ICDM
2010
IEEE
13 years 8 months ago
2010
IEEE
: D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-Defined Classification Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi HP Labo...
PR
2010
13 years 9 months ago
2010
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
PR
2006
13 years 10 months ago
2006
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
ICASSP
2010
IEEE
13 years 11 months ago
2010
IEEE
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
SDM
2004
SIAM
14 years 6 days ago
2004
SIAM
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
EWIMT
2004
14 years 7 days ago
2004
The identification of categories in image databases usually relies on clustering algorithms that only exploit the feature-based similarities between images. The addition of semant...
MLMTA
2007
14 years 8 days ago
2007
- Clustering plays an indispensable role for data analysis. Many clustering algorithms have been developed. However, most of them suffer either poor performance of unsupervised lea...
SDM
2008
SIAM
14 years 8 days ago
2008
SIAM
The recent years have witnessed a surge of interests of semi-supervised clustering methods, which aim to cluster the data set under the guidance of some supervisory information. U...
CIVR
2008
Springer
14 years 19 days ago
2008
Springer
Image clustering is useful in many retrieval and classification applications. The main goal of image clustering is to partition a given dataset into salient clusters such that the...
GECCO
2006
Springer
14 years 2 months ago
2006
Springer
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...