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» Learning to cluster using local neighborhood structure
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KDD
2006
ACM
156views Data Mining» more  KDD 2006»
15 years 10 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
GECCO
2009
Springer
254views Optimization» more  GECCO 2009»
15 years 4 months ago
Agglomerative genetic algorithm for clustering in social networks
Size and complexity of data repositories collaboratively created by Web users generate a need for new processing approaches. In this paper, we study the problem of detection of ï¬...
Marek Lipczak, Evangelos E. Milios
ECCV
2008
Springer
15 years 11 months ago
Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...
VLUDS
2010
232views Visualization» more  VLUDS 2010»
14 years 4 months ago
Methods for Feature Detection in Point Clouds
This paper gives an overview over several techniques for detection of features, and in particular sharp features, on point-sampled geometry. In addition, a new technique using the...
Christopher Weber, Stefanie Hahmann, Hans Hagen
CLEF
2009
Springer
14 years 10 months ago
MorphoNet: Exploring the Use of Community Structure for Unsupervised Morpheme Analysis
This paper investigates a novel approach to unsupervised morphology induction relying on community detection in networks. In a first step, morphological transformation rules are a...
Delphine Bernhard