Nearest-neighbor methods in learning and vision : theory and practice / edited by Gregory Shakhnarovich, Trevor Darrell, Piotr Indyk.

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

Regression and classification methods based on similarity of the input to stored examples have not been widely used in applications involving very large sets of high-dimensional data. Recent advances in computational geometry and machine learning, however, may alleviate the problems in using these m...

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Bibliographic Details
Other Authors: Shakhnarovich, Gregory, Darrell, Trevor, Indyk, Piotr
Format: Electronic eBook
Language:English
Published: Cambridge, Mass. : MIT Press, ©2005.
Series:Neural information processing series.
Subjects:
Nearest neighbor analysis (Statistics) > Congresses.
Machine learning > Congresses.
Algorithms > Congresses.
Geometry > Data processing > Congresses.
Artificial intelligence.
Algorithms
Artificial Intelligence
algorithms.
artificial intelligence.
Congress
proceedings (reports)
Conference papers and proceedings.
Online Access: Full text (Wentworth users only)
Local Note:ProQuest Ebook Central
Table of Contents:
  • Nearest-neighbor searching and metric space dimensions / Kenneth L. Clarkson
  • Locality-sensitive hashing using stable distributions / Alexandr Andoni [and others]
  • New algorithms for efficient high-dimensional nonparametric classification / Ting Liu, Andrew W. Moore, and Alexander Gray
  • Approximate nearest neighbor regression in very high dimensions / Sethu Vijayakumar, Aaron D'Souza, and Stefan Schaal
  • Learning embeddings for fast approximate nearest neighbor retrieval / Vassilis Athitsos [and others]
  • Parameter-sensitive hashing for fast pose estimation / Gregory Shakhnarovich, Paul Viola, and Trevor Darrell
  • Contour matching using approximate Earth mover's distance / Kristen Grauman and Trevor Darrell
  • Adaptive mean shift based clustering in high dimensions / Ilan Shimshoni, Bogdan Georgescu, and Peter Meer
  • Object recognition using locality sensitive hashing of shape contexts / Andrea Frome and Jitendra Malik.

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