Algorithmic Advances in Riemannian Geometry and Applications
For Machine Learning, Computer Vision, Statistics, and Optimization
This book presents a selection of the most recent algorithmic advances in Riemannian geometry in the context of machine learning, statistics, optimization, computer vision, and related fields. The unifying theme of the different chapters in the book is the exploitation of the geometry of data using the mathematical machinery of Riemannian geometry. As demonstrated by all the chapters in the book, when the data is intrinsically non-Euclidean, the utilization of this geometrical information can lead to better algorithms that can capture more accurately the structures inherent in the data, leading ultimately to better empirical performance. This…
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Produktdetails
Weitere Autoren: Murino, Vittorio (Hrsg.)
- ISBN: 978-3-319-45025-4
- EAN: 9783319450254
- Produktnummer: 20327118
- Verlag: Springer-Verlag GmbH
- Sprache: Englisch
- Erscheinungsjahr: 2016
- Seitenangabe: 208 S.
- Masse: H24.1 cm x B16.1 cm x D1.7 cm 521 g
- Abbildungen: Book; 4 schwarz-weiße und 51 farbige Abbildungen, 50 farbige Tabellen, Bibliographie
- Gewicht: 521
Über den Autor
Dr. Hà Quang Minh is a researcher in the Pattern Analysis and Computer Vision (PAVIS) group, at the Italian Institute of Technology (IIT), in Genoa, Italy. Dr. Vittorio Murino is a full professor at the University of Verona Department of Computer Science, and the Director of the PAVIS group at the IIT.
2 weitere Werke von Hà Quang (Hrsg.) Minh:
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