Technical perspective: Why don't today's deep nets overfit to their training data?
Author(s): Arora, Sanjeev
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http://arks.princeton.edu/ark:/88435/pr10c2q| Abstract: | THE FOLLOWING ARTICLE by Zhang et al. is well-known for having highlighted that widespread success of deep learn- ing in artificial intelligence brings with it a fundamental new theoretical challenge, specifically: Why don’t to- day’s deep nets overfit to training data? This question has come to animate the theory of deep learning. |
| Publication Date: | 2021 |
| Citation: | Arora, Sanjeev. "Technical perspective: Why don't today's deep nets overfit to their training data?." Communications of the ACM 64, no. 3 (2021): pp. 106. doi:10.1145/3446773 |
| DOI: | 10.1145/3446773 |
| ISSN: | 0001-0782 |
| Pages: | 106 |
| Type of Material: | Journal Article |
| Journal/Proceeding Title: | Communications of the ACM |
| Version: | Final published version. Article is made available in OAR by the publisher's permission or policy. |
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