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Topological methods for unsupervised learning. (English) Zbl 1458.68174

Nielsen, Frank (ed.) et al., Geometric science of information. 4th international conference, GSI 2019, Toulouse, France, August 27–29, 2019. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 11712, 343-350 (2019).
Summary: Unsupervised learning is a broad topic in machine learning with many diverse sub-disciplines. Within the field of unsupervised learning we will consider three major topics: dimension reduction; clustering; and anomaly detection. We seek to use the languages of topology and category theory to provide a unified mathematical approach to these three major problems in unsupervised learning.
For the entire collection see [Zbl 1428.94016].

MSC:

68T05 Learning and adaptive systems in artificial intelligence
62H30 Classification and discrimination; cluster analysis (statistical aspects)
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