%0 Conference Paper %1 10767666 %A Reichmann, Luca %A Hägele, David %A Weiskopf, Daniel %B 2024 IEEE 14th Symposium on Large Data Analysis and Visualization (LDAV) %D 2024 %K visualization;Principal management;Data libraries;Data analysis;Dimensionality analysis;High performance reduction;Runtime;Software algorithms;Memory component computing;Software Measurement;Dimensionality reduction;out-of-core;out-of-sample;evaluation %P 43-53 %R 10.1109/LDAV64567.2024.00008 %T Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions

@inproceedings{10767666, added-at = {2025-01-14T13:12:56.000+0100}, author = {Reichmann, Luca and Hägele, David and Weiskopf, Daniel}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/29c9eb741374853e3a11c6dc7c697bd8a/haegeldd}, booktitle = {2024 IEEE 14th Symposium on Large Data Analysis and Visualization (LDAV)}, doi = {10.1109/LDAV64567.2024.00008}, interhash = {16d151ef59945b90f62af611c911ddd8}, intrahash = {9c9eb741374853e3a11c6dc7c697bd8a}, keywords = {visualization;Principal management;Data libraries;Data analysis;Dimensionality analysis;High performance reduction;Runtime;Software algorithms;Memory component computing;Software Measurement;Dimensionality reduction;out-of-core;out-of-sample;evaluation}, pages = {43-53}, timestamp = {2025-01-14T13:12:56.000+0100}, title = {Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions}, year = 2024 }