When the state of the art is ahead of the state of understanding: Unintuitive properties of deep neural networks

Authors

  • Joan Serrà Telefónica R&D, Barcelona (Spain).

DOI:

https://doi.org/10.7203/metode.9.11035

Keywords:

deep learning, machine learning, neural networks, unintuitive properties

Abstract

Deep learning is an undeniably hot topic, not only within both academia and industry, but also among society and the media. The reasons for the advent of its popularity are manifold: unprecedented availability of data and computing power, some innovative methodologies, minor but significant technical tricks, etc. However, interestingly, the current success and practice of deep learning seems to be uncorrelated with its theoretical, more formal understanding. And with that, deep learning’s state-of-the-art presents a number of unintuitive properties or situations. In this note, I highlight some of these unintuitive properties, trying to show relevant recent work, and expose the need to get insight into them, either by formal or more empirical means.

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Author Biography

Joan Serrà, Telefónica R&D, Barcelona (Spain).

Research scientist with Telefónica R&D in Barcelona, where he works on machine learning and deep learning topics. He obtained his PhD in Computer Science from the Pompeu Fabra University in 2011 and was a postdoctoral researcher in artificial intelligence at IIIA-CSIC, the Artificial Intelligence Institute of the Spanish National Research Council (2015). He has been involved in more than ten research projects, funded by Spanish and European institutions, and co-authored over a hundred publications, many of them highly-cited and in top-tier journals and conferences, in diverse scientific areas.  

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Published

2019-03-06

How to Cite

Serrà, J. (2019). When the state of the art is ahead of the state of understanding: Unintuitive properties of deep neural networks. Metode Science Studies Journal, (9), 127–133. https://doi.org/10.7203/metode.9.11035
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Issue

The grounds of science (2019)

Section

Interlinked. Machines and humans facing the 10101 century

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