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» Embedding ultrametrics into low-dimensional spaces
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NIPS
2001
14 years 11 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»
14 years 11 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
14 years 11 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
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...
ICPR
2006
IEEE
15 years 10 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...