Next Article in Journal / Special Issue
Multivariate Dependence beyond Shannon Information
Previous Article in Journal
How Can We Fully Use Noiseless Feedback to Enhance the Security of the Broadcast Channel with Confidential Messages
Previous Article in Special Issue
Coarse-Graining and the Blackwell Order
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Entropy 2017, 19(10), 530; https://doi.org/10.3390/e19100530

Bivariate Partial Information Decomposition: The Optimization Perspective

Institute of Computer Science, University of Tartu, 51014 Tartu, Estonia
*
Author to whom correspondence should be addressed.
Received: 7 July 2017 / Revised: 21 September 2017 / Accepted: 28 September 2017 / Published: 7 October 2017
Full-Text   |   PDF [459 KB, uploaded 26 October 2017]   |  

Abstract

Bertschinger, Rauh, Olbrich, Jost, and Ay (Entropy, 2014) have proposed a definition of a decomposition of the mutual information M I ( X : Y , Z ) into shared, synergistic, and unique information by way of solving a convex optimization problem. In this paper, we discuss the solution of their Convex Program from theoretical and practical points of view. View Full-Text
Keywords: partial information decomposition; bivariate information decomposition; applications of convex optimization partial information decomposition; bivariate information decomposition; applications of convex optimization
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Makkeh, A.; Theis, D.O.; Vicente, R. Bivariate Partial Information Decomposition: The Optimization Perspective. Entropy 2017, 19, 530.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top