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» On randomized representations of graphs using short labels
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ICPR
2008
IEEE
14 years 8 months ago
HOPS: Efficient region labeling using Higher Order Proxy Neighborhoods
We present the Higher Order Proxy Neighborhoods (HOPS) approach to modeling higher order neighborhoods in Markov Random Fields (MRFs). HOPS incorporates more context information i...
Albert Y. C. Chen, Jason J. Corso, Le Wang
CVPR
2012
IEEE
11 years 9 months ago
Mode-seeking on graphs via random walks
Mode-seeking has been widely used as a powerful data analysis technique for clustering and filtering in a metric feature space. We introduce a versatile and efficient modeseekin...
Minsu Cho, Kyoung Mu Lee
PAMI
2010
215views more  PAMI 2010»
13 years 5 months ago
Fusion Moves for Markov Random Field Optimization
—The efficient application of graph cuts to Markov Random Fields (MRFs) with multiple discrete or continuous labels remains an open question. In this paper, we demonstrate one p...
Victor S. Lempitsky, Carsten Rother, Stefan Roth, ...
NAACL
2007
13 years 8 months ago
Data-Driven Graph Construction for Semi-Supervised Graph-Based Learning in NLP
Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely ...
Andrei Alexandrescu, Katrin Kirchhoff
CVPR
2009
IEEE
15 years 2 months ago
Higher-Order Clique Reduction in Binary Graph Cut
We introduce a new technique that can reduce any higher-order Markov random field with binary labels into a first-order one that has the same minima as the original. Moreover, w...
Hiroshi Ishikawa 0002