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» Improved Induced Matchings in Sparse Graphs
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ICCV
2009
IEEE
14 years 9 months ago
Sparsity Induced Similarity Measure for Label Propagation
Graph-based semi-supervised learning has gained considerable interests in the past several years thanks to its effectiveness in combining labeled and unlabeled data through labe...
Hong Cheng, Zicheng Liu, Jie Yang
STACS
2004
Springer
13 years 10 months ago
Matching Algorithms Are Fast in Sparse Random Graphs
We present an improved average case analysis of the maximum cardinality matching problem. We show that in a bipartite or general random graph on n vertices, with high probability ...
Holger Bast, Kurt Mehlhorn, Guido Schäfer, Hi...
FSTTCS
2006
Springer
13 years 8 months ago
Fast Exponential Algorithms for Maximum r-Regular Induced Subgraph Problems
Given a graph G=(V, E) on n vertices, the MAXIMUM r-REGULAR INDUCED SUBGRAPH (M-r-RIS) problems ask for a maximum sized subset of vertices R V such that the induced subgraph on R,...
Sushmita Gupta, Venkatesh Raman, Saket Saurabh
CVPR
2011
IEEE
13 years 1 months ago
Global Stereo Matching Leveraged by Sparse Ground Control Points
We present a novel global stereo model that makes use of constraints from points with known depths, i.e., the Ground Control Points (GCPs) as referred to in stereo literature. Our...
Liang Wang, Ruigang Yang
CVPR
2009
IEEE
15 years 9 days ago
Stereo Matching with Nonparametric Smoothness Priors in Feature Space
We propose a novel formulation of stereo matching that considers each pixel as a feature vector. Under this view, matching two or more images can be cast as matching point clouds i...
Brandon M. Smith, Hailin Jin, Li Zhang