Stefan Faußer
Stefan Faußer
Neu-Ulm University of Applied Science (HNU)
Adresse e-mail validée de hnu.de - Page d'accueil
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Neural network ensembles in reinforcement learning
S Faußer, F Schwenker
Neural Processing Letters 41 (1), 55-69, 2015
392015
Ensemble methods for reinforcement learning with function approximation
S Faußer, F Schwenker
International Workshop on Multiple Classifier Systems, 56-65, 2011
272011
Selective neural network ensembles in reinforcement learning: taking the advantage of many agents
S Faußer, F Schwenker
Neurocomputing 169, 350-357, 2015
212015
Semi-Supervised kernel clustering with sample-to-cluster weights
S Faußer, F Schwenker
IAPR International Workshop on Partially Supervised Learning, 72-81, 2011
102011
Semi-supervised clustering of large data sets with kernel methods
S Faußer, F Schwenker
Pattern recognition letters 37, 78-84, 2014
92014
Learning a strategy with neural approximated temporal-difference methods in english draughts
S Faußer, F Schwenker
2010 20th International Conference on Pattern Recognition, 2925-2928, 2010
92010
Clustering large datasets with kernel methods
S Fausser, F Schwenker
Pattern Recognition (ICPR), 2012 21st International Conference on, 501-504, 2012
8*2012
Neural approximation of monte carlo policy evaluation deployed in connect four
S Faußer, F Schwenker
IAPR Workshop on Artificial Neural Networks in Pattern Recognition, 90-100, 2008
72008
Parallelized kernel patch clustering
S Faußer, F Schwenker
IAPR Workshop on Artificial Neural Networks in Pattern Recognition, 131-140, 2010
62010
Selective Neural Network Ensembles in Reinforcement Learning
S Faußer, F Schwenker
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2014
42014
Predicting Social Perception from Faces: A Deep Learning Approach
U Messer, S Fausser
arXiv preprint arXiv:1907.00217, 2019
22019
Machine Learning Infusion in Service Processes
U Messer, S Faußer
Automatisierung und Personalisierung von Dienstleistungen, 343-364, 2020
2020
Large state spaces and large data: Utilizing neural network ensembles in reinforcement learning and kernel methods for clustering
SA Faußer
Universität Ulm, 2015
2015
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