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BMCBI
2004
140views more  BMCBI 2004»
15 years 4 months ago
What can we learn from noncoding regions of similarity between genomes?
Background: In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to as...
Thomas A. Down, Tim J. P. Hubbard
CORR
2002
Springer
95views Education» more  CORR 2002»
15 years 4 months ago
Unsupervised Learning of Morphology without Morphemes
The first morphological learner based upon the theory of Whole Word Morphology (Ford et al., 1997) is outlined, and preliminary evaluation results are presented. The program, Whol...
Sylvain Neuvel, Sean A. Fulop
176
Voted
JMLR
2011
192views more  JMLR 2011»
14 years 12 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
PAMI
2011
14 years 12 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
CVPR
2012
IEEE
13 years 7 months ago
Discriminately decreasing discriminability with learned image filters
In machine learning and computer vision, input signals are often filtered to increase data discriminability. For example, preprocessing face images with Gabor band-pass filters ...
Jacob Whitehill, Javier R. Movellan