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ORCIDWolfgang Konen
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2020 – today
- 2024
[c30]Raphael C. Engelhardt
, Moritz Lange, Laurenz Wiskott, Wolfgang Konen:
Exploring the Reliability of SHAP Values in Reinforcement Learning. xAI (3) 2024: 165-184- [i11]Moritz Lange, Raphael C. Engelhardt, Wolfgang Konen, Laurenz Wiskott:
Interpretable Brain-Inspired Representations Improve RL Performance on Visual Navigation Tasks. CoRR abs/2402.12067 (2024) - [i10]Marc Oedingen, Raphael C. Engelhardt, Robin Denz, Maximilian Hammer, Wolfgang Konen:
ChatGPT Code Detection: Techniques for Uncovering the Source of Code. CoRR abs/2405.15512 (2024) - 2023
- [j14]Raphael C. Engelhardt, Marc Oedingen, Moritz Lange, Laurenz Wiskott, Wolfgang Konen:
Iterative Oblique Decision Trees Deliver Explainable RL Models. Algorithms 16(6): 282 (2023) - [j13]Johannes Scheiermann, Wolfgang Konen:
AlphaZero-Inspired Game Learning: Faster Training by Using MCTS Only at Test Time. IEEE Trans. Games 15(4): 637-647 (2023) - [c29]Raphael C. Engelhardt, Ralitsa Raycheva, Moritz Lange, Laurenz Wiskott, Wolfgang Konen:
Ökolopoly: Case Study on Large Action Spaces in Reinforcement Learning. LOD (2) 2023: 109-123 - [c28]Moritz Lange, Noah Krystiniak, Raphael C. Engelhardt, Wolfgang Konen, Laurenz Wiskott:
Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-visual Environments: A Comparison. LOD (2) 2023: 177-191 - [i9]Wolfgang Konen:
Towards Learning Rubik's Cube with N-tuple-based Reinforcement Learning. CoRR abs/2301.12167 (2023) - [i8]Moritz Lange, Noah Krystiniak, Raphael C. Engelhardt, Wolfgang Konen, Laurenz Wiskott:
Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-Visual Environments: A Comparison. CoRR abs/2310.04241 (2023) - 2022
- [c27]Raphael C. Engelhardt, Moritz Lange, Laurenz Wiskott, Wolfgang Konen:
Sample-Based Rule Extraction for Explainable Reinforcement Learning. LOD (1) 2022: 330-345 - [i7]Johannes Scheiermann, Wolfgang Konen:
AlphaZero-Inspired General Board Game Learning and Playing. CoRR abs/2204.13307 (2022) - 2021
- [j12]Markus Thill, Wolfgang Konen, Hao Wang, Thomas Bäck:
Temporal convolutional autoencoder for unsupervised anomaly detection in time series. Appl. Soft Comput. 112: 107751 (2021) - [j11]Samineh Bagheri, Ulf Reinicke, Denis Anders, Wolfgang Konen:
Surrogate-assisted optimization for augmentation of finite element techniques. J. Comput. Sci. 54: 101427 (2021) - [i6]Wolfgang Konen, Samineh Bagheri:
Final Adaptation Reinforcement Learning for N-Player Games. CoRR abs/2111.14375 (2021) - 2020
- [c26]Wolfgang Konen, Samineh Bagheri:
Reinforcement Learning for N-player Games: The Importance of Final Adaptation. BIOMA 2020: 84-96 - [c25]Markus Thill, Wolfgang Konen, Thomas Bäck:
Time Series Encodings with Temporal Convolutional Networks. BIOMA 2020: 161-173 - [d2]Markus Thill, Wolfgang Konen, Thomas Bäck:
MarkusThill/MGAB: The Mackey-Glass Anomaly Benchmark. Version v1.0.0. Zenodo, 2020 [all versions]
- [d1]Markus Thill, Wolfgang Konen, Thomas Bäck:
MarkusThill/MGAB: The Mackey-Glass Anomaly Benchmark. Version v1.0.1. Zenodo, 2020 [all versions]
2010 – 2019
- 2019
- [c24]Wolfgang Konen:
General Board Game Playing for Education and Research in Generic AI Game Learning. CoG 2019: 1-8 - [c23]Samineh Bagheri, Wolfgang Konen, Thomas Bäck:
