| Neural network ensembles in reinforcement learning S Faußer, F Schwenker Neural Processing Letters 41, 55-69, 2015 | 67 | 2015 |
| Ensemble methods for reinforcement learning with function approximation S Faußer, F Schwenker International Workshop on Multiple Classifier Systems, 56-65, 2011 | 37 | 2011 |
| Selective neural network ensembles in reinforcement learning: taking the advantage of many agents S Faußer, F Schwenker Neurocomputing 169, 350-357, 2015 | 29 | 2015 |
| Predicting social perception from faces: A deep learning approach U Messer, S Fausser arXiv preprint arXiv:1907.00217, 2019 | 16 | 2019 |
| Semi-supervised clustering of large data sets with kernel methods S Faußer, F Schwenker Pattern recognition letters 37, 78-84, 2014 | 11 | 2014 |
| Semi-supervised kernel clustering with sample-to-cluster weights S Faußer, F Schwenker IAPR International Workshop on Partially Supervised Learning, 72-81, 2011 | 10 | 2011 |
| 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 | 10 | 2010 |
| 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 | 10 | 2008 |
| Clustering large datasets with kernel methods S Fausser, F Schwenker Pattern Recognition (ICPR), 2012 21st International Conference on, 501-504, 2012 | 8* | 2012 |
| Parallelized kernel patch clustering S Faußer, F Schwenker IAPR Workshop on Artificial Neural Networks in Pattern Recognition, 131-140, 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 | 2 | 2022 |
| How are We Doing Today? Using Natural Speech Analysis to Assess Older Adults’ Subjective Well-Being N Finze, D Jechle, S Faußer, H Gewald Business & Information Systems Engineering 66 (3), 321-334, 2024 | 1 | 2024 |
| Using NLP to analyze whether customer statements comply with their inner belief F Thaler, S Faußer, H Gewald arXiv preprint arXiv:2107.11175, 2021 | 1 | 2021 |
| Assessing Delivery Commitments in Supply Chains: A Matrix-Based Framework M Vangeepuram, S Faußer, H Ehm, M Ratusny, S Heilmayer, TL Welling 2023 Winter Simulation Conference (WSC), 2182-2193, 2023 | | 2023 |
| A FRAMEWORK FOR THE DESIGN, IMPLEMENTATION AND EVALUATION OF AI BASED REAL-LIFE LEARNING SCENARIOS FOR COMPUTER SCIENCE NON-MAJORS D Meyer, S Fausser ICERI2022 Proceedings, 7499-7505, 2022 | | 2022 |
| 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 ProcessingZweryfikowany adres z uni-ulm.de
