Sciweavers

15 search results - page 1 / 3
» Genetic operators for hierarchical graph clustering
Sort
View
PRL
1998
91views more  PRL 1998»
13 years 4 months ago
Genetic operators for hierarchical graph clustering
In this paper we propose an encoding scheme and ad hoc operators for a genetic approach to hierarchical graph clustering. Given a connected graph whose vertices correspond to poin...
Stefano Rizzi
AAAI
2008
13 years 7 months ago
Visualization of Large-Scale Weighted Clustered Graph: A Genetic Approach
In this paper, a bottom-up hierarchical genetic algorithm is proposed to visualize clustered data into a planar graph. To achieve global optimization by accelerating local optimiz...
Jiayu Zhou, Youfang Lin, Xi Wang
PLDI
2003
ACM
13 years 10 months ago
Region-based hierarchical operation partitioning for multicluster processors
Clustered architectures are a solution to the bottleneck of centralized register files in superscalar and VLIW processors. The main challenge associated with clustered architectu...
Michael L. Chu, Kevin Fan, Scott A. Mahlke
ICEC
1994
86views more  ICEC 1994»
13 years 6 months ago
A Genetic Algorithm for Channel Routing using Inter-Cluster Mutation
In this paper, we propose an algorithm for the channel routing problem based on genetic approach that uses a new type of mutation, called inter-cluster mutation . The performance ...
B. B. Prahlada Rao, Lalit M. Patnaik, R. C. Hansda...
BMCBI
2008
142views more  BMCBI 2008»
13 years 4 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu