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KDD
2010
ACM
245views Data Mining» more  KDD 2010»
15 years 7 months ago
Flexible constrained spectral clustering
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
Xiang Wang, Ian Davidson
BMCBI
2008
142views more  BMCBI 2008»
15 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
ISCC
2002
IEEE
131views Communications» more  ISCC 2002»
15 years 8 months ago
Scheduling real time parallel structure on cluster computing
: - Efficient task scheduling is essential for achieving high performance computing applications for distributed systems. Most of existing real-time systems consider schedulability...
Reda A. Ammar, Abdulrahman Alhamdan
CORR
2010
Springer
155views Education» more  CORR 2010»
15 years 4 months ago
Repairing People Trajectories Based on Point Clustering
This paper presents a method for improving any object tracking algorithm based on machine learning. During the training phase, important trajectory features are extracted which are...
Duc Phu Chau, François Brémond, Etie...
LCPC
2007
Springer
15 years 10 months ago
Supporting Huge Address Spaces in a Virtual Machine for Java on a Cluster
Abstract. To solve problems that require far more memory than a single machine can supply, data can be swapped to disk in some manner, it can be compressed, and/or the memory of mu...
Ronald Veldema, Michael Philippsen