TY - JOUR A1 - Schleif, Frank-Michael A1 - Riemer, T. A1 - Börner, U. A1 - Schnapka-Hille, L. A1 - Cross, Michael T1 - Genetic algorithm for shift-uncertainty correction in 1-D NMR-based metabolite identifications and quantifications JF - Bioinformatics Y1 - 2011 U6 - https://doi.org/10.1093/bioinformatics/btq661 VL - 27 IS - 4 SP - 524 EP - 533 ER - TY - JOUR A1 - Mwebaze, Ernest A1 - Schneider, Petra A1 - Schleif, Frank-Michael A1 - Aduwo, Jennifer R. A1 - Quinn, John A. A1 - Haase, Sven A1 - Villmann, Thomas A1 - Biehl, Michael T1 - Divergence-based classification in learning vector quantization JF - Neurocomputing Y1 - 2011 U6 - https://doi.org/10.1016/j.neucom.2010.10.016 VL - 74 IS - 9 SP - 1429 EP - 1435 ER - TY - CHAP A1 - Schneider, Petra A1 - Schleif, Frank-Michael A1 - Villmann, Thomas A1 - Biehl, Michael T1 - Generalized matrix learning vector quantizer for the analysis of spectral data T2 - 16th European Symposium on Artificial Neural Networks, ESANN 2008, Bruges, Belgium, April 23-25, 2008, Proceedings Y1 - 2008 SP - 451 EP - 456 ER - TY - CHAP A1 - Mwebaze, Ernest A1 - Schneider, Petra A1 - Schleif, Frank-Michael A1 - Haase, Sven A1 - Villmann, Thomas A1 - Biehl, Michael T1 - Divergence based Learning Vector Quantization T2 - 18th European Symposium on Artificial Neural Networks, ESANN 2010, Bruges, Belgium, April 28-30, 2010, Proceedings Y1 - 2010 ER - TY - CHAP A1 - Schneider, Petra A1 - Geweniger, Tina A1 - Schleif, Frank-Michael A1 - Biehl, Michael A1 - Villmann, Thomas T1 - Multivariate class labeling in Robust Soft LVQ T2 - 19th European Symposium on Artificial Neural Networks, ESANN 2011, Bruges, Belgium, April 27-29, 2011, Proceedings Y1 - 2011 ER - TY - JOUR A1 - Schleif, Frank-Michael A1 - Biehl, Michael A1 - Vellido, Alfredo T1 - Advances in machine learning and computational intelligence JF - Neurocomputing Y1 - 2009 U6 - https://doi.org/10.1016/j.neucom.2008.12.013 VL - 72 IS - 7-9 SP - 1377 EP - 1378 ER - TY - JOUR A1 - Biehl, Michael A1 - Ghio, Alessandro A1 - Schleif, Frank-Michael T1 - Developments in computational intelligence and machine learning JF - Neurocomputing Y1 - 2015 U6 - https://doi.org/10.1016/j.neucom.2015.03.062 VL - 169 SP - 185 EP - 186 ER - TY - JOUR A1 - Schleif, Frank-Michael A1 - Hammer, Barbara A1 - Gonzalez Monroy, Javier A1 - González Jiménez, Javier A1 - Blanco-Claraco, José-Luis A1 - Biehl, Michael A1 - Petkov, Nicolai T1 - Odor recognition in robotics applications by discriminative time-series modeling JF - Pattern Analysis and Applications Y1 - 2016 U6 - https://doi.org/10.1007/s10044-014-0442-2 VL - 19 IS - 1 SP - 207 EP - 220 ER - TY - CHAP A1 - Biehl, Michael A1 - Bunte, Kerstin A1 - Schleif, Frank-Michael A1 - Schneider, Petra A1 - Villmann, Thomas T1 - Large margin linear discriminative visualization by Matrix Relevance Learning T2 - The 2012 International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, June 10-15, 2012 Y1 - 2012 U6 - https://doi.org/10.1109/IJCNN.2012.6252627 SP - 1 EP - 8 ER - TY - JOUR A1 - Bunte, Kerstin A1 - Schneider, Petra A1 - Hammer, Barbara A1 - Schleif, Frank-Michael A1 - Villmann, Thomas A1 - Biehl, Michael