Solving optimization problems with high conditioning by means of online whitening. GECCO (Companion) 2019: 243-244 - [c22]Markus Thill, Sina Däubener, Wolfgang Konen, Thomas Bäck:
Anomaly Detection in Electrocardiogram Readings with Stacked LSTM Networks. ITAT 2019: 17-25 - [i5]Samineh Bagheri, Wolfgang Konen, Thomas Bäck:
SACOBRA with Online Whitening for Solving Optimization Problems with High Conditioning. CoRR abs/1904.08397 (2019) - [i4]Wolfgang Konen:
General Board Game Playing for Education and Research in Generic AI Game Learning. CoRR abs/1907.06508 (2019) - 2017
- [j10]Samineh Bagheri, Wolfgang Konen, Michael Emmerich, Thomas Bäck:
Self-adjusting parameter control for surrogate-assisted constrained optimization under limited budgets. Appl. Soft Comput. 61: 377-393 (2017) - [c21]Markus Thill, Wolfgang Konen, Thomas Bäck:
Online anomaly detection on the webscope S5 dataset: A comparative study. EAIS 2017: 1-8 - [c20]Samineh Bagheri, Wolfgang Konen, Richard Allmendinger, Jürgen Branke, Kalyanmoy Deb, Jonathan E. Fieldsend, Domenico Quagliarella, Karthik Sindhya:
Constraint handling in efficient global optimization. GECCO 2017: 673-680 - 2016
- [j9]Samineh Bagheri, Markus Thill, Patrick Koch, Wolfgang Konen:
Online Adaptable Learning Rates for the Game Connect-4. IEEE Trans. Comput. Intell. AI Games 8(1): 33-42 (2016) - [c19]Samineh Bagheri, Wolfgang Konen, Thomas Bäck:
Equality constraint handling for surrogate-assisted constrained optimization. CEC 2016: 1924-1931 - [c18]Samineh Bagheri, Wolfgang Konen, Thomas Bäck:
Online selection of surrogate models for constrained black-box optimization. SSCI 2016: 1-8 - [i3]Wolfgang Konen:
Illumination-invariant image mosaic calculation based on logarithmic search. CoRR abs/1603.06433 (2016) - 2015
- [j8]Patrick Koch, Tobias Wagner, Michael T. M. Emmerich, Thomas Bäck, Wolfgang Konen:
Efficient multi-criteria optimization on noisy machine learning problems. Appl. Soft Comput. 29: 357-370 (2015) - [c17]Patrick Koch, Samineh Bagheri, Wolfgang Konen, Christophe Foussette, Peter Krause, Thomas Bäck:
A New Repair Method For Constrained Optimization. GECCO 2015: 273-280 - [i2]Samineh Bagheri, Wolfgang Konen, Michael Emmerich, Thomas Bäck:
Solving the G-problems in less than 500 iterations: Improved efficient constrained optimization by surrogate modeling and adaptive parameter control. CoRR abs/1512.09251 (2015) - 2014
- [c16]Markus Thill, Samineh Bagheri, Patrick Koch, Wolfgang Konen:
Temporal difference learning with eligibility traces for the game connect four. CIG 2014: 1-8 - [c15]Wolfgang Konen, Patrick Koch:
Adaptation in Nonlinear Learning Models for Nonstationary Tasks. PPSN 2014: 292-301 - 2013
- [c14]Jörg Stork, Ricardo Ramos, Patrick Koch, Wolfgang Konen:
SVM Ensembles Are Better When Different Kernel Types Are Combined. ECDA 2013: 191-201 - 2012
- [j7]Patrick Koch, Bernd Bischl, Oliver Flasch, Thomas Bartz-Beielstein, Claus Weihs, Wolfgang Konen:
Tuning and evolution of support vector kernels. Evol. Intell. 5(3): 153-170 (2012) - [c13]Markus Thill, Patrick Koch, Wolfgang Konen:
Reinforcement Learning with N-tuples on the Game Connect-4. PPSN (1) 2012: 184-194 - [c12]Patrick Koch, Wolfgang Konen:
Efficient Sampling and Handling of Variance in Tuning Data Mining Models. PPSN (1) 2012: 195-205 - 2011
- [c11]Thomas Bartz-Beielstein, Martina Friese, Martin Zaefferer, Boris Naujoks, Oliver Flasch, Wolfgang Konen, Patrick Koch:
