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» Algorithms for Clustering Data
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MVA
2010
130views Computer Vision» more  MVA 2010»
15 years 4 months ago
Neighborhood linear embedding for intrinsic structure discovery
In this paper, an unsupervised learning algorithm, neighborhood linear embedding (NLE), is proposed to discover the intrinsic structures such as neighborhood relationships, global ...
Shuzhi Sam Ge, Feng Guan, Yaozhang Pan, Ai Poh Loh
140
Voted
ICPR
2008
IEEE
16 years 17 days ago
Combining hierarchical clusterings using min-transitive closure
In the past, clusterings combination approaches are based on “flat” clustering algorithms, i.e. algorithms that operate on non-hierarchical clustering schemes. These approache...
Abdolreza Mirzaei, Mohammad Rahmati
147
Voted
CIKM
2004
Springer
15 years 11 months ago
Mining gene expression datasets using density-based clustering
Given the recent advancement of microarray technologies, we present a density-based clustering approach for the purpose of co-expressed gene cluster identification. The underlyin...
Seokkyung Chung, Jongeun Jun, Dennis McLeod
JCST
2008
124views more  JCST 2008»
15 years 6 months ago
Clustering by Pattern Similarity
The task of clustering is to identify classes of similar objects among a set of objects. The definition of similarity varies from one clustering model to another. However, in most ...
Haixun Wang, Jian Pei
153
Voted
ICARIS
2005
Springer
15 years 11 months ago
Two Ways to Grow Tissue for Artificial Immune Systems
An immune system without tissue is like evolution without genes. Something very important is missing. Here we present the novel concept of tissue for artificial immune systems. Muc...
Peter J. Bentley, Julie Greensmith, Supiya Ujjin