T1 - Limited Rank Matrix Learning, discriminative dimension reduction and visualization JF - Neural Networks Y1 - 2012 U6 - https://doi.org/10.1016/j.neunet.2011.10.001 VL - 26 SP - 159 EP - 173 ER - TY - JOUR A1 - Münch, Maximilian A1 - Raab, Christoph A1 - Biehl, Michael A1 - Schleif, Frank-Michael T1 - Data-Driven Supervised Learning for Life Science Data JF - Frontiers in Applied Mathematics and Statistics Y1 - 2020 U6 - https://doi.org/10.3389/fams.2020.553000 VL - 6 SP - 553000 EP - 553000 ER - TY - CHAP A1 - Bunte, Kerstin A1 - Schleif, Frank-Michael A1 - Biehl, Michael T1 - Adaptive learning for complex-valued data T2 - 20th European Symposium on Artificial Neural Networks, ESANN 2012, Bruges, Belgium, April 25-27, 2012 Y1 - 2012 ER - TY - CHAP A1 - Biehl, Michael A1 - Hammer, Barbara A1 - Schleif, Frank-Michael A1 - Schneider, Petra A1 - Villmann, Thomas T1 - Stationarity of Matrix Relevance LVQ T2 - 2015 International Joint Conference on Neural Networks, IJCNN 2015, Killarney, Ireland, July 12-17, 2015 Y1 - 2015 U6 - https://doi.org/10.1109/IJCNN.2015.7280441 SP - 1 EP - 8 ER - TY - JOUR A1 - Münch, Maximilian A1 - Straat, Michiel A1 - Biehl, Michael A1 - Schleif, Frank-Michael T1 - Complex-valued embeddings of generic proximity data JF - CoRR Y1 - 2020 VL - abs/2008.13454 ER - TY - CHAP A1 - Köping, Lukas A1 - Grzegorzek, Marcin A1 - Deinzer, Frank A1 - Bobek, Szymon A1 - Slazynski, Mateusz A1 - Nalepa, Grzegorz T1 - Improving indoor localization by user feedback T2 - 18th International Conference on Information Fusion (Fusion) Y1 - 2015 UR - https://ieeexplore.ieee.org/iel7/7229502/7266535/07266675.pdf SP - 1053 EP - 1060 ER - TY - CHAP A1 - Ebner, Frank A1 - Fetzer, Toni A1 - Köping, Lukas A1 - Grzegorzek, Marcin A1 - Deinzer, Frank T1 - Multi Sensor 3D Indoor Localisation T2 - International Conference on Indoor Positioning and Indoor Navigation (IPIN 2015) Y1 - 2015 UR - https://ieeexplore.ieee.org/iel7/7336693/7346746/07346772.pdf SP - 1 EP - 11 ER - TY - JOUR A1 - Schleif, Frank-Michael A1 - Zhu, Xibin A1 - Hammer, Barbara T1 - Sparse conformal prediction for dissimilarity data JF - Annals of Mathematics and Artificial Intelligence Y1 - 2015 U6 - https://doi.org/10.1007/s10472-014-9402-1 VL - 74 IS - 1-2 SP - 95 EP - 116 ER - TY - JOUR A1 - Gisbrecht, Andrej A1 - Schleif, Frank-Michael T1 - Metric and non-metric proximity transformations at linear costs JF - Neurocomputing Y1 - 2015 U6 - https://doi.org/10.1016/j.neucom.2015.04.017 VL - 167 SP - 643 EP - 657 ER - TY - JOUR A1 - Schleif, Frank-Michael T1 - Generic probabilistic prototype based classification of vectorial and proximity data JF - Neurocomputing Y1 - 2015 U6 - https://doi.org/10.1016/j.neucom.2014.12.002 VL - 154 SP - 208 EP - 216 ER - TY - CHAP A1 - Hoffmann, Christian A1 - Brand, Christoph A1 - Heinzl, Steffen T1 - Towards an Architecture for End-to-End-Encrypted File Synchronization Systems T2 - Proceedings of the 24th IEEE Int'l Conf. on Enabling Technologies: Infrastructures for Collaborative Enterprises (WETICE) Y1 - 2015 SP - 170 EP - 175 PB - IEEE Press ER - TY - CHAP A1 - Klehr, Lukas A1 - Engelmann, Bastian