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MICCAI
2010
Springer
13 years 6 months ago
Manifold Learning for Biomarker Discovery in MR Imaging
We propose a framework for the extraction of biomarkers from low-dimensional manifolds representing inter- and intra-subject brain variation in MR image data. The coordinates of ea...
Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Daniel...
LREC
2008
140views Education» more  LREC 2008»
13 years 10 months ago
Toward Active Learning in Data Selection: Automatic Discovery of Language Features During Elicitation
Data Selection has emerged as a common issue in language technologies. We define Data Selection as the choosing of a subset of training data that is most effective for a given tas...
Jonathan Clark, Robert E. Frederking, Lori S. Levi...
NIPS
2001
13 years 9 months ago
Active Learning in the Drug Discovery Process
We investigate the following data mining problem from Computational Chemistry: From a large data set of compounds, find those that bind to a target molecule in as few iterations o...
Manfred K. Warmuth, Gunnar Rätsch, Michael Ma...
WEBDB
2009
Springer
115views Database» more  WEBDB 2009»
14 years 3 months ago
A Machine Learning Approach to Foreign Key Discovery
We study the problem of automatically discovering semantic associations between schema elements, namely foreign keys. This problem is important in all applications where data sets...
Alexandra Rostin, Oliver Albrecht, Jana Bauckmann,...
BIOCOMP
2007
13 years 10 months ago
Biomarker Discovery Across Annotated and Unannotated Microarray Datasets Using Semi-Supervised Learning
The growing body of DNA microarray data has the potential to advance our understanding of the molecular basis of disease. However annotating microarray datasets with clinically us...
Cole Harris, Noushin Ghaffari