New upper bound on block sensitivity and certificate complexity in terms of sensitivity. - Andris Ambainis; Yihan Gao; Jieming Mao; Xiaoming Sun 001; Song Zuo (CoRR, 2013)

On the sensitivity complexity of bipartite graph properties. - Yihan Gao; Jieming Mao; Xiaoming Sun 001; Song Zuo (Theor. Comput. Sci., 2013)

Tighter Relations Between Sensitivity and Other Complexity Measures. - Andris Ambainis; Mohammad Bavarian; Yihan Gao; Jieming Mao; Xiaoming Sun 001; Song Zuo (Electron. Colloquium Comput. Complex., 2014)

Simulating Noisy Channel Interaction. - Mark Braverman; Jieming Mao (Electron. Colloquium Comput. Complex., 2014)

Interpolating Between Truthful and non-Truthful Mechanisms for Combinatorial Auctions. - Mark Braverman; Jieming Mao; S. Matthew Weinberg (SODA, 2016)

Parallel algorithms for select and partition with noisy comparisons. - Mark Braverman; Jieming Mao; S. Matthew Weinberg (STOC, 2016)

Competitive analysis of the top-K ranking problem. - Xi Chen 010; Sivakanth Gopi; Jieming Mao; Jon Schneider (CoRR, 2016)

Competitive analysis of the top-K ranking problem. - Xi Chen 010; Sivakanth Gopi; Jieming Mao; Jon Schneider (SODA, 2017)

A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model. - Xi Chen 010; Yuanzhi Li; Jieming Mao (CoRR, 2017)

Coding for Interactive Communication Correcting Insertions and Deletions. - Mark Braverman; Ran Gelles; Jieming Mao; Rafail Ostrovsky (IEEE Trans. Inf. Theory, 2017)

Contextual Pricing for Lipschitz Buyers. - Jieming Mao; Renato Paes Leme; Jon Schneider (NeurIPS, 2018)

Selling to a No-Regret Buyer. - Mark Braverman; Jieming Mao; Jon Schneider; S. Matthew Weinberg (EC, 2018)

On Simultaneous Two-player Combinatorial Auctions. - Mark Braverman; Jieming Mao; S. Matthew Weinberg (SODA, 2018)

A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model. - Xi Chen 010; Yuanzhi Li; Jieming Mao (SODA, 2018)

Incentivizing Exploration with Unbiased Histories. - Nicole Immorlica; Jieming Mao; Aleksandrs Slivkins; Zhiwei Steven Wu (CoRR, 2018)

Near-Optimal Bounds on the Bounded-Round Quantum Communication Complexity of Disjointness. - Mark Braverman; Ankit Garg; Young Kun-Ko; Jieming Mao; Dave Touchette (SIAM J. Comput., 2018)

Optimal Instance Adaptive Algorithm for the Top-K Ranking Problem. - Xi Chen 010; Sivakanth Gopi; Jieming Mao; Jon Schneider (IEEE Trans. Inf. Theory, 2018)

Algorithms in Strategic or Noisy Environments - Jieming Mao (2018)

Sorted Top-k in Rounds. - Mark Braverman; Jieming Mao; Yuval Peres (COLT, 2019)

Multi-armed Bandit Problems with Strategic Arms. - Mark Braverman; Jieming Mao; Jon Schneider; S. Matthew Weinberg (COLT, 2019)

The Role of Interactivity in Local Differential Privacy. - Matthew Joseph; Jieming Mao; Seth Neel; Aaron Roth 001 (FOCS, 2019)

Differentially Private Fair Learning. - Matthew Jagielski; Michael J. Kearns; Jieming Mao; Alina Oprea; Aaron Roth 001; Saeed Sharifi-Malvajerdi; Jonathan R. Ullman (ICML, 2019)

Locally Private Gaussian Estimation. - Matthew Joseph; Janardhan Kulkarni; Jieming Mao; Zhiwei Steven Wu (NeurIPS, 2019)

Bayesian Exploration with Heterogeneous Agents. - Nicole Immorlica; Jieming Mao; Aleksandrs Slivkins; Zhiwei Steven Wu (WWW, 2019)

Diversity and Exploration in Social Learning. - Nicole Immorlica; Jieming Mao; Christos Tzamos (WWW, 2019)

Exponential Separations in Local Differential Privacy Through Communication Complexity. - Matthew Joseph; Jieming Mao; Aaron Roth 001 (CoRR, 2019)

Pan-Private Uniformity Testing. - Kareem Amin 002; Matthew Joseph; Jieming Mao (COLT, 2020)

Smoothly Bounding User Contributions in Differential Privacy. - Alessandro Epasto; Mohammad Mahdian; Jieming Mao; Vahab S. Mirrokni; Lijie Ren (NeurIPS, 2020)

Incentivizing Exploration with Selective Data Disclosure. - Nicole Immorlica; Jieming Mao; Aleksandrs Slivkins; Zhiwei Steven Wu (EC, 2020)

Exponential Separations in Local Differential Privacy. - Matthew Joseph; Jieming Mao; Aaron Roth 001 (SODA, 2020)

Robust Auction Design in the Auto-bidding World. - Santiago R. Balseiro; Yuan Deng; Jieming Mao; Vahab S. Mirrokni; Song Zuo (NeurIPS, 2021)

The Landscape of Auto-bidding Auctions: Value versus Utility Maximization. - Santiago R. Balseiro; Yuan Deng; Jieming Mao; Vahab S. Mirrokni; Song Zuo (EC, 2021)

