Mingda Qiao

52 papers A* 16A 5Journal 29Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Computational and Statistical Hardness of Calibration Distance.
CoRR
Mingda Qiao
2026 A conf
Limitations of Membership Queries in Testable Learning.
ITCS
Jane Lange, Mingda Qiao
2025 A* conf
Leakage-Robust Bayesian Persuasion.
EC
Nika Haghtalab, Mingda Qiao, Kunhe Yang
2025 J jnl
Limitations of Membership Queries in Testable Learning.
CoRR
Jane Lange, Mingda Qiao
2025 J jnl
No Price Tags? No Problem: Query Strategies for Unpriced Information.
CoRR
Shivam Nadimpalli, Mingda Qiao, Ronitt Rubinfeld
2025 J jnl
Online Prediction with Limited Selectivity.
CoRR
Licheng Liu, Mingda Qiao
2025 J jnl
Optimal
CoRR
Mingda Qiao, Wei Zhang
2025 A* conf
Platforms for Efficient and Incentive-Aware Collaboration.
SODA
Nika Haghtalab, Mingda Qiao, Kunhe Yang
2025 J jnl
Sample-Adaptivity Tradeoff in On-Demand Sampling.
CoRR
Nika Haghtalab, Omar Montasser, Mingda Qiao
2025 A* conf
Truthfulness of Decision-Theoretic Calibration Measures.
COLT
Mingda Qiao, Eric Zhao
2025 J jnl
Truthfulness of Decision-Theoretic Calibration Measures.
CoRR
Mingda Qiao, Eric Zhao
2024 A conf
A Combinatorial Approach to Robust PCA.
ITCS
Weihao Kong, Mingda Qiao, Rajat Sen
2024 A* conf
Collaborative Learning with Different Labeling Functions.
ICML
Yuyang Deng, Mingda Qiao
2024 J jnl
Collaborative Learning with Different Labeling Functions.
CoRR
Yuyang Deng, Mingda Qiao
2024 J jnl
Leakage-Robust Bayesian Persuasion.
CoRR
Nika Haghtalab, Mingda Qiao, Kunhe Yang
2024 A* conf
On the Distance from Calibration in Sequential Prediction.
COLT
Mingda Qiao, Letian Zheng
2024 J jnl
On the Distance from Calibration in Sequential Prediction.
CoRR
Mingda Qiao, Letian Zheng
2024 J jnl
Platforms for Efficient and Incentive-Aware Collaboration.
CoRR
Nika Haghtalab, Mingda Qiao, Kunhe Yang
2024 A* conf
Truthfulness of Calibration Measures.
NeurIPS
Nika Haghtalab, Mingda Qiao, Kunhe Yang, Eric Zhao
2024 J jnl
Truthfulness of Calibration Measures.
CoRR
Nika Haghtalab, Mingda Qiao, Kunhe Yang, Eric Zhao
2023 J jnl
A Combinatorial Approach to Robust PCA.
CoRR
Weihao Kong, Mingda Qiao, Rajat Sen
2023 A conf
Online Pen Testing.
ITCS
Mingda Qiao, Gregory Valiant
2022 A* conf
A Fourier Approach to Mixture Learning.
NeurIPS
Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Kumar Avinava Dubey, Manzil Zaheer
2022 J jnl
A Fourier Approach to Mixture Learning.
CoRR
Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Avinava Dubey, Manzil Zaheer
2022 J jnl
Online Pen Testing.
CoRR
Mingda Qiao, Gregory Valiant
2022 J jnl
Open Problem: Properly learning decision trees in polynomial time?
CoRR
Guy Blanc, Jane Lange, Mingda Qiao, Li-Yang Tan
2022 J jnl
Properly Learning Decision Trees in almost Polynomial Time.
J. ACM
Guy Blanc, Jane Lange, Mingda Qiao, Li-Yang Tan
2021 — conf
Decision Tree Heuristics Can Fail, Even in the Smoothed Setting.
APPROX-RANDOM
Guy Blanc, Jane Lange, Mingda Qiao, Li-Yang Tan
2021 J jnl
Decision tree heuristics can fail, even in the smoothed setting.
CoRR
Guy Blanc, Jane Lange, Mingda Qiao, Li-Yang Tan
2021 A* conf
Exponential Weights Algorithms for Selective Learning.
COLT
Mingda Qiao, Gregory Valiant
2021 J jnl
Exponential Weights Algorithms for Selective Learning.
CoRR
Mingda Qiao, Gregory Valiant
2021 A* conf
Properly learning decision trees in almost polynomial time.
FOCS
Guy Blanc, Jane Lange, Mingda Qiao, Li-Yang Tan
2021 J jnl
Properly learning decision trees in almost polynomial time.
CoRR
Guy Blanc, Jane Lange, Mingda Qiao, Li-Yang Tan
2021 A* conf
Stronger calibration lower bounds via sidestepping.
STOC
Mingda Qiao, Gregory Valiant
2020 A* conf
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning.
ICLR
Jian Li, Xuanyuan Luo, Mingda Qiao
2020 J jnl
Stronger Calibration Lower Bounds via Sidestepping.
CoRR
Mingda Qiao, Gregory Valiant
2019 A* conf
A Theory of Selective Prediction.
COLT
Mingda Qiao, Gregory Valiant
2019 J jnl
A Theory of Selective Prediction.
CoRR
Mingda Qiao, Gregory Valiant
2019 A* conf
Low-Distortion Social Welfare Functions.
AAAI
Gerdus Benadè, Ariel D. Procaccia, Mingda Qiao
2019 J jnl
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning.
CoRR
Jian Li, Xuanyuan Luo, Mingda Qiao
2018 A* conf
Do Outliers Ruin Collaboration?
ICML
Mingda Qiao
2018 J jnl
Do Outliers Ruin Collaboration?
CoRR
Mingda Qiao
2018 A conf
Learning Discrete Distributions from Untrusted Batches.
ITCS
Mingda Qiao, Gregory Valiant
2017 — conf
Collaborative PAC Learning.
NIPS
Avrim Blum, Nika Haghtalab, Ariel D. Procaccia, Mingda Qiao
2017 J jnl
Learning Discrete Distributions from Untrusted Batches.
CoRR
Mingda Qiao, Gregory Valiant
2017 A conf
Nearly Instance Optimal Sample Complexity Bounds for Top-k Arm Selection.
AISTATS
Lijie Chen, Jian Li, Mingda Qiao
2017 J jnl
Nearly Instance Optimal Sample Complexity Bounds for Top-k Arm Selection.
CoRR
Lijie Chen, Jian Li, Mingda Qiao
2017 A* conf
Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration.
COLT
Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang
2017 J jnl
Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration.
CoRR
Lijie Chen, Anupam Gupta, Jian Li, Mingda Qiao, Ruosong Wang
2017 J jnl
Practical Algorithms for Best-K Identification in Multi-Armed Bandits.
CoRR
Haotian Jiang, Jian Li, Mingda Qiao
2017 A* conf
Towards Instance Optimal Bounds for Best Arm Identification.
COLT
Lijie Chen, Jian Li, Mingda Qiao
2016 J jnl
Towards Instance Optimal Bounds for Best Arm Identification.
CoRR
Lijie Chen, Jian Li, Mingda Qiao