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» A framework for visual data mining of structures
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ICDM
2005
IEEE
109views Data Mining» more  ICDM 2005»
14 years 2 months ago
Triple Jump Acceleration for the EM Algorithm
This paper presents the triple jump framework for accelerating the EM algorithm and other bound optimization methods. The idea is to extrapolate the third search point based on th...
Han-Shen Huang, Bou-Ho Yang, Chun-Nan Hsu
DAGM
2009
Springer
14 years 3 months ago
Active Structured Learning for High-Speed Object Detection
High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system th...
Christoph H. Lampert, Jan Peters
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 9 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...
CVPR
2012
IEEE
11 years 11 months ago
Fixed-rank representation for unsupervised visual learning
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...
PAKDD
2009
ACM
233views Data Mining» more  PAKDD 2009»
14 years 1 months ago
A Kernel Framework for Protein Residue Annotation
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...