Search Results for author:
Found 2 papers, 0 papers with code
Rate Analysis of Coupled Distributed Stochastic Approximation for Misspecified Optimization
To address the special optimization problem, we propose a coupled distributed stochastic approximation algorithm, in which every agent updates the current beliefs of its unknown parameter and decision variable by stochastic approximation method; and then averages the beliefs and decision variables of its neighbors over network in consensus protocol.
Distributed Fractional Bayesian Learning for Adaptive Optimization
This paper considers a distributed adaptive optimization problem, where all agents only have access to their local cost functions with a common unknown parameter, whereas they mean to collaboratively estimate the true parameter and find the optimal solution over a connected network.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
