Corpus ID: 236087943

# A Theory of PAC Learnability of Partial Concept Classes

@article{Alon2021ATO,
title={A Theory of PAC Learnability of Partial Concept Classes},
author={Noga Alon and Steve Hanneke and Ron Holzman and Shay Moran},
journal={ArXiv},
year={2021},
volume={abs/2107.08444}
}
• N. Alon, +1 author S. Moran
• Published 2021
• Computer Science, Mathematics
• ArXiv
We extend the classical theory of PAC learning in a way which allows to model a rich variety of practical learning tasks where the data satisfy special properties that ease the learning process. For example, tasks where the distance of the data from the decision boundary is bounded away from zero, or tasks where the data lie on a lower dimensional surface. The basic and simple idea is to consider partial concepts: these are functions that can be undefined on certain parts of the space. When… Expand

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