18 citations · 20 across the 3 of their papers we have counts for
9 papers
Learning Truthful Mechanisms without Discretization
Yunxuan Ma, Siqiang Wang, Zhijian Duan +2
This paper introduces TEDI (Truthful, Expressive, and Dimension-Insensitive approach), a discretization-free algorithm to learn truthful and utility-maximizing mechanisms. Existing…
An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising
Zhijian Duan, Yusen Huo, Tianyu Wang +6
In online advertising, advertisers commonly utilize auto-bidding services to bid for impression opportunities. A typical objective of the auto-bidder is to optimize the advertiser'…
Large-Scale Contextual Market Equilibrium Computation through Deep Learning
Yunxuan Ma, Yide Bian, Hao Xu +5
Market equilibrium is one of the most fundamental solution concepts in economics and social optimization analysis. Existing works on market equilibrium computation primarily focus…
Automated Deterministic Auction Design with Objective Decomposition
Zhijian Duan, Haoran Sun, Yichong Xia +6
Identifying high-revenue mechanisms that are both dominant strategy incentive compatible (DSIC) and individually rational (IR) is a fundamental challenge in auction design. While t…
A survey on algorithms for Nash equilibria in finite normal-form games
Hanyu Li, Wenhan Huang, Zhijian Duan +4
Nash equilibrium is one of the most influential solution concepts in game theory. With the development of computer science and artificial intelligence, there is an increasing deman…
Coordinated Dynamic Bidding in Repeated Second-Price Auctions with Budgets
Yurong Chen, Qian Wang, Zhijian Duan +4
In online ad markets, a rising number of advertisers are employing bidding agencies to participate in ad auctions. These agencies are specialized in designing online algorithms and…