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  • UB Potsdam  (3)
  • GB Hoppegarten
  • UdK Berlin
  • Ev. Landeskirche EKBO / Berl. Missionswerk
  • HS Musik Hanns Eisler
  • Computer Science  (3)
  • Konferenzschrift  (3)
  • 1
    UID:
    almahu_9947936561402882
    Format: XVII, 580 p. 150 illus. , online resource.
    ISBN: 9783319937649
    Series Statement: Lecture Notes in Computer Science, 10891
    Content: This book constitutes the proceedings of the 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018, held in Guildford, UK, in July 2018. The 52 full papers were carefully reviewed and selected from 62 initial submissions. As research topics the papers encompass a wide range of general mixtures of latent variables models but also theories and tools drawn from a great variety of disciplines such as structured tensor decompositions and applications; matrix and tensor factorizations; ICA methods; nonlinear mixtures; audio data and methods; signal separation evaluation campaign; deep learning and data-driven methods; advances in phase retrieval and applications; sparsity-related methods; and biomedical data and methods.
    Note: Structured Tensor Decompositions and Applications -- Matrix and Tensor Factorizations -- ICA Methods -- Nonlinear Mixtures -- Audio Data and Methods -- Signal Separation Evaluation Campaign -- Deep Learning and Data-driven Methods -- Advances in Phase Retrieval and Applications -- Sparsity-Related Methods -- Biomedical Data and Methods.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783319937632
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Konferenzschrift
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    almahu_9947363870702882
    Format: XVI, 237 p. 73 illus. , online resource.
    ISBN: 9783319067933
    Series Statement: Lecture Notes in Computer Science, 8380
    Content: This book is the outcome of the Dagstuhl Seminar 13201 on Information Visualization - Towards Multivariate Network Visualization, held in Dagstuhl Castle, Germany in May 2013. The goal of this Dagstuhl Seminar was to bring together theoreticians and practitioners from Information Visualization, HCI and Graph Drawing with a special focus on multivariate network visualization, i.e., on graphs where the nodes and/or edges have additional (multidimensional) attributes. The integration of multivariate data into complex networks and their visual analysis is one of the big challenges not only in visualization, but also in many application areas. Thus, in order to support discussions related to the visualization of real world data, also invited researchers from selected application areas, especially bioinformatics, social sciences and software engineering. The unique "Dagstuhl climate" ensured an open and undisturbed atmosphere to discuss the state-of-the-art, new directions and open challenges of multivariate network visualization.
    Note: Introduction to Multivariate Network Visualization -- Multivariate Networks in Software Engineering.- Multivariate Social Network Visual Analytics -- Multivariate Networks in the Life Sciences.- Tasks for Multivariate Network Analysis.- Interaction in the Visualization of Multivariate Networks.- Novel Visual Metaphors for Multivariate Networks.- Temporal Multivariate Networks -- Heterogeneous Networks on Multiple Levels.- Scalability Considerations for Multivariate Graph Visualization.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783319067926
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Konferenzschrift ; Konferenzschrift
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    UID:
    gbv_1656285770
    Format: Online-Ressource (XVI, 237 p. 73 illus, online resource)
    ISBN: 9783319067933
    Series Statement: Lecture Notes in Computer Science 8380
    Content: This book is the outcome of the Dagstuhl Seminar 13201 on Information Visualization - Towards Multivariate Network Visualization, held in Dagstuhl Castle, Germany in May 2013. The goal of this Dagstuhl Seminar was to bring together theoreticians and practitioners from Information Visualization, HCI and Graph Drawing with a special focus on multivariate network visualization, i.e., on graphs where the nodes and/or edges have additional (multidimensional) attributes. The integration of multivariate data into complex networks and their visual analysis is one of the big challenges not only in visualization, but also in many application areas. Thus, in order to support discussions related to the visualization of real world data, also invited researchers from selected application areas, especially bioinformatics, social sciences and software engineering. The unique "Dagstuhl climate" ensured an open and undisturbed atmosphere to discuss the state-of-the-art, new directions and open challenges of multivariate network visualization
    Note: Literaturangaben , Introduction to Multivariate Network VisualizationMultivariate Networks in Software Engineering.- Multivariate Social Network Visual Analytics -- Multivariate Networks in the Life Sciences.- Tasks for Multivariate Network Analysis.- Interaction in the Visualization of Multivariate Networks.- Novel Visual Metaphors for Multivariate Networks.- Temporal Multivariate Networks -- Heterogeneous Networks on Multiple Levels.- Scalability Considerations for Multivariate Graph Visualization.
    Additional Edition: ISBN 9783319067926
    Additional Edition: Erscheint auch als Druck-Ausgabe Seminar on "Information Visualization - towards Multivariate Network Visualization" (2013 : Dagstuhl) Multivariate network visualization Cham : Springer, 2014 ISBN 9783319067933
    Additional Edition: ISBN 9783319067926
    Additional Edition: ISBN 3319067923
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: World Wide Web 2.0 ; Bildkommunikation ; Bild ; Konferenzschrift
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
    Library Location Call Number Volume/Issue/Year Availability
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