J
Jonathan Goldstein
Researcher at University of Wisconsin-Madison
Publications - 7
Citations - 4307
Jonathan Goldstein is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Curse of dimensionality & k-nearest neighbors algorithm. The author has an hindex of 5, co-authored 5 publications receiving 4127 citations.
Papers
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Book ChapterDOI
When Is ''Nearest Neighbor'' Meaningful?
TL;DR: The effect of dimensionality on the "nearest neighbor" problem is explored, and it is shown that under a broad set of conditions, as dimensionality increases, the Distance to the nearest data point approaches the distance to the farthest data point.
Journal Article
When is nearest neighbor meaningful
TL;DR: In this article, the authors explore the effect of dimensionality on the nearest neighbor problem and show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance of the farthest data point.
Proceedings ArticleDOI
Compressing relations and indexes
TL;DR: A new compression algorithm that is tailored to database applications that can be applied to a collection of records, and is especially effective for records with many low to medium cardinality fields and numeric fields, is proposed.
Proceedings ArticleDOI
Processing queries by linear constraints
TL;DR: This paper presents several theoretical results about the processing strategy, and the results of several experiments which show that the processing cost of selection queries by linear constraints can be reduced dramatically by using the strategy.
Improved query processing and data representation techniques
TL;DR: This thesis presents new research on two topics: compression in relational database systems, and nearest neighbor processing techniques, and the relationship between sort orders, multidimensional bulk loading, and compression ratios.