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BMCBI
2011
12 years 11 months ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto
STOC
2005
ACM
130views Algorithms» more  STOC 2005»
14 years 7 months ago
Low-distortion embeddings of general metrics into the line
A low-distortion embedding between two metric spaces is a mapping which preserves the distances between each pair of points, up to a small factor called distortion. Low-distortion...
Mihai Badoiu, Julia Chuzhoy, Piotr Indyk, Anastasi...
APPROX
2010
Springer
137views Algorithms» more  APPROX 2010»
13 years 9 months ago
Online Embeddings
We initiate the study of on-line metric embeddings. In such an embedding we are given a sequence of n points X = x1, . . . , xn one by one, from a metric space M = (X, D). Our goal...
Piotr Indyk, Avner Magen, Anastasios Sidiropoulos,...
CVPR
2010
IEEE
13 years 10 months ago
Metric-Induced Optimal Embedding for Intrinsic 3D Shape Analysis
For various 3D shape analysis tasks, the LaplaceBeltrami(LB) embedding has become increasingly popular as it enables the efficient comparison of shapes based on intrinsic geometry...
Rongjie Lai, Yonggang Shi, Kevin Scheibel, Scott F...
FOCS
2004
IEEE
13 years 11 months ago
Measured Descent: A New Embedding Method for Finite Metrics
We devise a new embedding technique, which we call measured descent, based on decomposing a metric space locally, at varying speeds, according to the density of some probability m...
Robert Krauthgamer, James R. Lee, Manor Mendel, As...