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» Sensing-aware classification with high-dimensional data
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BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
13 years 10 months ago
What should be expected from feature selection in small-sample settings
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
Chao Sima, Edward R. Dougherty
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 11 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
BMCBI
2010
126views more  BMCBI 2010»
13 years 11 months ago
A boosting method for maximizing the partial area under the ROC curve
Background: The receiver operating characteristic (ROC) curve is a fundamental tool to assess the discriminant performance for not only a single marker but also a score function c...
Osamu Komori, Shinto Eguchi
ECCV
2008
Springer
15 years 19 days ago
Simultaneous Detection and Registration for Ileo-Cecal Valve Detection in 3D CT Colonography
Object detection and recognition has achieved a significant progress in recent years. However robust 3D object detection and segmentation in noisy 3D data volumes remains a challen...
Le Lu, Adrian Barbu, Matthias Wolf, Jianming Liang...
CIKM
2010
Springer
13 years 8 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan