3 citations · 5 across the 4 of their papers we have counts for
5 papers
Learning to Charge More: A Theoretical Study of Collusion by Q-Learning Agents
Cristian Chica, Yinglong Guo, Gilad Lerman
There is growing experimental evidence that -learning agents may learn to charge supracompetitive prices. We provide the first theoretical explanation for this behavior in infin…
Competition and Collusion in Two-Sided Markets with an Outside Option
Cristian Chica, Yinglong Guo, Gilad Lerman
We introduce pricing formulas for competition and collusion models of two-sided markets with an outside option. For the competition model, we find conditions under which prices and…
Artificial Intelligence and Algorithmic Price Collusion in Two-sided Markets
Cristian Chica, Yinglong Guo, Gilad Lerman
Algorithmic price collusion facilitated by artificial intelligence (AI) algorithms raises significant concerns. We examine how AI agents using Q-learning engage in tacit collusion…
The effect of Leaky ReLUs on the training and generalization of overparameterized networks
Yinglong Guo, Shaohan Li, Gilad Lerman
We investigate the training and generalization errors of overparameterized neural networks (NNs) with a wide class of leaky rectified linear unit (ReLU) functions. More specificall…
An Unpooling Layer for Graph Generation
Yinglong Guo, Dongmian Zou, Gilad Lerman
We propose a novel and trainable graph unpooling layer for effective graph generation. Given a graph with features, the unpooling layer enlarges this graph and learns its desired n…