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» Approximation algorithms for projective clustering
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86
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STOC
2004
ACM
88views Algorithms» more  STOC 2004»
16 years 1 months ago
Expander flows, geometric embeddings and graph partitioning
We give a O( log n)-approximation algorithm for sparsest cut, edge expansion, balanced separator, and graph conductance problems. This improves the O(log n)-approximation of Leig...
Sanjeev Arora, Satish Rao, Umesh V. Vazirani
87
Voted
ICDAR
2007
IEEE
15 years 7 months ago
Robust Document Warping with Interpolated Vector Fields
This paper describes a new versatile algorithm for correcting nonlinear distortions, such as curvature of book pages, in camera based document processing. We introduce the idea of...
D. Schneider, Marco Block, Raúl Rojas
121
Voted
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
16 years 1 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler
112
Voted
ANOR
2010
125views more  ANOR 2010»
15 years 27 days ago
A Bayesian approach for the alignment of high-resolution NMR spectra
: The rapid progresses in human genome project and biotechnologies result in the sheer volume of datasets associated with in-depth scientific knowledge. Metabolomics is defined as ...
Seoung Bum Kim, Zhou Wang, Basavaraj Hiremath
107
Voted
APPT
2005
Springer
15 years 6 months ago
Principal Component Analysis for Distributed Data Sets with Updating
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
Zheng-Jian Bai, Raymond H. Chan, Franklin T. Luk