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CVPR
2007
IEEE
16 years 6 months ago
Solving Large Scale Binary Quadratic Problems: Spectral Methods vs. Semidefinite Programming
In this paper we introduce two new methods for solving binary quadratic problems. While spectral relaxation methods have been the workhorse subroutine for a wide variety of comput...
Carl Olsson, Anders P. Eriksson, Fredrik Kahl
KDD
2009
ACM
243views Data Mining» more  KDD 2009»
16 years 5 months ago
Exploiting Wikipedia as external knowledge for document clustering
In traditional text clustering methods, documents are represented as "bags of words" without considering the semantic information of each document. For instance, if two ...
Xiaohua Hu, Xiaodan Zhang, Caimei Lu, E. K. Park, ...
BMCBI
2007
123views more  BMCBI 2007»
15 years 4 months ago
Robust clustering in high dimensional data using statistical depths
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
Yuanyuan Ding, Xin Dang, Hanxiang Peng, Dawn Wilki...
ACL
1997
15 years 5 months ago
Document Classification Using a Finite Mixture Model
We propose a new method of classifying documents into categories. We define for each category a finite mixture model based on soft clustering of words. We treat the problem of cla...
Hang Li, Kenji Yamanishi
ICIP
2009
IEEE
15 years 2 months ago
A hierarchical graph-based markovian clustering approach for the unsupervised segmentation of textured color images
In this paper, a new unsupervised hierarchical approach to textured color images segmentation is proposed. To this end, we have designed a two-step procedure based on a grey-scale...
Rachid Hedjam, Max Mignotte