Unsupervised extraction of predictable features from high-dimensional time series
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
Bochum, Ruhr-Universität Bochum, Dissertation, 2019
- Keyword
-
Time
Informatik
Maschinelles Lernen
Neurowissenschaften
Unüberwachtes Lernen
Dimensionsreduktion
- Event
-
Veröffentlichung
- (where)
-
Bochum
- (who)
-
Ruhr-Universität Bochum
- (when)
-
2019
- Creator
- Contributor
-
Wiskott, Laurenz
Igel, Christian
Fakultät für Elektrotechnik und Informationstechnik
- URN
-
urn:nbn:de:hbz:294-68195
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
25.03.2025, 1:55 PM CET
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Weghenkel, Björn
- Wiskott, Laurenz
- Igel, Christian
- Fakultät für Elektrotechnik und Informationstechnik
- Ruhr-Universität Bochum
Time of origin
- 2019
Other Objects (12)
Inhibition and loss of information in unsupervised feature extraction
Unsupervised sense-aware hypernymy extraction
Unsupervised relational feature learning for vision
Bidirectional job matching through unsupervised feature learning
Visual Feature Space Analysis for Unsupervised Effectiveness Estimation and Feature Engineering
Prototype based clustering in high-dimensional feature spaces
Unsupervised emotional pattern recognition using rhythmic and vocal features
SpikeShip: a method for fast, unsupervised discovery of high-dimensional neural spiking patterns
Unsupervised and Accurate Extraction of Primitive Unit Cells from Crystal Images
Feature Selection for High-Dimensional Data with RapidMiner
Feature Selection for High-Dimensional Data with RapidMiner
Feature extraction with hybrid neural networks
Inhibition and loss of information in unsupervised feature extraction
Unsupervised sense-aware hypernymy extraction
Unsupervised relational feature learning for vision
Bidirectional job matching through unsupervised feature learning
Visual Feature Space Analysis for Unsupervised Effectiveness Estimation and Feature Engineering
Prototype based clustering in high-dimensional feature spaces
Unsupervised emotional pattern recognition using rhythmic and vocal features
SpikeShip: a method for fast, unsupervised discovery of high-dimensional neural spiking patterns
Unsupervised and Accurate Extraction of Primitive Unit Cells from Crystal Images
Feature Selection for High-Dimensional Data with RapidMiner
Feature Selection for High-Dimensional Data with RapidMiner
Feature extraction with hybrid neural networks
Inhibition and loss of information in unsupervised feature extraction
Unsupervised sense-aware hypernymy extraction
Unsupervised relational feature learning for vision
Bidirectional job matching through unsupervised feature learning
Visual Feature Space Analysis for Unsupervised Effectiveness Estimation and Feature Engineering
Prototype based clustering in high-dimensional feature spaces
Unsupervised emotional pattern recognition using rhythmic and vocal features
SpikeShip: a method for fast, unsupervised discovery of high-dimensional neural spiking patterns
Unsupervised and Accurate Extraction of Primitive Unit Cells from Crystal Images
Feature Selection for High-Dimensional Data with RapidMiner
Feature Selection for High-Dimensional Data with RapidMiner