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» The complexity of learning SUBSEQ(A)
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SIGSOFT
2009
ACM
16 years 6 months ago
Automatic steering of behavioral model inference
Many testing and analysis techniques use finite state models to validate and verify the quality of software systems. Since the specification of such models is complex and timecons...
David Lo, Leonardo Mariani, Mauro Pezzè
KDD
2009
ACM
152views Data Mining» more  KDD 2009»
16 years 6 months ago
A multi-relational approach to spatial classification
Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...
Richard Frank, Martin Ester, Arno Knobbe
KDD
2009
ACM
611views Data Mining» more  KDD 2009»
16 years 6 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
KDD
2007
ACM
249views Data Mining» more  KDD 2007»
16 years 6 months ago
The minimum consistent subset cover problem and its applications in data mining
In this paper, we introduce and study the Minimum Consistent Subset Cover (MCSC) problem. Given a finite ground set X and a constraint t, find the minimum number of consistent sub...
Byron J. Gao, Martin Ester, Jin-yi Cai, Oliver Sch...
KDD
2003
ACM
180views Data Mining» more  KDD 2003»
16 years 6 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han