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ECCV
1998
Springer
16 years 8 months ago
Matching Hierarchical Structures Using Association Graphs
?It is well-known that the problem of matching two relational structures can be posed as an equivalent problem of finding a maximal clique in a (derived) ?association graph.? Howev...
Marcello Pelillo, Kaleem Siddiqi, Steven W. Zucker
ROCAI
2004
Springer
15 years 11 months ago
An Empirical Evaluation of Supervised Learning for ROC Area
We present an empirical comparison of the AUC performance of seven supervised learning methods: SVMs, neural nets, decision trees, k-nearest neighbor, bagged trees, boosted trees,...
Rich Caruana, Alexandru Niculescu-Mizil
HICSS
2008
IEEE
142views Biometrics» more  HICSS 2008»
15 years 6 months ago
K-Trunk and Efficient Algorithms for Finding a K-Trunk on a Tree Network
Given an edge-weighted tree T, a k-trunk is a subtree Tk with k leaves in T which minimizes the sum of the distances of all vertices in T from Tk plus the weight of Tk. In this pa...
Yamin Li, Shietung Peng, Wanming Chu
CORIA
2007
15 years 7 months ago
L'arbre recouvrant dans l'interrogation de documents XML
In this paper, we propose a fuzzy model to querying the XML documents, by taking into account not only the document contents, but also their structure. The concept of minimal size ...
Abdeslame Alilouar
ALGORITHMICA
2010
147views more  ALGORITHMICA 2010»
15 years 6 months ago
Note on the Structure of Kruskal's Algorithm
We study the merging process when Kruskal's algorithm is run with random graphs as inputs. Our aim is to analyze this process when the underlying graph is the complete graph ...
Nicolas Broutin, Luc Devroye, Erin McLeish