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ICPR
2010
IEEE
15 years 5 months ago
Adaptive Incremental Learning with an Ensemble of Support Vector Machines
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incre...
Marcelo N. Kapp, Robert Sabourin, Patrick Maupin
136
Voted
BMCBI
2008
136views more  BMCBI 2008»
15 years 5 months ago
A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model
Background: Bioactivity profiling using high-throughput in vitro assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also r...
Richard Judson, Fathi Elloumi, R. Woodrow Setzer, ...
IJAR
2010
152views more  IJAR 2010»
15 years 3 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
111
Voted
ICASSP
2010
IEEE
15 years 3 months ago
Efficient online learning with individual learning-rates for phoneme sequence recognition
We describe a fast and efficient online algorithm for phoneme sequence speech recognition. Our method is using a discriminative training to update the model parameters one utteran...
Koby Crammer
IEAAIE
2010
Springer
15 years 2 months ago
Web Usage Mining for Improving Students Performance in Learning Management Systems
An innovative technique based on multi-objective grammar guided genetic programming (MOG3P-MI) is proposed to detect the most relevant activities that a student needs to pass a cou...
Amelia Zafra, Sebastián Ventura