Bulletin of Symbolic Logic 25 (3):319-332 (2019)

Abstract
About 25 years ago, it came to light that a single combinatorial property determines both an important dividing line in model theory and machine learning. The following years saw a fruitful exchange of ideas between PAC-learning and the model theory of NIP structures. In this article, we point out a new and similar connection between model theory and machine learning, this time developing a correspondence between stability and learnability in various settings of online learning. In particular, this gives many new examples of mathematically interesting classes which are learnable in the online setting.
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DOI 10.1017/bsl.2018.71
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Notes on the Stability of Separably Closed Fields.Carol Wood - 1979 - Journal of Symbolic Logic 44 (3):412-416.

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