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Expert Graphs: Synthesizing New Expertise via Collaboration

Mazaheri, Bijan and Jain, Siddharth and Bruck, Jehoshua (2021) Expert Graphs: Synthesizing New Expertise via Collaboration. . (Unpublished)

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Consider multiple experts with overlapping expertise working on a classification problem under uncertain input. What constitutes a consistent set of opinions? How can we predict the opinions of experts on missing sub-domains? In this paper, we define a framework of to analyze this problem, termed "expert graphs." In an expert graph, vertices represent classes and edges represent binary opinions on the topics of their vertices. We derive necessary conditions for expert graph validity and use them to create "synthetic experts" which describe opinions consistent with the observed opinions of other experts. We show this framework to be equivalent to the well-studied linear ordering polytope. We show our conditions are not sufficient for describing all expert graphs on cliques, but are sufficient for cycles.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Mazaheri, Bijan0000-0001-9690-8686
Jain, Siddharth0000-0002-9164-6119
Bruck, Jehoshua0000-0001-8474-0812
Record Number:CaltechAUTHORS:20220804-201308000
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:116132
Deposited By: George Porter
Deposited On:09 Aug 2022 17:18
Last Modified:09 Aug 2022 17:18

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