Stefan Faußer
Stefan Faußer
Neu-Ulm University of Applied Science (HNU)
Email verificata su - Home page
Citata da
Citata da
Neural network ensembles in reinforcement learning
S Faußer, F Schwenker
Neural Processing Letters 41, 55-69, 2015
Ensemble methods for reinforcement learning with function approximation
S Faußer, F Schwenker
Multiple Classifier Systems: 10th International Workshop, MCS 2011, Naples …, 2011
Selective neural network ensembles in reinforcement learning: taking the advantage of many agents
S Faußer, F Schwenker
Neurocomputing 169, 350-357, 2015
Predicting social perception from faces: A deep learning approach
U Messer, S Fausser
arXiv preprint arXiv:1907.00217, 2019
Semi-supervised kernel clustering with sample-to-cluster weights
S Faußer, F Schwenker
Partially Supervised Learning: First IAPR TC3 Workshop, PSL 2011, Ulm …, 2012
Semi-supervised clustering of large data sets with kernel methods
S Faußer, F Schwenker
Pattern recognition letters 37, 78-84, 2014
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
Clustering large datasets with kernel methods
S Fausser, F Schwenker
Pattern Recognition (ICPR), 2012 21st International Conference on, 501-504, 2012
Neural approximation of monte carlo policy evaluation deployed in connect four
S Faußer, F Schwenker
Artificial Neural Networks in Pattern Recognition: Third IAPR Workshop …, 2008
Parallelized kernel patch clustering
S Faußer, F Schwenker
Artificial Neural Networks in Pattern Recognition: 4th IAPR TC3 Workshop …, 2010
Selective Neural Network Ensembles in Reinforcement Learning
S Faußer, F Schwenker
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2014
Face Value: On the Impact of Annotation (In-) Consistencies and Label Ambiguity in Facial Data on Emotion Recognition
J Gebele, P Brune, S Faußer
2022 26th International Conference on Pattern Recognition (ICPR), 2597-2604, 2022
Using NLP to analyze whether customer statements comply with their inner belief
F Thaler, S Faußer, H Gewald
arXiv preprint arXiv:2107.11175, 2021
Put your money where your mouth is: Using AI voice analysis to detect whether spoken arguments reflect the speaker's true convictions.
F Thaler, S Faußer, H Gewald
CoRR, 2021
Machine Learning Infusion in Service Processes
U Messer, S Faußer
Automatisierung und Personalisierung von Dienstleistungen: Methoden …, 2020
Large state spaces and large data: Utilizing neural network ensembles in reinforcement learning and kernel methods for clustering
SA Faußer
Universität Ulm, 2015
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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