Logical Interpretations of Autoencoders

Anton Fuxjaeger, Vaishak Belle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The unification of low-level perception and high-level reasoning is a long-standing problem in artificial intelligence, which has the potential to not only bring the areas of logic and learning closer together but also demonstrate how abstract concepts might emerge from sensory data. Precisely because deep learning methods dominate perception-based learning, including vision, speech, and linguistic grammar, there is fast-growing literature on how to integrate symbolic reasoning and deep learning. Broadly, efforts seem to fall into three camps: those focused on defining a logic whose formulas capture deep learning, ones that integrate symbolic constraints in deep learning, and others that allow neural computations and symbolic reasoning to co-exist separately, to enjoy the strengths of both worlds. In this paper, we identify another dimension to this inquiry: what do the hidden layers really capture, and how can we reason about that logically? In particular, we consider variational autoencoders that are widely used for dimensionality reduction and inject a symbolic generative framework onto the feature layer. This allows us, among other things, to generate example images for a class to get a sense of what was learned. Moreover, the modular structure of the proposed model makes it possible to learn relations over multiple images at a time, as well as handle noisy labels. Our empirical evaluations show the promise of this inquiry.
Original languageEnglish
Title of host publicationECAI 2020
EditorsGiuseppe De Giacomo, Alejandro Catala, Bistra Dilkina, Michela Milano, Senén Barro, Alberto Bugarín, Jérôme Lang
PublisherIOS Press
Pages2481-2488
Number of pages8
ISBN (Electronic)978-1-64368-101-6
ISBN (Print)978-1-64368-100-9
DOIs
Publication statusPublished - 9 Aug 2020
Event24th European Conference on Artificial Intelligence - Virtual conference, Spain
Duration: 29 Aug 20208 Sep 2020
Conference number: 24
http://ecai2020.eu/

Publication series

NameFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Volume325
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Conference

Conference24th European Conference on Artificial Intelligence
Abbreviated titleECAI 2020
Country/TerritorySpain
CityVirtual conference
Period29/08/208/09/20
Internet address

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