ViNNPruner: Visual Interactive Pruning for Deep Learning

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dc.contributor.authorSchlegel, Udoen_US
dc.contributor.authorSchiegg, Samuelen_US
dc.contributor.authorKeim, Daniel A.en_US
dc.contributor.editorArchambault, Danielen_US
dc.contributor.editorNabney, Ianen_US
dc.contributor.editorPeltonen, Jaakkoen_US
dc.date.accessioned2022-06-02T09:48:26Z
dc.date.available2022-06-02T09:48:26Z
dc.date.issued2022
dc.description.abstractNeural networks grow vastly in size to tackle more sophisticated tasks. In many cases, such large networks are not deployable on particular hardware and need to be reduced in size. Pruning techniques help to shrink deep neural networks to smaller sizes by only decreasing their performance as little as possible. However, such pruning algorithms are often hard to understand by applying them and do not include domain knowledge which can potentially be bad for user goals. We propose ViNNPruner, a visual interactive pruning application that implements state-of-the-art pruning algorithms and the option for users to do manual pruning based on their knowledge. We show how the application facilitates gaining insights into automatic pruning algorithms and semi-automatically pruning oversized networks to make them more efficient using interactive visualizations.en_US
dc.description.sectionheadersPapers
dc.description.seriesinformationMachine Learning Methods in Visualisation for Big Data
dc.identifier.doi10.2312/mlvis.20221070
dc.identifier.isbn978-3-03868-182-3
dc.identifier.pages13-17
dc.identifier.pages5 pages
dc.identifier.urihttps://doi.org/10.2312/mlvis.20221070
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/mlvis20221070
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing --> Visual analytics; Computing methodologies --> Neural networks
dc.subjectHuman centered computing
dc.subjectVisual analytics
dc.subjectComputing methodologies
dc.subjectNeural networks
dc.titleViNNPruner: Visual Interactive Pruning for Deep Learningen_US
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Machine Learning Methods in Visualisation for Big Data 2022