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» A Two-Level Approach to Making Class Predictions
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MICCAI
2010
Springer
13 years 3 months ago
Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...
BMCBI
2010
176views more  BMCBI 2010»
13 years 5 months ago
TargetSpy: a supervised machine learning approach for microRNA target prediction
Background: Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recen...
Martin Sturm, Michael Hackenberg, David Langenberg...
AAAI
2010
13 years 2 months ago
Latent Class Models for Algorithm Portfolio Methods
Different solvers for computationally difficult problems such as satisfiability (SAT) perform best on different instances. Algorithm portfolios exploit this phenomenon by predicti...
Bryan Silverthorn, Risto Miikkulainen
CVPR
2010
IEEE
14 years 1 months ago
Segmenting Video Into Classes of Algorithm-Suitability
Given a set of algorithms, which one(s) should you apply to, i) compute optical flow, or ii) perform feature matching? Would looking at the sequence in question help you decide? I...
Oisin Mac Aodha, Gabriel Brostow, marc Pollefeys
CORR
2006
Springer
96views Education» more  CORR 2006»
13 years 4 months ago
Metric entropy in competitive on-line prediction
Competitive on-line prediction (also known as universal prediction of individual sequences) is a strand of learning theory avoiding making any stochastic assumptions about the way...
Vladimir Vovk