Zhe Feng

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 46

Top Topics

Bayesian Inference

Combinatorial Auctions

Incentive Compatibility

Top Venues

Publications

Kshipra Bhawalkar, Zhe Feng, Anupam Gupta, Aranyak Mehta, David Wajc, Di Wang
The Average-Value Allocation Problem. CoRR (2024)
Yang Cai, Zhe Feng, Christopher Liaw, Aranyak Mehta, Grigoris Velegkas
User Response in Ad Auctions: An MDP Formulation of Long-term Revenue Optimization. WWW (2024)
Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath
Optimal Auctions through Deep Learning: Advances in Differentiable Economics. J. ACM 71 (1) (2024)
Avinava Dubey, Zhe Feng, Rahul Kidambi, Aranyak Mehta, Di Wang
Auctions with LLM Summaries. KDD (2024)
Seyed A. Esmaeili, Kshipra Bhawalkar, Zhe Feng, Di Wang, Haifeng Xu
How to Strategize Human Content Creation in the Era of GenAI? CoRR (2024)
Kumar Avinava Dubey, Zhe Feng, Rahul Kidambi, Aranyak Mehta, Di Wang
Auctions with LLM Summaries. CoRR (2024)
Jiahao Zhang, Tao Lin, Weiqiang Zheng, Zhe Feng, Yifeng Teng, Xiaotie Deng
Learning Thresholds with Latent Values and Censored Feedback. ICLR (2024)
Sai Srivatsa Ravindranath, Zhe Feng, Di Wang, Manzil Zaheer, Aranyak Mehta, David C. Parkes
Deep Reinforcement Learning for Sequential Combinatorial Auctions. CoRR (2024)
Yang Cai, Zhe Feng, Christopher Liaw, Aranyak Mehta
User Response in Ad Auctions: An MDP Formulation of Long-Term Revenue Optimization. CoRR (2023)
Ashwinkumar Badanidiyuru, Zhe Feng, Guru Guruganesh
Learning to Bid in Contextual First Price Auctions✱. WWW (2023)
Chaoqi Wang, Ziyu Ye, Zhe Feng, Ashwinkumar Badanidiyuru Varadaraja, Haifeng Xu
Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts. NeurIPS (2023)
Jiahao Zhang, Tao Lin, Weiqiang Zheng, Zhe Feng, Yifeng Teng, Xiaotie Deng
Learning Thresholds with Latent Values and Censored Feedback. CoRR (2023)
Chaoqi Wang, Ziyu Ye, Zhe Feng, Ashwinkumar Badanidiyuru, Haifeng Xu
Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts. CoRR (2023)
Zhe Feng, Swati Padmanabhan, Di Wang
Online Bidding Algorithms for Return-on-Spend Constrained Advertisers✱. WWW (2023)
Zhijian Duan, Jingwu Tang, Yutong Yin, Zhe Feng, Xiang Yan, Manzil Zaheer, Xiaotie Deng
A Context-Integrated Transformer-Based Neural Network for Auction Design. ICML (2022)
Jibang Wu, Zixuan Zhang, Zhe Feng, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan, Haifeng Xu
Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning. CoRR (2022)
Ashwinkumar Badanidiyuru Varadaraja, Zhe Feng, Tianxi Li, Haifeng Xu
Incrementality Bidding via Reinforcement Learning under Mixed and Delayed Rewards. NeurIPS (2022)
Jibang Wu, Zixuan Zhang, Zhe Feng, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan, Haifeng Xu
Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning. EC (2022)
Zhijian Duan, Jingwu Tang, Yutong Yin, Zhe Feng, Xiang Yan, Manzil Zaheer, Xiaotie Deng
A Context-Integrated Transformer-Based Neural Network for Auction Design. CoRR (2022)
Ashwinkumar Badanidiyuru, Zhe Feng, Tianxi Li, Haifeng Xu
Incrementality Bidding via Reinforcement Learning under Mixed and Delayed Rewards. CoRR (2022)
Ashwinkumar Badanidiyuru, Zhe Feng, Guru Guruganesh
