The notion of Stability [1–3] allows to answer a fundamental question in learning theory: which are the properties that a learning algorithm A should fulfill in order to achieve good generalization performance? Stability answers this question in a very intuitive way: if A selects similar models, even if the training data are (slightly) modified, then we can be confident that the learning algorithm is stable.
Algorithmic Stability Theory
Oneto L.
2020-01-01
Abstract
The notion of Stability [1–3] allows to answer a fundamental question in learning theory: which are the properties that a learning algorithm A should fulfill in order to achieve good generalization performance? Stability answers this question in a very intuitive way: if A selects similar models, even if the training data are (slightly) modified, then we can be confident that the learning algorithm is stable.
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