A1 - Schleif, Frank-Michael A1 - Regulin, Daniel ED - Iliadis, Lazaros S. ED - Maglogiannis, Ilias ED - Kyriacou, Efthyvoulos ED - Jayne, Chrisina T1 - Contextualized Segmentation of Milling Processes Using Discrete Rule-Based Pattern Recognition T2 - Engineering Applications of Neural Networks - 26th International Conference, EANN 2025, Limassol, Cyprus, June 26-29, 2025, Proceedings, Part II Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-96199-1\_18 VL - 2582 SP - 238 EP - 254 ER - TY - CHAP A1 - Münch, Maximilian A1 - Röder, Manuel A1 - Schleif, Frank-Michael ED - Frommholz, Ingo ED - Hopfgartner, Frank ED - Lee, Mark ED - Oakes, Michael ED - Lalmas, Mounia ED - Zhang, Min ED - Santos, Rodrygo L. T. T1 - Unlocking the Potential of Non-PSD Kernel Matrices: A Polar Decomposition-based Transformation for Improved Prediction Models T2 - Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023 Y1 - 2023 U6 - https://doi.org/10.1145/3583780.3615102 SP - 1867 EP - 1876 ER - TY - CHAP A1 - Polato, Mirko A1 - Hammer, Barbara A1 - Schleif, Frank-Michael T1 - Machine learning in distributed, federated and non-stationary environments - recent trends T2 - 32nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2024, Bruges, Belgium, October 9-11, 2024 Y1 - 2024 U6 - https://doi.org/10.14428/ESANN/2024.ES2024-3 ER - TY - JOUR A1 - Oneto, Luca A1 - Bunte, Kerstin A1 - Schleif, Frank-Michael T1 - Advances in artificial neural networks, machine learning and computational intelligence: Selected papers from the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018) JF - Neurocomputing Y1 - 2019 U6 - https://doi.org/10.1016/J.NEUCOM.2019.01.081 VL - 342 SP - 1 EP - 5 ER - TY - CHAP A1 - Ewecker, Lukas A1 - Winkler, Timo A1 - Väth, Philipp A1 - Schwager, Robin A1 - Brühl, Tim A1 - Schleif, Frank-Michael T1 - How Important is the Temporal Context to Anticipate Oncoming Vehicles at Night? T2 - IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023, Honolulu, Oahu, HI, USA, October 1-4, 2023 Y1 - 2023 U6 - https://doi.org/10.1109/SMC53992.2023.10394461 SP - 1000 EP - 1007 ER - TY - CHAP A1 - Röder, Manuel A1 - Schleif, Frank-Michael T1 - Sparse Uncertainty-Informed Sampling from Federated Streaming Data T2 - 32nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2024, Bruges, Belgium, October 9-11, 2024 Y1 - 2024 U6 - https://doi.org/10.14428/ESANN/2024.ES2024-9 ER - TY - JOUR A1 - Münch, Maximilian A1 - Röder, Manuel A1 - Heilig, Simon A1 - Raab, Christoph A1 - Schleif, Frank-Michael T1 - Static and adaptive subspace information fusion for indefinite heterogeneous proximity data JF - Neurocomputing Y1 - 2023 U6 - https://doi.org/10.1016/J.NEUCOM.2023.126635 VL - 555 SP - 126635 EP - 126635 ER - TY - JOUR A1 - Raab, Christoph A1 - Heusinger, Moritz A1 - Schleif, Frank-Michael T1 - Reactive Soft Prototype Computing for Concept Drift Streams JF - CoRR Y1 - 2020 VL - abs/2007.05432 ER - TY - JOUR A1 - Raab, Christoph A1 - Schleif, Frank-Michael T1 - Transfer learning extensions for the probabilistic classification vector machine JF - CoRR Y1 - 2020 VL - abs/2007.07090 ER - TY - CHAP A1 - Xu, Bangguo A1 - Yan, Simei A1 - Liu, Liang A1 - Schleif, Frank-Michael ED - Villmann, Thomas ED - Kaden, Marika ED - Geweniger, Tina ED - Schleif, Frank-Michael T1 - Optimizing YOLOv5 for Green AI: A Study on Model Pruning and Lightweight Networks T2 - Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond - Proceedings of the 15th International Workshop, WSOM+ 2024, Mittweida, Germany, July 10-12, 2024 Y1 - 2024 U6 - https://doi.org/10.1007/978-3-031-67159-3\_22 VL - 1087 SP - 196 EP - 205 ER - TY - CHAP A1 - Schleif, Frank-Michael ED - Villmann, Thomas ED - Kaden, Marika ED - Geweniger, Tina ED - Schleif, Frank-Michael T1 - Practical Approaches to Approximate Dominant Eigenvalues in Large Matrices T2 - Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond - Proceedings of the 15th International Workshop, WSOM+ 2024, Mittweida, Germany, July 10-12, 2024 Y1 - 2024 U6 - https://doi.org/10.1007/978-3-031-67159-3\_14 VL - 1087 SP - 118 EP - 128 ER - TY - CHAP A1 - Röder, Manuel A1 - Schleif, Frank-Michael ED - Bunse, Mirko ED - Herde, Marek ED - Krempl, Georg ED - Lemaire, Vincent ED - Tharwat, Alaa ED - Tuan Pham, Minh ED - Saadallah, Amal T1 - Deep Transfer Hashing for Adaptive Learning on Federated Streaming Data T2 - Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), Vilnius, Lithuania, September 9th, 2024 Y1 - 2024 VL - 3770 SP - 7 EP - 11 ER - TY - CHAP A1 - Röder, Manuel A1 - Münch, Maximilian A1 - Raab, Christoph A1 - Schleif, Frank-Michael ED - Castrillón Santana, Modesto ED - De Marsico, Maria ED - Fred, Ana T1 - Crossing Domain Borders with Federated Few-Shot Adaptation T2 - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2024, Rome, Italy, February 24-26, 2024 Y1 - 2024 U6 - https://doi.org/10.5220/0012351900003654 SP - 511 EP - 521 ER - TY - JOUR A1 - Röder, Manuel A1 - Schleif, Frank-Michael T1 - Sparse Uncertainty-Informed Sampling from Federated Streaming Data JF - CoRR Y1 - 2024 U6 - https://doi.org/10.48550/ARXIV.2408.17108 VL - abs/2408.17108 ER - TY - JOUR A1 - Röder, Manuel A1 - Schleif, Frank-Michael T1 - Deep Transfer Hashing for Adaptive Learning on Federated Streaming Data JF - CoRR Y1 - 2024 U6 - https://doi.org/10.48550/ARXIV.2409.12575 VL - abs/2409.12575 ER - TY - JOUR A1 - Röder, Manuel A1 - Heller, Leon A1 - Münch, Maximilian A1 - Schleif, Frank-Michael T1 - Efficient Cross-Domain Federated Learning by MixStyle Approximation JF - CoRR Y1 - 2023 U6 - https://doi.org/10.48550/ARXIV.2312.07064 VL - abs/2312.07064 ER - TY - CHAP A1 - Ebner, F. A1 - Fetzer, T. A1 - Deinzer, Frank A1 - Grzegorzek, M. T1 - On Prior Navigation Knowledge in Multi Sensor Indoor Localisation T2 - International Conference on Information Fusion (FUSION 2016) Y1 - 2016 UR - https://www.researchgate.net/profile/Toni-Fetzer/publication/306118756_On_Prior_Navigation_Knowledge_in_Multi_Sensor_Indoor_Localisation/links/57da7d8508aeea195932334f/On-Prior-Navigation-Knowledge-in-Multi-Sensor-Indoor-Localisation.pdf ER - TY - CHAP A1 - Fetzer, T. A1 - Ebner, F. A1 - Köping, L. A1 - Grzegorzek, M. A1 - Deinzer, Frank T1 - On Monte Carlo Smoothing in Multi Sensor Indoor Localisation T2 - International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016) Y1 - 2016 UR - https://ieeexplore.ieee.org/iel7/7738315/7743575/07743670.pdf ER - TY - JOUR A1 - Ebner, Markus A1 - Fetzer, Toni A1 - Bullmann, Markus A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - Recognition of Typical Locomotion Activities Based on the Sensor Data of a Smartphone in Pocket or Hand JF - Sensors Y1 - 2020 U6 - https://doi.org/10.3390/s20226559 SN - 1424-8220 VL - 20 IS - 22 ER - TY - CHAP A1 - Fetzer, Toni A1 - Deinzer, Frank A1 - Koping, Lukas A1 - Grzegorzek, Marcin T1 - Statistical indoor localization using fusion of depth-images and step detection T2 - International Conference on Indoor Positioning and Indoor Navigation (IPIN 2014) Y1 - 2014 U6 - https://doi.org/10.1109/IPIN.2014.7275509 SP - 407 EP - 415 ER - TY - JOUR A1 - Deinzer, Frank A1 - Fetzer, Toni T1 - Die Mischung macht’s: Mit KI und Augmented Reality die Welt immersiv erkunden JF - Transfer – Das Steinbeis-Magazin Y1 - 2021 VL - 2021 IS - 3 SP - 39 EP - 41 ER - TY - CHAP A1 - Bunte, Kerstin A1 - Kaden, Marika A1 - Schleif, Frank-Michael ED - Merényi, Erzsébet ED - Mendenhall, Michael J. ED - O’Driscoll, Patrick T1 - Low-Rank Kernel Space Representations in Prototype Learning T2 - Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016 Y1 - 2016 U6 - https://doi.org/10.1007/978-3-319-28518-4_30 SP - 341 EP - 353 ER - TY - JOUR A1 - Prappacher, Nico A1 - Bullmann, Markus A1 - Bohn, Gunther A1 - Deinzer, Frank A1 - Linke, Andreas T1 - Defect Detection on Rolling Element Surface Scans Using Neural Image Segmentation JF - Applied Sciences Y1 - 2020 U6 - https://doi.org/10.3390/app10093290 SN - 2076-3417 VL - 10 IS - 9 ER - TY - JOUR A1 - Deinzer, Frank A1 - Derichs, Christian A1 - Denzler, Joachim A1 - Niemann, Heinrich T1 - A Framework for Actively Selecting Viewpoints in Object Recognition JF - International Journal of Pattern Recognition and Artificial Intelligence Y1 - 2009 U6 - https://doi.org/10.1142/S0218001409007351 VL - 23 IS - 4 SP - 765 EP - 799 ER - TY - JOUR A1 - Embrechts, Mark J. A1 - Rossi, Fabrice A1 - Schleif, Frank-Michael A1 - Aldo Lee, John T1 - Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2013) JF - Neurocomputing Y1 - 2014 U6 - https://doi.org/10.1016/j.neucom.2014.03.002 VL - 141 SP - 1 EP - 2 ER - TY - JOUR A1 - Hofmann, Daniela A1 - Schleif, Frank-Michael A1 - Paaßen, Benjamin A1 - Hammer, Barbara T1 - Learning interpretable kernelized prototype-based models JF - Neurocomputing Y1 - 2014 U6 - https://doi.org/10.1016/j.neucom.2014.03.003 VL - 141 SP - 84 EP - 96 ER - TY - JOUR A1 - Saueressig, Gabriele A1 - Bauer, C. A1 - Löbmann, Rebecca A1 - Wunderlich, C. A1 - Wilke, W. A1 - Bräutigam, Volker A1 - Arnholdt, J. T1 - Zweite Förderphase BEST-FIT: Maßnahmen zur Verbesserung von Bestehensquoten und Praxisfitness der Absolvierenden JF - Didaktik-Nachrichten Y1 - 2020 VL - 12 SP - 18 EP - 26 ER - TY - BOOK A1 - Heinzl, Steffen T1 - Java Übungen 2: Mehr als 50 erprobte Übungen für das zweite Semester Programmieren in Java N2 - In diesem Buch finden Sie mehr als 50 erprobte Übungsaufgaben, die Ihnen dabei helfen, die objektorientierte Programmierung