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» Clustering Rules Using Empirical Similarity of Support Sets
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TEC
2010
126views more  TEC 2010»
14 years 4 months ago
Learning the Large-Scale Structure of the MAX-SAT Landscape Using Populations
A new algorithm for solving MAX-SAT problems is introduced which clusters good solutions, and restarts the search from the closest feasible solution to the centroid of each cluster...
Mohamed Qasem, Adam Prügel-Bennett
IAT
2005
IEEE
15 years 3 months ago
Decomposing Large-Scale POMDP Via Belief State Analysis
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Xin Li, William K. Cheung, Jiming Liu
CORR
2010
Springer
157views Education» more  CORR 2010»
14 years 9 months ago
Efficient Clustering with Limited Distance Information
Given a point set S and an unknown metric d on S, we study the problem of efficiently partitioning S into k clusters while querying few distances between the points. In our model ...
Konstantin Voevodski, Maria-Florina Balcan, Heiko ...
FSKD
2008
Springer
174views Fuzzy Logic» more  FSKD 2008»
14 years 10 months ago
A Hybrid Re-sampling Method for SVM Learning from Imbalanced Data Sets
Support Vector Machine (SVM) has been widely studied and shown success in many application fields. However, the performance of SVM drops significantly when it is applied to the pr...
Peng Li, Pei-Li Qiao, Yuan-Chao Liu
72
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AUSAI
2003
Springer
15 years 2 months ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra