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FOCS
2009
IEEE
15 years 4 months ago
Distance Oracles for Sparse Graphs
Abstract— Thorup and Zwick, in their seminal work, introduced the approximate distance oracle, which is a data structure that answers distance queries in a graph. For any integer...
Christian Sommer 0002, Elad Verbin, Wei Yu
ECCV
2008
Springer
15 years 12 months ago
Online Sparse Matrix Gaussian Process Regression and Vision Applications
We present a new Gaussian Process inference algorithm, called Online Sparse Matrix Gaussian Processes (OSMGP), and demonstrate its merits with a few vision applications. The OSMGP ...
Ananth Ranganathan, Ming-Hsuan Yang
CORR
2011
Springer
209views Education» more  CORR 2011»
14 years 1 months ago
Analysis and Improvement of Low Rank Representation for Subspace segmentation
We analyze and improve low rank representation (LRR), the state-of-the-art algorithm for subspace segmentation of data. We prove that for the noiseless case, the optimization mode...
Siming Wei, Zhouchen Lin
ICASSP
2010
IEEE
14 years 10 months ago
Kronecker product matrices for compressive sensing
Compressive sensing (CS) is an emerging approach for acquisition of signals having a sparse or compressible representation in some basis. While CS literature has mostly focused on...
Marco F. Duarte, Richard G. Baraniuk
ICPR
2006
IEEE
15 years 11 months ago
Learning Wormholes for Sparsely Labelled Clustering
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Eng-Jon Ong, Richard Bowden