• Cite/Export
  Cite/Export

  Copy a citation

  APA (6th ed.)

  

  Chicago (Author-Date, 15th ed.)

  

  Harvard (18th ed.)

  

  MLA (7th ed.)

  

  Turabian (6th ed.)

  

  Export a citation

  Export to RefWorks   Export to EndNote   Export to EasyBib   Cancel

  Note: Citations are based on reference standards. However, formatting rules can vary widely between applications and fields of interest or study. The specific requirements or preferences of your reviewing publisher, classroom teacher, institution or organization should be applied.
• Print
• E-mail
  E-mail

  All fields are required.

  The E-mail Address(es) field is required. Please enter recipient e-mail address(es).

  The E-mail Address(es) you entered is(are) not in a valid format. Please re-enter recipient e-mail address(es).

  You may send this item to up to five recipients.

  Enter recipient e-mail address(es): Separate up to five addresses with commas (,)

  The name field is required. Please enter your name.

  Enter your name: The subject field is required. Please enter the subject. Subject:

  The E-mail message field is required. Please enter the message.

  E-mail Message: I thought you might be interested in this item at http://www.worldcat.org/oclc/68907209 Title: Nearest-neighbor methods in learning and vision : theory and practice Author: Gregory Shakhnarovich; Trevor Darrell; Piotr Indyk Publisher: Cambridge, Mass. : MIT Press, ©2005. ISBN/ISSN: 9780262256957 0262256959 026219547X 9780262195478 OCLC:68907209

  
  

  The ReCaptcha terms you entered were incorrect. Please try to match the 2 words shown in the window, or try the audio version.

  Cancel
• Share
• Permalink
  Permalink

  Copy this URL to link to this page:

• Write a review
• Rate this item:
• • 1
  • 2
  • 3
  • 4
  • 5

More like this

Subjects

• Nearest neighbor analysis (Statistics) -- Congresses.
• Machine learning -- Congresses.
• Algorithms -- Congresses.
• View all subjects

Similar Items

Nearest-neighbor methods in learning and vision : theory and practice

Author:	Gregory Shakhnarovich; Trevor Darrell; Piotr Indyk
Publisher:	Cambridge, Mass. : MIT Press, ©2005.
Series:	Neural information processing series.
Edition/Format:	eBook : Document : Conference publication : EnglishView all editions and formats
Summary:	Advances in computational geometry and machine learning that offer new methods for search, regression, and classification with large amounts of high-dimensional data.
Rating:	(not yet rated) 0 with reviews - Be the first.