Noisy optimization with sequential parameter optimization and optimal computational budget allocation. GECCO (Companion) 2011: 119-120 - [c10]Wolfgang Konen, Patrick Koch, Oliver Flasch, Thomas Bartz-Beielstein, Martina Friese, Boris Naujoks:
Tuned data mining: a benchmark study on different tuners. GECCO 2011: 1995-2002 - [i1]Wolfgang Konen:
Self-configuration from a Machine-Learning Perspective. CoRR abs/1105.1951 (2011) - 2010
- [c9]Oliver Flasch, Thomas Bartz-Beielstein, Artur Davtyan, Patrick Koch, Wolfgang Konen, Tosin Daniel Oyetoyan, Michael Tamutan:
Comparing SPO-tuned GP and NARX prediction models for stormwater tank fill level prediction. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c8]Jörg Ziegenhirt, Thomas Bartz-Beielstein, Oliver Flasch, Wolfgang Konen, Martin Zaefferer:
Optimization of biogas production with computational intelligence a comparative study. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c7]Patrick Koch, Wolfgang Konen, Kristine Hein:
Gesture recognition on few training data using Slow Feature Analysis and parametric bootstrap. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [j6]Wolfgang Konen, Tobias Zimmer, Thomas Bartz-Beielstein:
Optimierte Modellierung von Füllständen in Regenüberlaufbecken mittels CI-basierter Parameterselektion (Optimized Modelling of Fill Levels in Stormwater Tanks Using CI-based Parameter Selection Schemes). Autom. 57(3): 155-166 (2009) - [c6]Wolfgang Konen, Thomas Bartz-Beielstein:
Reinforcement learning for games: failures and successes. GECCO (Companion) 2009: 2641-2648 - 2008
- [c5]Wolfgang Konen, Thomas Bartz-Beielstein:
Reinforcement Learning: Insights from Interesting Failures in Parameter Selection. PPSN 2008: 478-487 - 2007
- [j5]Wolfgang Konen, S. Tombrock, Martin Scholz:
Robust registration procedures for endoscopic imaging. Medical Image Anal. 11(6): 526-539 (2007) - [c4]Wolfgang Konen, Beate Breiderhoff, Martin Scholz:
Real-Time Image Mosaic for Endoscopic Video Sequences. Bildverarbeitung für die Medizin 2007: 298-302
1990 – 1999
- 1999
- [j4]Rolf P. Würtz, Wolfgang Konen, Kay-Ole Behrmann:
On the performance of neuronal matching algorithms. Neural Networks 12(1): 127-134 (1999) - 1996
- [c3]Rolf P. Würtz, Wolfgang Konen, Kay-Ole Behrmann:
How Fast can Neuronal Algorithms Match Patterns. ICANN 1996: 145-150 - [c2]Wolfgang Konen:
Comparing Facial Line Drawings with Gray-Level Images: A Case Study on PHANTOMAS. ICANN 1996: 727-734 - 1995
- [c1]Jörg Kopecz, Wolfgang Konen, Rolf Ekkehard Schulze-Krüger:
ZN-Face: A system for access control using automated face recognition. SNN Symposium on Neural Networks 1995: 356-365 - 1994
- [j3]Wolfgang Konen, Thomas Maurer, Christoph von der Malsburg:
A fast dynamic link matching algorithm for invariant pattern recognition. Neural Networks 7(6-7): 1019-1030 (1994) - 1993
- [j2]Wolfgang Konen, Christoph von der Malsburg:
Learning to Generalize from Single Examples in the Dynamic Link Architecture. Neural Comput. 5(5): 719-735 (1993) - [j1]Martin Lades, Jan C. Vorbrüggen, Joachim M. Buhmann, Jörg Lange, Christoph von der Malsburg, Rolf P. Würtz, Wolfgang Konen:
Distortion Invariant Object Recognition in the Dynamic Link Architecture. IEEE Trans. Computers 42(3): 300-311 (1993)
Coauthor Index
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