Recent Trends in Learning From Data
Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL2019)
Published on 3. April 2020
VII, 221 pages
978-3-030-43883-8 (ISBN)
Description
This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
VII, 221 p. 81 illus., 55 illus. in color.
File size
7,32 MB
ISBN-13
978-3-030-43883-8 (9783030438838)
DOI
10.1007/978-3-030-43883-8
Schweitzer Classification
Other editions
Additional editions
Luca Oneto | Nicolò Navarin | Alessandro Sperduti
Recent Trends in Learning From Data
Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL2019)
Book
04/2020
Springer
€149.79
Shipment within 7-9 days
Content
Introduction: Recent Trends in Learning From Data.- Learned data structures.- Deep Randomized Neural Networks.- Tensor Decompositions and Practical Applications.- Deep learning for graphs.- Limitations of Shallow Networks.- Fairness in Machine Learning.- Online Continual Learning on Sequences.
