Buch, Englisch, 232 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 529 g
Buch, Englisch, 232 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 529 g
Reihe: Unsupervised and Semi-Supervised Learning
ISBN: 978-3-030-29348-2
Verlag: Springer
"This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge."
M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas
"In science the difficulty is not to have ideas, but it is to make them work"From Carlo Rovelli
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management
Weitere Infos & Material
Introduction to sampling techniques.- Core-sets: an Updated Survey.- A family of unsupervised sampling algorithms.- From supervised instance and feature selection algorithms to dual selection: A Review.- Approximating Spectral Clustering via Sampling: A Review.- Sampling technique for complex data.- Boosting the Exploration of Huge Dynamic Graphs.