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BMCBI
2007
146views more  BMCBI 2007»
15 years 1 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
AAAI
2008
15 years 3 months ago
Clustering via Random Walk Hitting Time on Directed Graphs
In this paper, we present a general data clustering algorithm which is based on the asymmetric pairwise measure of Markov random walk hitting time on directed graphs. Unlike tradi...
Mo Chen, Jianzhuang Liu, Xiaoou Tang
CVPR
2011
IEEE
14 years 9 months ago
From Region Similarity to Category Discovery
The goal of object category discovery is to automatically identify groups of image regions which belong to some new, previously unseen category. This task is typically performed i...
Carolina Galleguillos, Brian McFee, Serge Belongie...
KAIS
2006
126views more  KAIS 2006»
15 years 1 months ago
Fast and exact out-of-core and distributed k-means clustering
Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...
Ruoming Jin, Anjan Goswami, Gagan Agrawal
KDD
2002
ACM
293views Data Mining» more  KDD 2002»
16 years 1 months ago
Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
Alexander Ypma, Tom Heskes