NeurIPS 2024
Nika Haghtalab, Mingda Qiao, Kunhe Yang, Eric Zhao
On the Distance from Calibration in Sequential Prediction. COLT 2024
Mingda Qiao, Letian Zheng
Collaborative Learning with Different Labeling Functions. ICML 2024
Yuyang Deng, Mingda Qiao
[arXiv][conference version][video]
A Combinatorial Approach to Robust PCA. ITCS 2024
Weihao Kong, Mingda Qiao, Rajat Sen
[arXiv][conference version][video]
Online Pen Testing. ITCS 2023
Mingda Qiao, Gregory Valiant
[arXiv][conference version][video]
A Fourier Approach to Mixture Learning. NeurIPS 2022
Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Kumar Avinava Dubey, Manzil Zaheer
Open Problem: Properly Learning Decision Trees in Polynomial Time? COLT 2022 (Open Problem)
Guy Blanc, Jane Lange, Mingda Qiao, Li-Yang Tan
Properly Learning Decision Trees in Almost Polynomial Time. FOCS 2021
Guy Blanc, Jane Lange, Mingda Qiao, Li-Yang Tan
[arXiv][conference version][journal version][video][Guy's TCS+ talk]
Invited to FOCS 2021 special issue
Journal of the ACM, 2022
Decision Tree Heuristics Can Fail, Even in the Smoothed Setting. RANDOM 2021
Guy Blanc, Jane Lange, Mingda Qiao, Li-Yang Tan
[arXiv][conference version][video]
Exponential Weights Algorithms for Selective Learning. COLT 2021
Mingda Qiao, Gregory Valiant
[arXiv][conference version][video]
Stronger Calibration Lower Bounds via Sidestepping. STOC 2021
Mingda Qiao, Gregory Valiant
[arXiv][conference version][video]
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning. ICLR 2020
Jian Li, Xuanyuan Luo, Mingda Qiao
A Theory of Selective Prediction. COLT 2019
Mingda Qiao, Gregory Valiant
Low-Distortion Social Welfare Functions. AAAI 2019
Gerdus Benade, Ariel D. Procaccia, Mingda Qiao
Do Outliers Ruin Collaboration? ICML 2018
Mingda Qiao
Learning Discrete Distributions from Untrusted Batches. ITCS 2018
Mingda Qiao, Gregory Valiant
Collaborative PAC Learning. NIPS 2017
Avrim Blum, Nika Haghtalab, Ariel D. Procaccia, Mingda Qiao
Towards Instance Optimal Bounds for Best Arm Identification. COLT 2017
Lijie Chen, Jian Li, Mingda Qiao
Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration. COLT 2017
Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang
Practical Algorithms for Best-K Identification in Multi-Armed Bandits
Haotian Jiang, Jian Li, Mingda Qiao
[arXiv]
Nearly Instance Optimal Sample Complexity Bounds for Top-k Arm Selection. AISTATS 2017
Lijie Chen, Jian Li, Mingda Qiao