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» The Generalized Dimensionality Reduction Problem
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113
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KDD
2008
ACM
172views Data Mining» more  KDD 2008»
15 years 10 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
COMPGEOM
2007
ACM
15 years 1 months ago
Embeddings of surfaces, curves, and moving points in euclidean space
In this paper we show that dimensionality reduction (i.e., Johnson-Lindenstrauss lemma) preserves not only the distances between static points, but also between moving points, and...
Pankaj K. Agarwal, Sariel Har-Peled, Hai Yu
85
Voted
IVC
2007
184views more  IVC 2007»
14 years 9 months ago
Image distance functions for manifold learning
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
Richard Souvenir, Robert Pless
JGO
2008
95views more  JGO 2008»
14 years 9 months ago
Generalized Semi-Infinite Programming: on generic local minimizers
Abstract In this paper a basic structural problem in Generalized Semi-Infinite Programming is solved. In fact, under natural and generic assumptions we show that at any (local) min...
Harald Günzel, Hubertus Th. Jongen, Oliver St...
76
Voted
TCS
2002
14 years 9 months ago
Binary (generalized) Post Correspondence Problem
An instance of the (Generalized) Post Correspondence Problem is during the decision process typically reduced to one or more other instances, called its successors. In this paper ...
Vesa Halava, Tero Harju, Mika Hirvensalo