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Activity Number: 74
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Learning and Data Science
Abstract #318975
Title: Topological Property Hypotheses for Graphical Models
Author(s): Junwei Lu* and Matey Neykov and Han Liu
Companies: Princeton and Princeton and Princeton
Keywords: property test ; graphical model ; skip-down method ; bootstrap ; minimax
Abstract:

We propose a systematic inferential toolkit to conduct the hypothesis testing for the structural properties of the graphical model, including the connectivity, degrees, isolated nodes, etc. A generalized algorithm called skip-down method is applied to test these graph properties. We also derive the lower bound of signal strengths of the graphical models on these tests.


Authors who are presenting talks have a * after their name.

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