Representation Learning

Nada Lavrač (), Vid Podpečan () and Marko Robnik-Šikonja ()
Additional contact information
Nada Lavrač: University of Nova Gorica, Department of Knowledge Technologies, Jožef Stefan Institute, Ljubljana, Slovenia; School of Engineering and Management
Vid Podpečan: Jožef Stefan Institute, Department of Knowledge Technologies
Marko Robnik-Šikonja: University of Ljubljana, Faculty of Computer and Information Science

in Springer Books from Springer

Date: 2021
ISBN: 978-3-030-68817-2
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Chapters in this book:

Ch Chapter 1 Introduction to Representation Learning

Nada Lavrač, Vid Podpečan and Marko Robnik-Šikonja

Ch Chapter 2 Machine Learning Background

Nada Lavrač, Vid Podpečan and Marko Robnik-Šikonja

Ch Chapter 3 Text Embeddings

Nada Lavrač, Vid Podpečan and Marko Robnik-Šikonja

Ch Chapter 4 Propositionalization of Relational Data

Nada Lavrač, Vid Podpečan and Marko Robnik-Šikonja

Ch Chapter 5 Graph and Heterogeneous Network Transformations

Nada Lavrač, Vid Podpečan and Marko Robnik-Šikonja

Ch Chapter 6 Unified Representation Learning Approaches

Nada Lavrač, Vid Podpečan and Marko Robnik-Šikonja

Ch Chapter 7 Many Faces of Representation Learning

Nada Lavrač, Vid Podpečan and Marko Robnik-Šikonja

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprbok:978-3-030-68817-2

Ordering information: This item can be ordered from
http://www.springer.com/9783030688172

DOI: 10.1007/978-3-030-68817-2

Access Statistics for this book

More books in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().