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105
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MICCAI
2010
Springer
14 years 11 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...
100
Voted
ICPR
2006
IEEE
16 years 1 months ago
Learning Wormholes for Sparsely Labelled Clustering
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Eng-Jon Ong, Richard Bowden
ACL
2009
14 years 10 months ago
A Graph-based Semi-Supervised Learning for Question-Answering
We present a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate sentences. Using textual entailment analysis, we obtain entailment sco...
Asli Çelikyilmaz, Marcus Thint, Zhiheng Hua...
FLAIRS
2007
15 years 3 months ago
Mining Sequences in Distributed Sensors Data for Energy Production
The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is conce...
Mehmed M. Kantardzic, John Gant
117
Voted
ICASSP
2011
IEEE
14 years 4 months ago
Sensing-aware classification with high-dimensional data
In many applications decisions must be made about the state of an object based on indirect noisy observation of highdimensional data. An example is the determination of the presen...
Burkay Orten, Prakash Ishwar, W. Clem Karl, Venkat...