Sciweavers

43 search results - page 1 / 9
» On Low Distortion Embeddings of Statistical Distance Measure...
Sort
View
DEXA
2009
Springer
153views Database» more  DEXA 2009»
13 years 11 months ago
On Low Distortion Embeddings of Statistical Distance Measures into Low Dimensional Spaces
Arnab Bhattacharya, Purushottam Kar, Manjish Pal
FOCS
2003
IEEE
13 years 10 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
AAAI
2006
13 years 6 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...
NIPS
2004
13 years 6 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»
14 years 4 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