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Abstract About 25 years ago, it came to light that a single combinatorial property determines both an important dividing line in model theory (NIP) and machine learning (PAC-learnability). 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.  more » « less
Award ID(s):
Author(s) / Creator(s):
Date Published:
Journal Name:
The Bulletin of Symbolic Logic
Page Range / eLocation ID:
319 to 332
Medium: X
Sponsoring Org:
National Science Foundation
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