Jieming Mao (毛杰明)
I am a research scientist at Google Research New York. Before that, I was a Warren Center Postdoctoral Fellow at University of Pennsylvania, hosted by Michael Kearns, Aaron Roth and Rakesh Vohra. I graduated with a PhD from Computer Science Department at Princeton University, advised by Mark Braverman.
Email: maojm517@gmail.com
Publications:
2024:
Autobidder's Dilemma: Why More Sophisticated Autobidders Lead to Worse Auction Efficiency
with Yuan Deng, Vahab Mirrokni, Hanrui Zhang and Song Zuo. NeurIPS 2024
Efficiency of the First-Price Auction in the Autobidding World
with Yuan Deng, Vahab Mirrokni, Hanrui Zhang and Song Zuo. NeurIPS 2024 [arXiv]
Optimal Mechanisms for a Value Maximizer: The Futility of Screening Targets
with Santiago Balseiro, Yuan Deng, Vahab Mirrokni and Song Zuo. EC 2024 [ssrn]
Non-uniform Bid-scaling and Equilibria for Different Auctions: An Empirical Study
with Yuan Deng, Vahab Mirrokni, Yifeng Teng and Song Zuo. TheWebConf 2024 [arXiv]
Efficiency of the Generalized Second-Price Auction for Value Maximizers
with Yuan Deng, Mohammad Mahdian, Vahab Mirrokni, Hanrui Zhang and Song Zuo. TheWebConf 2024 [arXiv]
2023:
Regret Minimization with Noisy Observations
with Mohammad Mahdian and Kangning Wang. EC 2023 [arXiv]
Autobidding Auctions in the Presence of User Costs
with Yuan Deng, Vahab Mirrokni, Hanrui Zhang and Song Zuo. TheWebConf 2023 [arXiv]
Differentially Private Continual Releases of Streaming Frequency Moment Estimations
with Alessandro Epasto, Andres Munoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, and Peilin Zhong ITCS 2023 [arXiv]
Optimal Pricing Schemes for an Impatient Buyer
with Yuan Deng, Balasubramanian Sivan and Kangning Wang. SODA 2023 [arXiv]
2022:
Optimal Mechanism for Value Maximizers with Budget Constraints via Target Clipping
with Santiago Balseiro, Yuan Deng, Vahab Mirrokni and Song Zuo. EC 2022 [ssrn]
Approximately Efficient Bilateral Trade
with Yuan Deng, Balasubramanian Sivan and Kangning Wang. STOC 2022 [arXiv]
Shuffle Private Stochastic Convex Optimization
with Albert Cheu, Matthew Joseph and Binghui Peng. ICLR 2022 [arXiv]
Interactive Communication in Bilateral Trade
with Renato Paes Leme and Kangning Wang. ITCS 2022 [arXiv]
2021:
Robust Auction Design in the Auto-bidding World
with Santiago Balseiro, Yuan Deng, Vahab Mirrokni and Song Zuo. NeurIPS 2021 [arXiv]
Welfare-maximizing Guaranteed Dashboard Mechanisms
with Yuan Deng, Jason Hartline and Balasubramanian Sivan. EC 2021 [ssrn]
The Landscape of Aubobidding Auctions: Value versus Utility Maximization
with Santiago Balseiro, Yuan Deng, Vahab Mirrokni and Song Zuo. EC 2021 [ssrn]
Towards Efficient Auctions in an Auto-Bidding World
with Yuan Deng, Vahab Mirrokni and Song Zuo. TheWebConf 2021 [arXiv]
Connecting Robust Shuffle Privacy and Pan-Privacy
with Victor Balcer, Albert Cheu and Matthew Joseph. SODA 2021 [arXiv]
2020:
Smoothly Bounding User Contributions in Differential Privacy
with Alessandro Epasto, Mohammad Mahdian, Vahab Mirrokni and Lijie Ren. NeurIPS 2020
Pan-Private Uniformity Testing
with Kareem Amin and Matthew Joseph. PriML 2019, COLT 2020 [arXiv]
Incentivizing Exploration with Selective Data Disclosure
with Nicole Immorlica, Aleksandrs Slivkins and Zhiwei Steven Wu. EC 2020 [arXiv]
Exponential Separations in Local Differential Privacy Through Communication Complexity
with Matthew Joseph and Aaron Roth. SODA 2020, invited to TALG Special Issue for SODA 2020 [arXiv]
2019:
Locally Private Gaussian Estimation
with Matthew Joseph, Janardhan Kulkarni and Zhiwei Steven Wu. NeurIPS 2019 [arXiv]
The Role of Interactivity in Local Differential Privacy
with Matthew Joseph, Seth Neel and Aaron Roth. FOCS 2019 [arXiv]
Differentially Private Fair Learning
with Matthew Jagielski, Michael Kearns, Alina Oprea, Aaron Roth, Saeed Sharifi-Malvajerdi and Jonathan Ullman. ICML 2019 [arXiv]
Multi-armed Bandit Problems with Strategic Arms
with Mark Braverman, Jon Schneider and Matthew Weinberg. COLT 2019 [arXiv]
Sorted Top-k in Rounds
with Mark Braverman and Yuval Peres. COLT 2019 [arXiv]
Bayesian Exploration with Heterogeneous Agents
with Nicole Immorlica, Aleksandrs Slivkins and Zhiwei Steven Wu. TheWebConf 2019 [arXiv]
Diversity and Exploration in Social Learning
with Nicole Immorlica and Christos Tzamos. TheWebConf 2019 [arXiv]
2018:
Contextual Pricing for Lipschitz Buyers
with Renato Paes Leme and Jon Schneider. NeurIPS 2018 [link]
Combinatorial Assortment Optimization
with Nicole Immorlica, Brendan Lucier, Vasilis Syrgkanis and Christos Tzamos. WINE 2018 [arXiv]
Selling to a No-Regret Buyer
with Mark Braverman, Jon Schneider and Matthew Weinberg. EC 2018 [arXiv]
Best Full Paper Award and Best Paper with a Student Lead Author
A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model
with Xi Chen and Yuanzhi Li. SODA 2018 [arXiv]
On Simultaneous Two-player Combinatorial Auctions
with Mark Braverman and Matthew Weinberg. SODA 2018 [arXiv]
2017 and before:
Competitive Analysis of the Top-K Ranking Problem
with Xi Chen, Sivakanth Gopi and Jon Schneider. SODA 2017 [arXiv]
Parallel Algoirithms for Select and Partition with Noisy Comparisons
with Mark Braverman and Matthew Weinberg. STOC 2016 [arXiv]
Coding for Interactive Communication Correcting Insertions and Deletions
with Mark Braverman, Ran Gelles and Rafail Ostrovsky. ICALP 2016 [arXiv]
Interpolating Between Truthful and Non-truthful Mechanisms for Combinatorial Auctions
with Mark Braverman and Matthew Weinberg. SODA 2016 [arXiv]
Near-optimal Bounds on Bounded-round Quantum Communication Complexity of Disjointness
with Mark Braverman, Ankit Garg, Young Kun Ko and Dave Touchette. FOCS 2015, QIP 2016 [ECCC]
Simulating Noisy Channel Interaction
with Mark Braverman. ITCS 2015 [ECCC]
Tighter Relations Between Sensitivity and Other Complexity Measures
with Andris Ambainis, Mohammad Bavarian, Yihan Gao, Xiaoming Sun and Song Zuo. ICALP 2014 [ECCC]
On the Sensitivity Complexity of Bipartite Graph Properties
with Yihan Gao, Xiaoming Sun and Song Zuo. Theor. Comput. Sci. 468: 83-91 (2013)