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ECML
2007
Springer
15 years 9 months ago
Learning to Classify Documents with Only a Small Positive Training Set
Many real-world classification applications fall into the class of positive and unlabeled (PU) learning problems. In many such applications, not only could the negative training ex...
Xiaoli Li, Bing Liu, See-Kiong Ng
ECML
2006
Springer
15 years 6 months ago
Bayesian Active Learning for Sensitivity Analysis
Abstract. Designs of micro electro-mechanical devices need to be robust against fluctuations in mass production. Computer experiments with tens of parameters are used to explore th...
Tobias Pfingsten
ICML
2010
IEEE
15 years 4 months ago
Bayesian Multi-Task Reinforcement Learning
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Alessandro Lazaric, Mohammad Ghavamzadeh
ECML
2001
Springer
15 years 7 months ago
Classification on Data with Biased Class Distribution
Labeled data for classification could often be obtained by sampling that restricts or favors choice of certain classes. A classifier trained using such data will be biased, resulti...
Slobodan Vucetic, Zoran Obradovic
ECTEL
2006
Springer
15 years 6 months ago
A Formal Model of Learning Object Metadata
In this paper, we introduce a new, formal model of learning object metadata. The model enables more formal, rigorous reasoning over metadata. An important feature of the model is t...
Kris Cardinaels, Erik Duval, Henk J. Olivié