Welfare-maximizing Guaranteed Dashboard Mechanisms. - Yuan Deng; Jason D. Hartline; Jieming Mao; Balasubramanian Sivan (EC, 2021)

Connecting Robust Shuffle Privacy and Pan-Privacy. - Victor Balcer; Albert Cheu; Matthew Joseph; Jieming Mao (SODA, 2021)

Towards Efficient Auctions in an Auto-bidding World. - Yuan Deng; Jieming Mao; Vahab S. Mirrokni; Song Zuo (WWW, 2021)

Combinatorial Assortment Optimization. - Nicole Immorlica; Brendan Lucier; Jieming Mao; Vasilis Syrgkanis; Christos Tzamos (ACM Trans. Economics and Comput., 2021)

Shuffle Private Stochastic Convex Optimization. - Albert Cheu; Matthew Joseph; Jieming Mao; Binghui Peng (ICLR, 2022)

Interactive Communication in Bilateral Trade. - Jieming Mao; Renato Paes Leme; Kangning Wang 001 (ITCS, 2022)

Optimal Mechanisms for Value Maximizers with Budget Constraints via Target Clipping. - Santiago R. Balseiro; Yuan Deng; Jieming Mao; Vahab S. Mirrokni; Song Zuo (EC, 2022)

Approximately efficient bilateral trade. - Yuan Deng; Jieming Mao; Balasubramanian Sivan; Kangning Wang 001 (STOC, 2022)

Exponential Separations in Local Privacy. - Matthew Joseph; Jieming Mao; Aaron Roth 001 (ACM Trans. Algorithms, 2022)

Differentially Private Continual Releases of Streaming Frequency Moment Estimations. - Alessandro Epasto; Jieming Mao; Andres Muñoz Medina; Vahab Mirrokni; Sergei Vassilvitskii; Peilin Zhong (ITCS, 2023)

Regret Minimization with Noisy Observations. - Mohammad Mahdian; Jieming Mao; Kangning Wang 001 (EC, 2023)

Optimal Pricing Schemes for an Impatient Buyer. - Yuan Deng; Jieming Mao; Balasubramanian Sivan; Kangning Wang 001 (SODA, 2023)

Autobidding Auctions in the Presence of User Costs. - Yuan Deng; Jieming Mao; Vahab Mirrokni; Hanrui Zhang 001; Song Zuo (WWW, 2023)

Learning across Data Owners with Joint Differential Privacy. - Yangsibo Huang; Haotian Jiang; Daogao Liu; Mohammad Mahdian; Jieming Mao; Vahab Mirrokni (CoRR, 2023)

Leveraging Spatial Characteristics in Trajectory Compression: An Angle-Based Bounded-Error Method. - Yongcheng Liu; Xue Ouyang; Huan Zhou 006; Weichen Peng; Jieming Mao; Yongke Pan (ICPCSEE (2), 2024)

Autobidder's Dilemma: Why More Sophisticated Autobidders Lead to Worse Auction Efficiency. - Yuan Deng; Jieming Mao; Vahab Mirrokni; Hanrui Zhang 001; Song Zuo (NeurIPS, 2024)

Efficiency of the First-Price Auction in the Autobidding World. - Yuan Deng; Jieming Mao; Vahab Mirrokni; Hanrui Zhang 001; Song Zuo (NeurIPS, 2024)

Optimal Mechanisms for a Value Maximizer: The Futility of Screening Targets. - Santiago R. Balseiro; Yuan Deng; Jieming Mao; Vahab Mirrokni; Song Zuo (EC, 2024)

Efficiency of the Generalized Second-Price Auction for Value Maximizers. - Yuan Deng; Mohammad Mahdian; Jieming Mao; Vahab Mirrokni; Hanrui Zhang 001; Song Zuo (WWW, 2024)

Non-uniform Bid-scaling and Equilibria for Different Auctions: An Empirical Study. - Yuan Deng; Jieming Mao; Vahab Mirrokni; Yifeng Teng; Song Zuo (WWW, 2024)

Retraining with Predicted Hard Labels Provably Increases Model Accuracy. - Rudrajit Das; Inderjit S. Dhillon; Alessandro Epasto; Adel Javanmard; Jieming Mao; Vahab Mirrokni; Sujay Sanghavi; Peilin Zhong (CoRR, 2024)

Auto-Bidding and Auctions in Online Advertising: A Survey. - Gagan Aggarwal; Ashwinkumar Badanidiyuru; Santiago R. Balseiro; Kshipra Bhawalkar; Yuan Deng; Zhe Feng 004; Gagan Goel; Christopher Liaw; Haihao Lu; Mohammad Mahdian; Jieming Mao; Aranyak Mehta; et al. (SIGecom Exch., 2024)

Approximately Efficient Bilateral Trade with Samples. - Yuan Deng; Jieming Mao; Balasubramanian Sivan; Kangning Wang 001; Jinzhao Wu (EC, 2025)

A New Benchmark for Online Learning with Budget-Balancing Constraints. - Mark Braverman; Jingyi Liu; Jieming Mao; Jon Schneider; Eric Xue 001 (CoRR, 2025)

Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model. - Rachel Cummings; Alessandro Epasto; Jieming Mao; Tamalika Mukherjee; Tingting Ou; Peilin Zhong (CoRR, 2025)

Position Auctions in AI-Generated Content. - Santiago R. Balseiro; Kshipra Bhawalkar; Yuan Deng; Zhe Feng 004; Jieming Mao; Aranyak Mehta; Vahab Mirrokni; Renato Paes Leme; Di Wang 005; Song Zuo (CoRR, 2025)