2 citations · 3 across the 3 of their papers we have counts for
3 papers
No-Regret Learning in Games is Turing Complete
Gabriel P. Andrade, Rafael Frongillo, Georgios Piliouras
Games are natural models for multi-agent machine learning settings, such as generative adversarial networks (GANs). The desirable outcomes from algorithmic interactions in these ga…
Graphical Economies with Resale
Gabriel P. Andrade, Rafael Frongillo, Elliot Gorokhovsky +1
Kakade, Kearns, and Ortiz (KKO) introduce a graph-theoretic generalization of the classic Arrow--Debreu (AD) exchange economy. Despite its appeal as a networked version of AD, we a…
Learning in Matrix Games can be Arbitrarily Complex
Gabriel P. Andrade, Rafael Frongillo, Georgios Piliouras
A growing number of machine learning architectures, such as Generative Adversarial Networks, rely on the design of games which implement a desired functionality via a Nash equilibr…