rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: How Can We Use Machine Learning in the Search for Exoplanets?
  type of resource: moving image
  genre: videorecording
  origin info:
    place:
      place term: xx
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (15 minutes)
  abstract: Exoplanets are planets beyond our own solar system. Since they do not emit much light and moreover are very close to their parent stars they are difficult to detect directly. When searching for exoplanets, astronomers use telescopes to monitor the brightness of the parent star under investigation: Changes in brightness can point to a passing planet that obstructs part of the star's surface. The recorded signal, however, contains not only the physical signal of the star but also systematic errors caused by the instrument. As BERNHARD SCHÖLKOPF explains in this video, this noise can be removed by comparing the signal of the star of interest to those of a large number of other stars. Commonalities in their signals might be due to confounding effects of the instrument. Using machine learning, these observations can be used to train a system to predict the errors and correct the light curves.
  target audience: adult
  note: Title from resource description page (viewed August 24, 2020).
  subject:
    topic: Machine learning
  subject:
    topic: Apprentissage automatique
  subject:
    topic: Machine learning
  classification: Q325.5 .S355 2015
  classification: 006.31
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: VJA
    record creation date: 200824
    record change date: 20241201233839.2
    record identifier: in00005596879
    language of cataloging:
      language term: eng