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ICCV
2011
IEEE
14 years 6 months ago
Learning to Cluster Using High Order Graphical Models with Latent Variables
This paper proposes a very general max-margin learning framework for distance-based clustering. To this end, it formulates clustering as a high order energy minimization problem w...
Nikos Komodakis
BMCBI
2008
105views more  BMCBI 2008»
15 years 6 months ago
Using the longest significance run to estimate region-specific p-values in genetic association mapping studies
Background: Association testing is a powerful tool for identifying disease susceptibility genes underlying complex diseases. Technological advances have yielded a dramatic increas...
Ie-Bin Lian, Yi-Hsien Lin, Ying-Chao Lin, Hsin-Cho...
NN
2006
Springer
163views Neural Networks» more  NN 2006»
15 years 6 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine
ICCS
2009
Springer
16 years 1 months ago
Frequent Itemset Mining for Clustering Near Duplicate Web Documents
A vast amount of documents in the Web have duplicates, which is a challenge for developing efficient methods that would compute clusters of similar documents. In this paper we use ...
Dmitry I. Ignatov, Sergei O. Kuznetsov
ICPR
2008
IEEE
16 years 29 days ago
Kernel Bisecting k-means clustering for SVM training sample reduction
This paper presents a new algorithm named Kernel Bisecting k-means and Sample Removal (KBK-SR) as a sampling preprocessing for SVM training to improve the scalability. The novel c...
Xiao-Zhang Liu, Guo-Can Feng