Sum-product-quotient networks

Or Sharir, Amnon Shashua

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations

Abstract

We present a novel tractable generative model that extends Sum-Product Networks (SPNs) and significantly boosts their power. We call it Sum-Product-Quotient Networks (SPQNs), whose core concept is to incorporate conditional distributions into the model by direct computation using quotient nodes, e.g. (Formula presented.). We provide sufficient conditions for the tractability of SPQNs that generalize and relax the decomposable and complete tractability conditions of SPNs. These relaxed conditions give rise to an exponential boost to the expressive efficiency of our model, i.e. we prove that there are distributions which SPQNs can compute efficiently but require SPNs to be of exponential size. Thus, we narrow the gap in expressivity between tractable graphical models and other Neural Network-based generative models.

Original languageAmerican English
Pages529-537
Number of pages9
StatePublished - 2018
Event21st International Conference on Artificial Intelligence and Statistics, AISTATS 2018 - Playa Blanca, Lanzarote, Canary Islands, Spain
Duration: 9 Apr 201811 Apr 2018

Conference

Conference21st International Conference on Artificial Intelligence and Statistics, AISTATS 2018
Country/TerritorySpain
CityPlaya Blanca, Lanzarote, Canary Islands
Period9/04/1811/04/18

Bibliographical note

Publisher Copyright:
Copyright 2018 by the author(s).

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