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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
CVPR
2004
IEEE
14 years 10 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
KCAP
2011
ACM
12 years 11 months ago
LinkedDataLens: linked data as a network of networks
With billions of assertions and counting, the Web of Data represents the largest multi-contributor interlinked knowledge base that ever existed. We present a novel framework for a...
Yolanda Gil, Paul T. Groth
WWW
2010
ACM
14 years 3 months ago
Visualizing differences in web search algorithms using the expected weighted hoeffding distance
We introduce a new dissimilarity function for ranked lists, the expected weighted Hoeffding distance, that has several advantages over current dissimilarity measures for ranked s...
Mingxuan Sun, Guy Lebanon, Kevyn Collins-Thompson
BMCBI
2006
150views more  BMCBI 2006»
13 years 8 months ago
Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains
Background: The subcellular location of a protein is closely related to its function. It would be worthwhile to develop a method to predict the subcellular location for a given pr...
Alla Bulashevska, Roland Eils