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» Two-Stage Machine Learning model for guideline development
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SIGIR
2012
ACM
11 years 11 months ago
Robust ranking models via risk-sensitive optimization
Many techniques for improving search result quality have been proposed. Typically, these techniques increase average effectiveness by devising advanced ranking features and/or by...
Lidan Wang, Paul N. Bennett, Kevyn Collins-Thompso...
GECCO
2007
Springer
149views Optimization» more  GECCO 2007»
14 years 2 months ago
Modeling XCS in class imbalances: population size and parameter settings
This paper analyzes the scalability of the population size required in XCS to maintain niches that are infrequently activated. Facetwise models have been developed to predict the ...
Albert Orriols-Puig, David E. Goldberg, Kumara Sas...
BMCBI
2010
118views more  BMCBI 2010»
13 years 8 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
IJCAI
1989
13 years 10 months ago
A Critique of the Valiant Model
This paper considers the Valiant framework as it is applied to the task of learning logical concepts from random examples. It is argued that the current interpretation of this Val...
Wray L. Buntine
ICML
2010
IEEE
13 years 9 months ago
The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling
The hierarchical Dirichlet process (HDP) is a Bayesian nonparametric mixed membership model--each data point is modeled with a collection of components of different proportions. T...
Sinead Williamson, Chong Wang, Katherine A. Heller...