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LATIN
2010
Springer
14 years 4 months ago
Kernelization through Tidying
Abstract. We introduce the NP-hard graph-based data clustering problem s-Plex Cluster Vertex Deletion, where the task is to delete at most k vertices from a graph so that the conne...
René van Bevern, Hannes Moser, Rolf Niederm...
ICPR
2008
IEEE
14 years 4 months ago
Semi-supervised learning by locally linear embedding in kernel space
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
Rujie Liu, Yuehong Wang, Takayuki Baba, Daiki Masu...
ICML
2008
IEEE
14 years 10 months ago
The skew spectrum of graphs
The central issue in representing graphstructured data instances in learning algorithms is designing features which are invariant to permuting the numbering of the vertices. We pr...
Risi Imre Kondor, Karsten M. Borgwardt
NIPS
2008
13 years 11 months ago
Bayesian Network Score Approximation using a Metagraph Kernel
Many interesting problems, including Bayesian network structure-search, can be cast in terms of finding the optimum value of a function over the space of graphs. However, this fun...
Benjamin Yackley, Eduardo Corona, Terran Lane
NIPS
2004
13 years 11 months ago
An Application of Boosting to Graph Classification
This paper presents an application of Boosting for classifying labeled graphs, general structures for modeling a number of real-world data, such as chemical compounds, natural lan...
Taku Kudo, Eisaku Maeda, Yuji Matsumoto