Learning to Bid in Contextual First Price Auctions. CoRR (2021)
Sai Srivatsa Ravindranath, Zhe Feng, Shira Li, Jonathan Ma, Scott Duke Kominers, David C. Parkes
Deep Learning for Two-Sided Matching. CoRR (2021)
Vincent Conitzer, Zhe Feng, David C. Parkes, Eric Sodomka
Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss. WINE (2021)
Zhe Feng, Guru Guruganesh, Christopher Liaw, Aranyak Mehta, Abhishek Sethi
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions. AAAI (2021)
Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath
Optimal auctions through deep learning. Commun. ACM 64 (8) (2021)
Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye
Reserve Price Optimization for First Price Auctions in Display Advertising. ICML (2021)
Zhe Feng, Sébastien Lahaie
Robust Clearing Price Mechanisms for Reserve Price Optimization. CoRR (2021)
Xiaotie Deng, Jack R. Edmonds, Zhe Feng, Zhengyang Liu, Qi Qi, Zeying Xu
Understanding PPA-completeness. J. Comput. Syst. Sci. 115 (2021)
Vincent Conitzer, Zhe Feng, David C. Parkes, Eric Sodomka
Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss. CoRR (2020)
Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye
Reserve Price Optimization for First Price Auctions. CoRR (2020)
Zhe Feng, Guru Guruganesh, Christopher Liaw, Aranyak Mehta, Abhishek Sethi
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions. CoRR (2020)
Zhe Feng, David C. Parkes, Haifeng Xu
The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation. ICML (2020)
Zhe Feng, Okke Schrijvers, Eric Sodomka
Online Learning for Measuring Incentive Compatibility in Ad Auctions. CoRR (2019)
Zhe Feng, David C. Parkes, Haifeng Xu
The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation. CoRR (2019)
Zhe Feng, Okke Schrijvers, Eric Sodomka
Online Learning for Measuring Incentive Compatibility in Ad Auctions? WWW (2019)
Paul Duetting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, Sai Srivatsa Ravindranath
Optimal Auctions through Deep Learning. ICML (2019)
Zhe Feng, Chara Podimata, Vasilis Syrgkanis
Learning to Bid Without Knowing your Value. EC (2018)
Zhe Feng, Jinglai Li
An Adaptive Independence Sampler MCMC Algorithm for Bayesian Inferences of Functions. SIAM J. Sci. Comput. 40 (3) (2018)
Zhe Feng, Harikrishna Narasimhan, David C. Parkes
Deep Learning for Revenue-Optimal Auctions with Budgets. AAMAS (2018)
Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes
Optimal Auctions through Deep Learning. CoRR (2017)
Xiaotie Deng, Zhe Feng, Rucha Kulkarni
Octahedral Tucker is PPA-Complete. Electron. Colloquium Comput. Complex. 24 (2017)
Zhe Feng, Chara Podimata, Vasilis Syrgkanis
Learning to Bid Without Knowing your Value. CoRR (2017)
Xiaotie Deng, Zhe Feng, Christos H. Papadimitriou
Power-Law Distributions in a Two-sided Market and Net Neutrality. CoRR (2016)
Xiaotie Deng, Jack R. Edmonds, Zhe Feng, Zhengyang Liu, Qi Qi, Zeying Xu
Understanding PPA-Completeness. Computational Complexity Conference (2016)
Xiaotie Deng, Zhe Feng, Christos H. Papadimitriou
Power-Law Distributions in a Two-Sided Market and Net Neutrality. WINE (2016)
Xiaotie Deng, Zhe Feng, Zhengyang Liu, Qi Qi
Understanding PPA-Completeness. Electron. Colloquium Comput. Complex. 22 (2015)