Understanding PPA-Completeness. - Xiaotie Deng; Zhe Feng 004; Zhengyang Liu 002; Qi Qi 003 (Electron. Colloquium Comput. Complex., 2015)

Power-Law Distributions in a Two-Sided Market and Net Neutrality. - Xiaotie Deng; Zhe Feng 004; Christos H. Papadimitriou (WINE, 2016)

Optimal Auctions through Deep Learning. - Paul Dütting; Zhe Feng 004; Harikrishna Narasimhan; David C. Parkes (CoRR, 2017)

Octahedral Tucker is PPA-Complete. - Xiaotie Deng; Zhe Feng 004; Rucha Kulkarni (Electron. Colloquium Comput. Complex., 2017)

Deep Learning for Revenue-Optimal Auctions with Budgets. - Zhe Feng 004; Harikrishna Narasimhan; David C. Parkes (AAMAS, 2018)

Learning to Bid Without Knowing your Value. - Zhe Feng 004; Chara Podimata; Vasilis Syrgkanis (EC, 2018)

An Adaptive Independence Sampler MCMC Algorithm for Bayesian Inferences of Functions. - Zhe Feng 004; Jinglai Li (SIAM J. Sci. Comput., 2018)

Online Learning for Measuring Incentive Compatibility in Ad Auctions? - Zhe Feng 004; Okke Schrijvers; Eric Sodomka (WWW, 2019)

The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation. - Zhe Feng 004; David C. Parkes; Haifeng Xu (ICML, 2020)

Reserve Price Optimization for First Price Auctions. - Zhe Feng 004; Sébastien Lahaie; Jon Schneider; Jinchao Ye (CoRR, 2020)

Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions. - Zhe Feng 004; Guru Guruganesh; Christopher Liaw; Aranyak Mehta; Abhishek Sethi (AAAI, 2021)

Reserve Price Optimization for First Price Auctions in Display Advertising. - Zhe Feng 004; Sébastien Lahaie; Jon Schneider; Jinchao Ye (ICML, 2021)

Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss. - Vincent Conitzer; Zhe Feng 004; David C. Parkes; Eric Sodomka (WINE, 2021)

Optimal auctions through deep learning. - Paul Dütting; Zhe Feng 004; Harikrishna Narasimhan; David C. Parkes; Sai Srivatsa Ravindranath (Commun. ACM, 2021)

Deep Learning for Two-Sided Matching. - Sai Srivatsa Ravindranath; Zhe Feng 004; Shira Li; Jonathan Ma; Scott Duke Kominers; David C. Parkes (CoRR, 2021)

Robust Clearing Price Mechanisms for Reserve Price Optimization. - Zhe Feng 004; Sébastien Lahaie (CoRR, 2021)

Understanding PPA-completeness. - Xiaotie Deng; Jack R. Edmonds; Zhe Feng 004; Zhengyang Liu 002; Qi Qi 003; Zeying Xu (J. Comput. Syst. Sci., 2021)

A Context-Integrated Transformer-Based Neural Network for Auction Design. - Zhijian Duan 001; Jingwu Tang; Yutong Yin; Zhe Feng 004; Xiang Yan; Manzil Zaheer; Xiaotie Deng (ICML, 2022)

Incrementality Bidding via Reinforcement Learning under Mixed and Delayed Rewards. - Ashwinkumar Badanidiyuru Varadaraja; Zhe Feng 004; Tianxi Li; Haifeng Xu (NeurIPS, 2022)

Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning. - Jibang Wu; Zixuan Zhang; Zhe Feng 004; Zhaoran Wang 001; Zhuoran Yang; Michael I. Jordan; Haifeng Xu (EC, 2022)

Improved Online Learning Algorithms for CTR Prediction in Ad Auctions. - Zhe Feng 004; Christopher Liaw; Zixin Zhou (ICML, 2023)

Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts. - Chaoqi Wang; Ziyu Ye; Zhe Feng 004; Ashwinkumar Badanidiyuru Varadaraja; Haifeng Xu (NeurIPS, 2023)

Learning to Bid in Contextual First Price Auctions✱. - Ashwinkumar Badanidiyuru; Zhe Feng 004; Guru Guruganesh (WWW, 2023)

Online Bidding Algorithms for Return-on-Spend Constrained Advertisers✱. - Zhe Feng 004; Swati Padmanabhan; Di Wang 005 (WWW, 2023)

User Response in Ad Auctions: An MDP Formulation of Long-Term Revenue Optimization. - Yang Cai 001; Zhe Feng 004; Christopher Liaw; Aranyak Mehta (CoRR, 2023)

Joint Feedback Loop for Spend and Return-On-Spend Constraints. - Santiago R. Balseiro; Kshipra Bhawalkar; Zhe Feng 004; Haihao Lu; Vahab Mirrokni; Balasubramanian Sivan; Di Wang 005 (CoRR, 2023)

The Average-Value Allocation Problem. - Kshipra Bhawalkar; Zhe Feng 004; Anupam Gupta 001; Aranyak Mehta; David Wajc; Di Wang 005 (APPROX/RANDOM, 2024)

Learning Thresholds with Latent Values and Censored Feedback. - Jiahao Zhang; Tao Lin 013; Weiqiang Zheng; Zhe Feng 004; Yifeng Teng; Xiaotie Deng (ICLR, 2024)

A Field Guide for Pacing Budget and ROS Constraints. - Santiago R. Balseiro; Kshipra Bhawalkar; Zhe Feng 004; Haihao Lu; Vahab Mirrokni; Balasubramanian Sivan; Di Wang 005 (ICML, 2024)

Auctions with LLM Summaries. - Avinava Dubey; Zhe Feng 004; Rahul Kidambi; Aranyak Mehta; Di Wang 005 (KDD, 2024)

User Response in Ad Auctions: An MDP Formulation of Long-term Revenue Optimization. - Yang Cai 001; Zhe Feng 004; Christopher Liaw; Aranyak Mehta; Grigoris Velegkas (WWW, 2024)

How to Strategize Human Content Creation in the Era of GenAI? - Seyed A. Esmaeili; Kshipra Bhawalkar; Zhe Feng 004; Di Wang 005; Haifeng Xu (CoRR, 2024)

Deep Reinforcement Learning for Sequential Combinatorial Auctions. - Sai Srivatsa Ravindranath; Zhe Feng 004; Di Wang 005; Manzil Zaheer; Aranyak Mehta; David C. Parkes (CoRR, 2024)

Optimal Auctions through Deep Learning: Advances in Differentiable Economics. - Paul Dütting; Zhe Feng 004; Harikrishna Narasimhan; David C. Parkes; Sai Srivatsa Ravindranath (J. ACM, 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)

Online Bidding under RoS Constraints without Knowing the Value. - Sushant Vijayan; Zhe Feng 004; Swati Padmanabhan; Karthikeyan Shanmugam; Arun Sai Suggala; Di Wang 005 (WWW, 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)