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Neurocomputing, Volume 192

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Volume 192, June 2016

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Fabio Aiolli, Kerstin Bunte, Romain Hérault, Mikhail F. Kanevski:
Special issue: Advances in artificial neural networks, machine learning and computational intelligenceSelected papers from the 23rd European Symposium on Artificial Neural Networks (ESANN 2015). 1-2

Advances in learning analytics and educational data mining

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Benjamin Paaßen, Bassam Mokbel, Barbara Hammer:
Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. 3-13
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  - journals/ijon/VahdatOAFR16
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Mehrnoosh Vahdat, Luca Oneto, Davide Anguita, Mathias Funk, Matthias Rauterberg:
Can machine learning explain human learning? 14-28

Regression and prediction

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Jens Schreiter, Duy Nguyen-Tuong, Marc Toussaint:
Efficient sparsification for Gaussian process regression. 29-37
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Arnaud De Myttenaere, Boris Golden, Bénédicte Le Grand, Fabrice Rossi:
Mean Absolute Percentage Error for regression models. 38-48

Reinforcement learning

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Robert Lieck, Marc Toussaint:
Temporally extended features in model-based reinforcement learning with partial observability. 49-60

Machine learning and optimization theory

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Jakramate Bootkrajang:
A generalised label noise model for classification in the presence of annotation errors. 61-71
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Guifang Zhou, Wen Huang, Kyle A. Gallivan, Paul Van Dooren, Pierre-Antoine Absil:
A Riemannian rank-adaptive method for low-rank optimization. 72-80

Graphs in machine learning

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Marco Corneli, Pierre Latouche, Fabrice Rossi:
Exact ICL maximization in a non-stationary temporal extension of the stochastic block model for dynamic networks. 81-91
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Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti:
Ordered Decompositional DAG kernels enhancements. 92-103

Prototype-based and weightless models

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Andrea Bohnsack, Kristin Domaschke, Marika Kaden, Mandy Lange, Thomas Villmann:
Learning matrix quantization and relevance learning based on Schatten-p-norms. 104-114
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Massimo De Gregorio, Maurizio Giordano:
Cloning DRASiW systems via memory transfer. 115-127

Sequence learning and time series

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Sebastian Otte, Martin V. Butz, Danil Koryakin, Fabian Becker, Marcus Liwicki, Andreas Zell:
Optimizing recurrent reservoirs with neuro-evolution. 128-138
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Nikolaos Gianniotis, Sven Dennis Kügler, Peter Tiño, Kai Lars Polsterer:
Model-coupled autoencoder for time series visualisation. 139-146

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