Bivariate Partial Information Decomposition: The Optimization Perspective
Institute of Computer Science, University of Tartu, 51014 Tartu, Estonia
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Received: 7 July 2017 / Revised: 21 September 2017 / Accepted: 28 September 2017 / Published: 7 October 2017
Bertschinger, Rauh, Olbrich, Jost, and Ay (Entropy, 2014) have proposed a definition of a decomposition of the mutual information
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.
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).
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MDPI and ACS Style
Makkeh, A.; Theis, D.O.; Vicente, R. Bivariate Partial Information Decomposition: The Optimization Perspective. Entropy 2017, 19, 530.
Makkeh A, Theis DO, Vicente R. Bivariate Partial Information Decomposition: The Optimization Perspective. Entropy. 2017; 19(10):530.
Makkeh, Abdullah; Theis, Dirk O.; Vicente, Raul. 2017. "Bivariate Partial Information Decomposition: The Optimization Perspective." Entropy 19, no. 10: 530.
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