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» Group-based learning: a boosting approach
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KDD
2009
ACM
249views Data Mining» more  KDD 2009»
14 years 8 months ago
Drosophila gene expression pattern annotation using sparse features and term-term interactions
The Drosophila gene expression pattern images document the spatial and temporal dynamics of gene expression and they are valuable tools for explicating the gene functions, interac...
Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, ...
CVPR
2006
IEEE
14 years 9 months ago
Applying Ensembles of Multilinear Classifiers in the Frequency Domain
Ensemble methods such as bootstrap, bagging or boosting have had a considerable impact on recent developments in machine learning, pattern recognition and computer vision. Theoret...
Christian Bauckhage, Thomas Käster, John K. T...
WSDM
2009
ACM
161views Data Mining» more  WSDM 2009»
14 years 2 months ago
Predicting the readability of short web summaries
Readability is a crucial presentation attribute that web summarization algorithms consider while generating a querybaised web summary. Readability quality also forms an important ...
Tapas Kanungo, David Orr
CIVR
2007
Springer
144views Image Analysis» more  CIVR 2007»
14 years 1 months ago
Image retrieval on large-scale image databases
Online image repositories such as Flickr contain hundreds of millions of images and are growing quickly. Along with that the needs for supporting indexing, searching and browsing ...
Eva Hörster, Rainer Lienhart, Malcolm Slaney
ESANN
2006
13 years 8 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...