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» Proximity Graphs for Clustering and Manifold Learning
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NIPS
2004
9 years 1 months ago
Proximity Graphs for Clustering and Manifold Learning
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Miguel Á. Carreira-Perpiñán, ...
COLT
2005
Springer
9 years 5 months ago
Towards a Theoretical Foundation for Laplacian-Based Manifold Methods
In recent years manifold methods have attracted a considerable amount of attention in machine learning. However most algorithms in that class may be termed ā€œmanifold-motivatedā€...
Mikhail Belkin, Partha Niyogi
CVPR
2007
IEEE
10 years 2 months ago
Fiber Tract Clustering on Manifolds With Dual Rooted-Graphs
We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...
ISBI
2011
IEEE
8 years 3 months ago
Sparse Riemannian manifold clustering for HARDI segmentation
We address the problem of segmenting high angular resolution diffusion images of the brain into cerebral regions corresponding to distinct white matter ļ¬ber bundles. We cast thi...
Hasan Ertan Çetingül, René Vida...
CVPR
2008
IEEE
10 years 2 months ago
Large-scale manifold learning
This paper examines the problem of extracting lowdimensional manifold structure given millions of highdimensional face images. Specifically, we address the computational challenge...
Ameet Talwalkar, Sanjiv Kumar, Henry A. Rowley
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