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JMLR
2010
186views more  JMLR 2010»
13 years 3 months ago
Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting
We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
Philippos Mordohai, Gérard G. Medioni
COMGEO
2007
ACM
13 years 8 months ago
Delaunay triangulations approximate anchor hulls
Recent results establish that a subset of the Voronoi diagram of a point set that is sampled from the smooth boundary of a shape approximates the medial axis. The corresponding qu...
Tamal K. Dey, Joachim Giesen, Samrat Goswami
ICDE
2002
IEEE
91views Database» more  ICDE 2002»
14 years 1 months ago
Lossy Reduction for Very High Dimensional Data
We consider the use of data reduction techniques for the problem of approximate query answering. We focus on applications for which accurate answers to selective queries are requi...
Chris Jermaine, Edward Omiecinski
CVPR
2005
IEEE
14 years 10 months ago
Rank-R Approximation of Tensors: Using Image-as-Matrix Representation
We present a novel multilinear algebra based approach for reduced dimensionality representation of image ensembles. We treat an image as a matrix, instead of a vector as in tradit...
Hongcheng Wang, Narendra Ahuja
PAMI
2006
141views more  PAMI 2006»
13 years 8 months ago
Diffusion Maps and Coarse-Graining: A Unified Framework for Dimensionality Reduction, Graph Partitioning, and Data Set Parameter
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...
Stéphane Lafon, Ann B. Lee