4 papers
A General Framework for Distributed Inference with Uncertain Models
James Z. Hare, Cesar A. Uribe, Lance Kaplan +1
This paper studies the problem of distributed classification with a network of heterogeneous agents. The agents seek to jointly identify the underlying target class that best descr…
Non-Bayesian Social Learning with Gaussian Uncertain Models
James Z. Hare, Cesar Uribe, Lance Kaplan +1
Non-Bayesian social learning theory provides a framework for distributed inference of a group of agents interacting over a social network by sequentially communicating and updating…
Non-Bayesian Social Learning with Uncertain Models
James Z. Hare, Cesar A. Uribe, Lance Kaplan +1
Non-Bayesian social learning theory provides a framework that models distributed inference for a group of agents interacting over a social network. In this framework, each agent it…
Non-Bayesian Social Learning with Uncertain Models over Time-Varying Directed Graphs
César A. Uribe, James Z. Hare, Lance Kaplan +1
We study the problem of non-Bayesian social learning with uncertain models, in which a network of agents seek to cooperatively identify the state of the world based on a sequence o…