Accession Number:

AD1042531

Title:

Consensus in the Wasserstein Metric Space of Probability Measures

Descriptive Note:

Journal Article

Corporate Author:

University of Technology Sydney Australia

Personal Author(s):

Report Date:

2015-07-01

Pagination or Media Count:

14.0

Abstract:

Distributed consensus in the Wasserstein metric space of probability measures is introduced in this work. Convergence of each agents measure to a common measure value is proven under a weak network connectivity condition. The common measure reached a teach agent is one minimizing a weighted sum of its Wasserstein distance to all initial agent measures. This measure is known as the Wasserstein bary centre. Special cases involving Gaussian measures, empirical measures, and time-invariant network topologies are considered, where convergence rates and average-consensus results are given. This algorithm has potential applicability in computer vision, machine learning and distributed estimation, etc.

Subject Categories:

  • Operations Research
  • Statistics and Probability
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE