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CVPR
2005
IEEE
14 years 10 months ago
A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin
HIS
2004
13 years 9 months ago
Selection of Time Series Forecasting Models based on Performance Information
In this work, we proposed to use the Zoomed Ranking approach to rank and select time series models. Zoomed Ranking, originally proposed to generate a ranking of candidate algorith...
Patrícia Maforte dos Santos, Teresa Bernard...
KDD
2010
ACM
318views Data Mining» more  KDD 2010»
13 years 6 months ago
DivRank: the interplay of prestige and diversity in information networks
Information networks are widely used to characterize the relationships between data items such as text documents. Many important retrieval and mining tasks rely on ranking the dat...
Qiaozhu Mei, Jian Guo, Dragomir R. Radev
ICDCIT
2005
Springer
14 years 1 months ago
FlexiRank: An Algorithm Offering Flexibility and Accuracy for Ranking the Web Pages
The existing search engines sometimes give unsatisfactory search result for lack of any categorization. If there is some means to know the preference of user about the search resul...
Debajyoti Mukhopadhyay, Pradipta Biswas
TKDE
2008
115views more  TKDE 2008»
13 years 8 months ago
A Niching Memetic Algorithm for Simultaneous Clustering and Feature Selection
Clustering is inherently a difficult task and is made even more difficult when the selection of relevant features is also an issue. In this paper, we propose an approach for simult...
Weiguo Sheng, Xiaohui Liu, Michael C. Fairhurst