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ICPR
2006
IEEE
16 years 5 months ago
A New Data Selection Principle for Semi-Supervised Incremental Learning
Current semi-supervised incremental learning approaches select unlabeled examples with predicted high confidence for model re-training. We show that for many applications this dat...
Alexander I. Rudnicky, Rong Zhang
MICCAI
2006
Springer
16 years 5 months ago
MR Image Segmentation Using Phase Information and a Novel Multiscale Scheme
This paper considers the problem of automatic classification of textured tissues in 3D MRI. More specifically, it aims at validating the use of features extracted from the phase of...
Jurgen Fripp, Peter Stanwell, Pierrick Bourgeat, S...
ICML
2006
IEEE
16 years 5 months ago
Experience-efficient learning in associative bandit problems
We formalize the associative bandit problem framework introduced by Kaelbling as a learning-theory problem. The learning environment is modeled as a k-armed bandit where arm payof...
Alexander L. Strehl, Chris Mesterharm, Michael L. ...
ISBI
2006
IEEE
16 years 5 months ago
A multiresolution enhancement to generic classifiers of subcellular protein location images
We propose an algorithm for the classification of fluorescence microscopy images depicting the spatial distribution of proteins within the cell. The problem is at the forefront of...
Thomas E. Merryman, Keridon Williams, Gowri Sriniv...
IEEEICCI
2006
IEEE
15 years 10 months ago
Using Feature Selection Filtering Methods for Binding Site Predictions
Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. In previous work we applied classification techniques on predictio...
Yi Sun, Mark Robinson, Rod Adams, Rene te Boekhors...