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UAI
2004
13 years 9 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
BIRTHDAY
2010
Springer
13 years 8 months ago
The Edge of Graph Transformation - Graphs for Behavioural Specification
The title of this paper, besides being a pun, can be taken to mean either the frontier of research in graph transformation, or the advantage of using graph transformation. To focus...
Arend Rensink
KDD
2008
ACM
142views Data Mining» more  KDD 2008»
14 years 8 months ago
Weighted graphs and disconnected components: patterns and a generator
The vast majority of earlier work has focused on graphs which are both connected (typically by ignoring all but the giant connected component), and unweighted. Here we study numer...
Mary McGlohon, Leman Akoglu, Christos Faloutsos
ICML
2003
IEEE
14 years 9 months ago
Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries
Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of ...
Jeremy Kubica, Andrew W. Moore, David Cohn, Jeff G...
ICPR
2008
IEEE
14 years 9 months ago
Supervised learning of a generative model for edge-weighted graphs
This paper addresses the problem of learning archetypal structural models from examples. To this end we define a generative model for graphs where the distribution of observed nod...
Andrea Torsello, David L. Dowe