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» High-dimensional labeled data analysis with Gabriel graphs
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ALT
2008
Springer
14 years 4 months ago
Exploiting Cluster-Structure to Predict the Labeling of a Graph
Abstract. The nearest neighbor and the perceptron algorithms are intuitively motivated by the aims to exploit the “cluster” and “linear separation” structure of the data to...
Mark Herbster
ACSD
2005
IEEE
126views Hardware» more  ACSD 2005»
14 years 1 months ago
Modelling and Analysis of Distributed Simulation Protocols with Distributed Graph Transformation
This paper presents our approach to model distributed discrete event simulation systems in the framework of distributed graph transformation. We use distributed typed attributed g...
Juan de Lara, Gabriele Taentzer
KDD
2009
ACM
167views Data Mining» more  KDD 2009»
14 years 8 months ago
SNARE: a link analytic system for graph labeling and risk detection
Classifying nodes in networks is a task with a wide range of applications. It can be particularly useful in anomaly and fraud detection. Many resources are invested in the task of...
Mary McGlohon, Stephen Bay, Markus G. Anderle, Dav...
CORR
1999
Springer
164views Education» more  CORR 1999»
13 years 7 months ago
Annotation graphs as a framework for multidimensional linguistic data analysis
In recent work we have presented a formal framework for linguistic annotation based on labeled acyclic digraphs. These `annotation graphs' oer a simple yet powerful method fo...
Steven Bird, Mark Liberman
PAA
2002
13 years 7 months ago
Hierarchical Fusion of Multiple Classifiers for Hyperspectral Data Analysis
: Many classification problems involve high dimensional inputs and a large number of classes. Multiclassifier fusion approaches to such difficult problems typically centre around s...
Shailesh Kumar, Joydeep Ghosh, Melba M. Crawford