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Neurocomputing, Volume 342
Volume 342, May 2019
- Luca Oneto
, Kerstin Bunte
Advances in artificial neural networks, machine learning and computational intelligence: Selected papers from the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018). 1-5
- Khadija Musayeva, Fabien Lauer
Rademacher complexity and generalization performance of multi-category margin classifiers. 6-15 - Joseph Rynkiewicz:
Asymptotic statistics for multilayer perceptron with ReLU hidden units. 16-23
- Luca Oneto
Local Rademacher Complexity Machine. 24-32 - Tommi Kärkkäinen:
Extreme minimal learning machine: Ridge regression with distance-based basis. 33-48 - Davide Bacciu
Bayesian mixtures of Hidden Tree Markov Models for structured data clustering. 49-59
- Josef Feigl, Martin Bogdan:
Neural networks for personalized item rankings. 60-65 - Jan M. Wülfing, Sreedhar S. Kumar
Adaptive long-term control of biological neural networks with Deep Reinforcement Learning. 66-74 - Tayfun Alpay, Fares Abawi
Preserving activations in recurrent neural networks based on surprisal. 75-82
- Rebecca Marion
BIR: A method for selecting the best interpretable multidimensional scaling rotation using external variables. 83-96 - Borja Seijo-Pardo, Amparo Alonso-Betanzos
Biases in feature selection with missing data. 97-112
- Mirko Polato
Boolean kernels for rule based interpretation of support vector machines. 113-124 - Johannes Brinkrolf
Differential privacy for learning vector quantization. 125-136
- Stefan Heinrich
Continuous convolutional object tracking in developmental robot scenarios. 137-144 - Miguel Angrick
Interpretation of convolutional neural networks for speech spectrogram regression from intracranial recordings. 145-151 - Niall Twomey
An application of hierarchical Gaussian processes to the detection of anomalies in star light curves. 152-163 - Mohammad Mohammadi
Globular cluster detection in the GAIA survey. 164-171 - Aleke Nolte, Lingyu Wang, Maciej Bilicki, Benne Holwerda, Michael Biehl
Galaxy classification: A machine learning analysis of GAMA catalogue data. 172-190
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