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ML
2008
ACM
110views Machine Learning» more  ML 2008»
8 years 1 months ago
A theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum, Nathan Srebro
ML
2008
ACM
174views Machine Learning» more  ML 2008»
8 years 2 months ago
ALLPAD: approximate learning of logic programs with annotated disjunctions
In this paper we present the system ALLPAD for learning Logic Programs with Annotated Disjunctions (LPADs). ALLPAD modifies the previous system LLPAD in order to tackle real world ...
Fabrizio Riguzzi
ML
2008
ACM
8 years 3 months ago
Flexible latent variable models for multi-task learning
Jian Zhang 0003, Zoubin Ghahramani, Yiming Yang
ML
2008
ACM
134views Machine Learning» more  ML 2008»
8 years 3 months ago
Multilabel classification via calibrated label ranking
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operat...
Johannes Fürnkranz, Eyke Hüllermeier, En...
ML
2008
ACM
150views Machine Learning» more  ML 2008»
8 years 3 months ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
ML
2008
ACM
8 years 3 months ago
Structured machine learning: the next ten years
Thomas G. Dietterich, Pedro Domingos, Lise Getoor,...
ML
2008
ACM
8 years 3 months ago
A bias/variance decomposition for models using collective inference
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen
ML
2008
ACM
222views Machine Learning» more  ML 2008»
8 years 3 months ago
Boosted Bayesian network classifiers
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
ML
2008
ACM
100views Machine Learning» more  ML 2008»
8 years 3 months ago
Convex multi-task feature learning
Andreas Argyriou, Theodoros Evgeniou, Massimiliano...
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