4 citations · 9 across the 6 of their papers we have counts for
5 papers · 1 filter
Information Design With Large Language Models
Paul Duetting, Safwan Hossain, Tao Lin +4
Information design is typically studied through the lens of Bayesian signaling, where signals shape beliefs purely based on their correlation with the true state of the world. Howe…
Deep Reinforcement Learning for Sequential Combinatorial Auctions
Sai Srivatsa Ravindranath, Zhe Feng, Di Wang +3
Revenue-optimal auction design is a challenging problem with significant theoretical and practical implications. Sequential auction mechanisms, known for their simplicity and stron…
Data Market Design through Deep Learning
Sai Srivatsa Ravindranath, Yanchen Jiang, David C. Parkes
The data market design problem is a problem in economic theory to find a set of signaling schemes (statistical experiments) to maximize expected revenue to the information seller,…
Deep Learning for Two-Sided Matching
Sai Srivatsa Ravindranath, Zhe Feng, Shira Li +3
We initiate the study of deep learning for the automated design of two-sided matching mechanisms. What is of most interest is to use machine learning to understand the possibility…
Optimal Auctions through Deep Learning: Advances in Differentiable Economics
Paul Dütting, Zhe Feng, Harikrishna Narasimhan +2
Designing an incentive compatible auction that maximizes expected revenue is an intricate task. The single-item case was resolved in a seminal piece of work by Myerson in 1981, but…