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» K-means clustering via principal component analysis
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DAS
2006
Springer
13 years 11 months ago
Efficient Word Retrieval by Means of SOM Clustering and PCA
Abstract. We propose an approach for efficient word retrieval from printed documents belonging to Digital Libraries. The approach combines word image clustering (based on Self Orga...
Simone Marinai, Stefano Faini, Emanuele Marino, Gi...
SSDBM
2008
IEEE
114views Database» more  SSDBM 2008»
14 years 1 months ago
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
Hans-Peter Kriegel, Peer Kröger, Erich Schube...
DIAL
2006
IEEE
167views Image Analysis» more  DIAL 2006»
14 years 1 months ago
Tree clustering for layout-based document image retrieval
We describe a system for the retrieval on the basis of layout similarity of document images belonging to collections stored in digital libraries. Layout regions are extracted and ...
Simone Marinai, Emanuele Marino, Giovanni Soda
ORL
2011
13 years 2 months ago
Convex approximations to sparse PCA via Lagrangian duality
We derive a convex relaxation for cardinality constrained Principal Component Analysis (PCA) by using a simple representation of the L1 unit ball and standard Lagrangian duality. ...
Ronny Luss, Marc Teboulle
ICAD
2004
13 years 9 months ago
Designing Sound: Towards a System for Designing Audio Interfaces using Timbre Spaces
The creation of audio interfaces is currently hampered by the difficulty of designing sounds for them. This paper presents a novel system for generating and manipulating non-speec...
Craig Nicol, Stephen A. Brewster, Philip D. Gray