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» Embedding ultrametrics into low-dimensional spaces
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NIPS
2001
13 years 8 months ago
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
Mikhail Belkin, Partha Niyogi
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,...
NIPS
2004
13 years 8 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, ...
AAAI
2006
13 years 8 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...
ICPR
2006
IEEE
14 years 8 months ago
Object Tracking Using Globally Coordinated Nonlinear Manifolds
We present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. An appearance manifold is usually non...
Che-Bin Liu, Ming-Hsuan Yang, Narendra Ahuja, Ruei...