30 citations · 102 across the 19 of their papers we have counts for
20 papers
MEV Makes Everyone Happy under Greedy Sequencing Rule
Yuhao Li, Mengqian Zhang, Jichen Li +3
Trading through decentralized exchanges (DEXs) has become crucial in today's blockchain ecosystem, enabling users to swap tokens efficiently and automatically. However, the capacit…
On Convergence Lemma and Convergence Stability for Piecewise Analytic Functions
Xiaotie Deng, Hanyu Li, Ningyuan Li
In this work, a convergence lemma for function being finite compositions of analytic mappings and the maximum operator is proved. The lemma shows that the set of -stationary…
A Context-Integrated Transformer-Based Neural Network for Auction Design
Zhijian Duan, Jingwu Tang, Yutong Yin +4
One of the central problems in auction design is developing an incentive-compatible mechanism that maximizes the auctioneer's expected revenue. While theoretical approaches have en…
Nash Convergence of Mean-Based Learning Algorithms in First-Price Auctions
Xiaotie Deng, Xinyan Hu, Tao Lin +1
The convergence properties of learning dynamics in repeated auctions is a timely and important question, with numerous applications in, e.g., online advertising markets. This work…
On the Complexity of Computing Markov Perfect Equilibrium in General-Sum Stochastic Games
Xiaotie Deng, Ningyuan Li, David Mguni +2
Similar to the role of Markov decision processes in reinforcement learning, Stochastic Games (SGs) lay the foundation for the study of multi-agent reinforcement learning (MARL) and…
A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling
Xiaotie Deng, Ron Lavi, Tao Lin +3
The Empirical Revenue Maximization (ERM) is one of the most important price learning algorithms in auction design: as the literature shows it can learn approximately optimal reserv…