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ICMLA
2009
14 years 10 months ago
Learning Probabilistic Structure Graphs for Classification and Detection of Object Structures
Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
Johannes Hartz
UAI
2004
15 years 1 months ago
Convolutional Factor Graphs as Probabilistic Models
Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...
Yongyi Mao, Frank R. Kschischang, Brendan J. Frey
108
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ICTAI
2007
IEEE
15 years 6 months ago
A Probabilistic Substructure-Based Approach for Graph Classification
The classification of graph based objects is an important challenge from a knowledge discovery standpoint and has attracted considerable attention recently. In this paper, we pres...
H. D. K. Moonesinghe, Hamed Valizadegan, Samah Jam...
SDM
2012
SIAM
294views Data Mining» more  SDM 2012»
13 years 2 months ago
Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
Tinghui Zhou, Hanhuai Shan, Arindam Banerjee, Guil...
109
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ICASSP
2008
IEEE
15 years 7 months ago
Probabilistic framework for gene expression clustering validation based on gene ontology and graph theory
Based on the correlation between expression and ontologydriven gene similarity, we incorporate functional annotations into gene expression clustering validation. A probabilistic f...
Yinyin Yuan, Chang-Tsun Li