Skip to main navigation Skip to main content
info(at)avldigital.remove-this.de
Deutsch English
Last searches

Results for *

Displaying results 1 to 3 of 3.

  1. Artefakte des Entwerfens
    Skizzieren, Zeichnen, Skripten, Modellieren
    Contributor: Lyngsø Christensen, Rikke (Herausgeber); Drach, Ekkerhard (Herausgeber); Gasperoni, Lidia (Herausgeber); Hallama, Doris (Herausgeber); Hougaard, Anna Katrine (Herausgeber); Liptau, Ralf (Herausgeber)
    Published: 2022
    Publisher:  Universitätsverlag der TU Berlin, Berlin

    Export to reference management software   RIS file
      BibTeX file
    Source: Union catalogues
    Contributor: Lyngsø Christensen, Rikke (Herausgeber); Drach, Ekkerhard (Herausgeber); Gasperoni, Lidia (Herausgeber); Hallama, Doris (Herausgeber); Hougaard, Anna Katrine (Herausgeber); Liptau, Ralf (Herausgeber)
    Language: German
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 11303/9452.2
    Series: Forum Architekturwissenschaft ; 4
    Subjects: Bauentwurf; Architekturzeichnung; Architekturtheorie; Ästhetik; Entwurf; Architektur
    Other subjects: Entwerfen; Skizzieren; Zeichnen; Skripten; Modellieren; design; sketching; drawing; scripts; models
    Scope: Online-Ressource
  2. An econometric perspective on algorithmic subsampling
    Author: Lee, Sokbae; Ng, Serena
    Published: [2020]
    Publisher:  Cemmap, Centre for Microdata Methods and Practice, The Institute for Fiscal Studies, Department of Economics, UCL, [London]

    Datasets that are terabytes in size are increasingly common, but computer bottlenecks often frustrate a complete analysis of the data. While more data are better than less, diminishing returns suggest that we may not need terabytes of data to... more

    Access:
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)
    Resolving-System (kostenfrei)

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 243
    Inter-library loan:
    No inter-library loan

     

    Datasets that are terabytes in size are increasingly common, but computer bottlenecks often frustrate a complete analysis of the data. While more data are better than less, diminishing returns suggest that we may not need terabytes of data to estimate a parameter or test a hypothesis. But which rows of data should we analyze, and might an arbitrary subset of rows preserve the features of the original data? This paper reviews a line of work that is grounded in theoretical computer science and numerical linear algebra, and which finds that an algorithmically desirable sketch, which is a randomly chosen subset of the data, must preserve the eigenstructure of the data, a property known as a subspace embedding. Building on this work, we study how prediction and inference can be affected by data sketching within a linear regression setup. We show that the sketching error is small compared to the sample size effect which a researcher can control. As a sketch size that is algorithmically optimal may not be suitable for prediction and inference, we use statistical arguments to provide 'inference conscious' guides to the sketch size. When appropriately implemented, an estimator that pools over different sketches can be nearly as efficient as the infeasible one using the full sample.

     
    Export to reference management software   RIS file
      BibTeX file
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/241893
    Series: Cemmap working paper ; CWP20, 18
    Subjects: sketching; coresets; subspace embedding; countsketch; uniform sampling
    Scope: 1 Online-Ressource (circa 64 Seiten), Illustrationen
  3. Everyday Sketching and Drawing
    Five Steps to a Unique and Personal Sketchbook Habit
    Author: Reddy, Steven B.
    Published: 2022
    Publisher:  Monacelli Studio, New York, N. Y.

    Export to reference management software   RIS file
      BibTeX file
    Content information
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Print
    ISBN: 9781580935050; 1580935052
    Other identifier:
    9781580935050
    Other subjects: (Produktform)Hardback; (Produktform (spezifisch))Paper over boards; easy-to-follow; 5-step formula; beginner-friendly; techniques; learning; skills; drawing; sketching; everyday habit; (VLB-WN)1953: Hardcover, Softcover / Sachbücher/Kunst, Literatur/Bildende Kunst
    Scope: 192 Seiten, 25.4 cm x 21.2 cm