in Java zu erlernen. Das Buch richtet sich an Studierende des zweiten Semesters, die Programmieren in Java lernen. Dabei zielen die Übungen auf die objektorientierte Programmierung ab. Die letzten Lektionen des Buchs stellen einige Übungsaufgaben zur Verfügung, um einen Einstieg in die funktionale Programmierung in Java zu erhalten. Das Buch verzichtet bewusst auf Musterlösungen. Y1 - 2020 PB - KDP ET - 1. Auflage ER - TY - CHAP A1 - Münch, Maximilian A1 - Sophie Bohnsack, Katrin A1 - Engelsberger, Alexander A1 - Schleif, Frank-Michael A1 - Villmann, Thomas T1 - Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection T2 - 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2023, Bruges, Belgium, October 4-6, 2023 Y1 - 2023 U6 - https://doi.org/10.14428/ESANN/2023.ES2023-136 ER - TY - CHAP A1 - Heinzl, Steffen A1 - Schreibmann, Vitaliy T1 - Function References as First Class Citizens in UML Class Modeling T2 - Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE) N2 - There have been a number of philosophical discussions whether functional programming or object-oriented programming is the better programming concept. In reality, programmers utilize both concepts and functional programming concepts improve object-oriented languages. Likewise the modeling of OO languages should also reflect these concepts in the modeling process. This paper improves the modeling of behavior (usually expressed through functional programming) in UML class diagrams. In UML class diagrams, behavior modeling is only achieved by modeling a new class containing the desired function. If several alternatives for a certain behavior have to be expressed, the modeling complexity increases because we need to introduce an interface and for each alternative an additional class. Therefore, we propose a new function element that circumvents these problems and reduces the complexity of the model. Due to the proposed <> stereotype, functions in the model can be identified at first glance. The new model is motivated by the strategy pattern and evaluated against a more complex design pattern. A possible first implementation is presented. Y1 - 2018 SP - 335 EP - 342 PB - Scitepress ER - TY - CHAP A1 - Heinzl, Steffen A1 - Metz, Christoph T1 - Toward a Cloud-ready Dynamic Load Balancer based on the Apache Web Server T2 - Proceedings of the 22nd IEEE Int'l Conf. on Enabling Technologies: Infrastructures for Collaborative Enterprises (WETICE) N2 - Perhaps, the most interesting part of Cloud Computing is rapid elasticity. To be able to exploit the elasticity of a cloud infrastructure, the applications usually need to be able to scale horizontally, i.e. it must be possible to add (and also remove) nodes offering the same capabilities as the existing ones. In such scenarios, a load balancer is usually used. To keep the manual labor down, the load balancer should automatically be able to distribute load to the newly added nodes. In this paper, we show how to transform the popular Apache Web Server (which is only able to act as a static load balancer) into a dynamic cloud-ready load balancer. Y1 - 2013 SP - 342 EP - 345 PB - IEEE Press ER -