| Neural network ensembles in reinforcement learning S Faußer, F Schwenker Neural Processing Letters 41, 55-69, 2015 | 53 | 2015 |
| Ensemble methods for reinforcement learning with function approximation S Faußer, F Schwenker Multiple Classifier Systems: 10th International Workshop, MCS 2011, Naples …, 2011 | 34 | 2011 |
| Selective neural network ensembles in reinforcement learning: taking the advantage of many agents S Faußer, F Schwenker Neurocomputing 169, 350-357, 2015 | 21 | 2015 |
| Predicting social perception from faces: A deep learning approach U Messer, S Fausser arXiv preprint arXiv:1907.00217, 2019 | 10 | 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 | 10 | 2012 |
| Semi-supervised clustering of large data sets with kernel methods S Faußer, F Schwenker Pattern recognition letters 37, 78-84, 2014 | 9 | 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 | 9 | 2010 |
| 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 Artificial Neural Networks in Pattern Recognition: Third IAPR Workshop …, 2008 | 8 | 2008 |
| Parallelized kernel patch clustering S Faußer, F Schwenker Artificial Neural Networks in Pattern Recognition: 4th IAPR TC3 Workshop …, 2010 | 6 | 2010 |
| Selective Neural Network Ensembles in Reinforcement Learning S Faußer, F Schwenker European Symposium on Artificial Neural Networks, Computational Intelligence …, 2014 | 3 | 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 | | 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 | | 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 | | 2021 |
| Machine Learning Infusion in Service Processes U Messer, S Faußer Automatisierung und Personalisierung von Dienstleistungen: Methoden …, 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 |
Friedhelm SchwenkerUlm University, Institute of Neural Information ProcessingEmail verificata su uni-ulm.de
