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» On Low Distortion Embeddings of Statistical Distance Measure...
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89
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DEXA
2009
Springer
153views Database» more  DEXA 2009»
15 years 4 months ago
On Low Distortion Embeddings of Statistical Distance Measures into Low Dimensional Spaces
Arnab Bhattacharya, Purushottam Kar, Manjish Pal
FOCS
2003
IEEE
15 years 2 months ago
Bounded Geometries, Fractals, and Low-Distortion Embeddings
The doubling constant of a metric space (X, d) is the smallest value λ such that every ball in X can be covered by λ balls of half the radius. The doubling dimension of X is the...
Anupam Gupta, Robert Krauthgamer, James R. Lee
87
Voted
AAAI
2006
14 years 11 months ago
Embedding Heterogeneous Data Using Statistical Models
Embedding algorithms are a method for revealing low dimensional structure in complex data. Most embedding algorithms are designed to handle objects of a single type for which pair...
Amir Globerson, Gal Chechik, Fernando Pereira, Naf...
96
Voted
NIPS
2004
14 years 10 months ago
Euclidean Embedding of Co-Occurrence Data
Embedding algorithms search for low dimensional structure in complex data, but most algorithms only handle objects of a single type for which pairwise distances are specified. Thi...
Amir Globerson, Gal Chechik, Fernando C. Pereira, ...
STOC
2004
ACM
126views Algorithms» more  STOC 2004»
15 years 9 months ago
Bypassing the embedding: algorithms for low dimensional metrics
The doubling dimension of a metric is the smallest k such that any ball of radius 2r can be covered using 2k balls of raThis concept for abstract metrics has been proposed as a na...
Kunal Talwar