Small sample size generalization

By Robert P. W. Duin. 1995

Subfields: Scaling & Learning Theory

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In Scaling & Learning Theory

1. Marco Loog
2. Tristan Yang
3. Zhi-Hua Zhou
4. Boaz Barak
5. Ilya Sutskever
6. Robert P. W. Duin
7. Preetum Nakkiran
8. Xiaoyang Tan

Citations in the corpus

• Deep double descent: where bigger models and more data hurt (2019, background): “(2018), and Geiger et al. (2019b). This phenomenon was first postulated in generality by Belkin et al.”
• The Dipping Phenomenon (2012, methodology): “This phenomenon has been described and investigated, for instance, for the Fisher discriminant classifier [4,13,14], for particular perceptron rules [12,11], and for lasso regression [8].”
• Classifiers in almost empty spaces (2000, methodology): “Elsewhere ([14], [18]) we named this the PseudoFisher Linear Discriminant (PFLD), as it is equivalent to the use of pseudo-inverse for the singular scatter matrix.”
• Face recognition from a single image per person: A survey (2006, background): “However, in some application scenarios where a large amount of face images are available (e.g. in law enforcement ), one may need more intelligent and less laborious way to process faces.”