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JCT
2007
94views more  JCT 2007»
15 years 22 days ago
A zero-free interval for flow polynomials of cubic graphs
Let P(G,t) and F(G,t) denote the chromatic and flow polynomials of a graph G. D.R. Woodall has shown that, if G is a plane triangulation, then the only zeros of P(G,t) in (−∞...
Bill Jackson
121
Voted
ICDM
2009
IEEE
139views Data Mining» more  ICDM 2009»
14 years 10 months ago
Frequent Pattern Discovery from a Single Graph with Quantitative Itemsets
In this paper, we focus on a single graph whose vertices contain a set of quantitative attributes. Several networks can be naturally represented in this complex graph. An example i...
Yuuki Miyoshi, Tomonobu Ozaki, Takenao Ohkawa
CVPR
2009
IEEE
16 years 8 months ago
A Revisit of Generative Model for Automatic Image Annotation using Markov Random Fields
Much research effort on Automatic Image Annotation (AIA) has been focused on Generative Model, due to its well formed theory and competitive performance as compared with many we...
Yu Xiang (Fudan University), Xiangdong Zhou (Fudan...
120
Voted
ECCV
2008
Springer
16 years 2 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 4 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing