@inproceedings{SimmuteitSchleifVillmannetal., author = {Simmuteit, Stephan and Schleif, Frank-Michael and Villmann, Thomas and Elssner, Thomas}, title = {Tanimoto Metric in Tree-SOM for Improved Representation of Mass Spectrometry Data with an Underlying Taxonomic Structure}, series = {International Conference on Machine Learning and Applications, ICMLA 2009, Miami Beach, Florida, USA, December 13-15, 2009}, booktitle = {International Conference on Machine Learning and Applications, ICMLA 2009, Miami Beach, Florida, USA, December 13-15, 2009}, editor = {Arif Wani, M. and Kantardzic, Mehmed M. and Palade, Vasile and Kurgan, Lukasz A. and (Alan) Qi, Yuan}, doi = {10.1109/ICMLA.2009.111}, pages = {563 -- 567}, language = {en} } @inproceedings{SchleifVillmannHammer, author = {Schleif, Frank-Michael and Villmann, Thomas and Hammer, Barbara}, title = {Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data}, series = {Fuzzy Logic and Applications, 6th International Workshop, WILF 2005, Crema, Italy, September 15-17, 2005, Revised Selected Papers}, volume = {3849}, booktitle = {Fuzzy Logic and Applications, 6th International Workshop, WILF 2005, Crema, Italy, September 15-17, 2005, Revised Selected Papers}, editor = {Bloch, Isabelle and Petrosino, Alfredo and Tettamanzi, Andrea}, doi = {10.1007/11676935_36}, pages = {290 -- 296}, language = {en} } @inproceedings{GewenigerSchleifVillmann, author = {Geweniger, Tina and Schleif, Frank-Michael and Villmann, Thomas}, title = {Probabilistic Prototype Classification Using t-norms}, series = {Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014}, booktitle = {Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014}, editor = {Villmann, Thomas and Schleif, Frank-Michael and Kaden, Marika and Lange, Mandy}, doi = {10.1007/978-3-319-07695-9_9}, pages = {99 -- 108}, language = {en} } @inproceedings{SchleifElssnerKostrzewaetal., author = {Schleif, Frank-Michael and Elssner, Thomas and Kostrzewa, Markus and Villmann, Thomas and Hammer, Barbara}, title = {Analysis and Visualization of Proteomic Data by Fuzzy Labeled Self-Organizing Maps}, series = {19th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2006), 22-23 June 2006, Salt Lake City, Utah, USA}, booktitle = {19th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2006), 22-23 June 2006, Salt Lake City, Utah, USA}, doi = {10.1109/CBMS.2006.44}, pages = {919 -- 924}, language = {en} } @inproceedings{SchleifVillmannZhu, author = {Schleif, Frank-Michael and Villmann, Thomas and Zhu, Xibin}, title = {High Dimensional Matrix Relevance Learning}, series = {2014 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2014, Shenzhen, China, December 14, 2014}, booktitle = {2014 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2014, Shenzhen, China, December 14, 2014}, editor = {Zhou, Zhi-Hua and Wang, Wei and Kumar, Ravi and Toivonen, Hannu and Pei, Jian and Zhexue Huang, Joshua and Wu, Xindong}, doi = {10.1109/ICDMW.2014.15}, pages = {661 -- 667}, language = {en} } @inproceedings{SchleifTinoVillmann, author = {Schleif, Frank-Michael and Ti{\~n}o, Peter and Villmann, Thomas}, title = {Recent trends in learning of structured and non-standard data}, series = {22th European Symposium on Artificial Neural Networks, ESANN 2014, Bruges, Belgium, April 23-25, 2014}, booktitle = {22th European Symposium on Artificial Neural Networks, ESANN 2014, Bruges, Belgium, April 23-25, 2014}, language = {en} } @inproceedings{VillmannSchleifvanderWerffetal., author = {Villmann, Thomas and Schleif, Frank-Michael and van der Werff, Martijn and Deelder, Andr{\´e} M. and Tollenaar, Rob A. E. M.}, title = {Association Learning in SOMs for Fuzzy-Classification}, series = {The Sixth International Conference on Machine Learning and Applications, ICMLA 2007, Cincinnati, Ohio, USA, 13-15 December 2007}, booktitle = {The Sixth International Conference on Machine Learning and Applications, ICMLA 2007, Cincinnati, Ohio, USA, 13-15 December 2007}, editor = {Arif Wani, M. and Kantardzic, Mehmed M. and Li, Tao and Liu, Ying and Kurgan, Lukasz A. and Ye, Jieping and Ogihara, Mitsunori and Sagiroglu, Seref and Chen, Xue-wen and Peterson, Leif E. and Hafeez, Khalid}, doi = {10.1109/ICMLA.2007.29}, pages = {581 -- 586}, language = {en} } @inproceedings{SchleifVillmannHammer, author = {Schleif, Frank-Michael and Villmann, Thomas and Hammer, Barbara}, title = {Supervised Neural Gas for Classification of Functional Data and Its Application to the Analysis of Clinical Proteom Spectra}, series = {Computational and Ambient Intelligence, 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebasti{\´a}n, Spain, June 20-22, 2007, Proceedings}, booktitle = {Computational and Ambient Intelligence, 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebasti{\´a}n, Spain, June 20-22, 2007, Proceedings}, editor = {Sandoval Hern{\´a}ndez, Francisco and Prieto, Alberto and Cabestany, Joan and Gra{\~n}a, Manuel}, doi = {10.1007/978-3-540-73007-1_125}, pages = {1036 -- 1044}, language = {en} } @inproceedings{HasenfussHammerSchleifetal., author = {Hasenfuss, Alexander and Hammer, Barbara and Schleif, Frank-Michael and Villmann, Thomas}, title = {Neural Gas Clustering for Dissimilarity Data with Continuous Prototypes}, series = {Computational and Ambient Intelligence, 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebasti{\´a}n, Spain, June 20-22, 2007, Proceedings}, booktitle = {Computational and Ambient Intelligence, 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebasti{\´a}n, Spain, June 20-22, 2007, Proceedings}, editor = {Sandoval Hern{\´a}ndez, Francisco and Prieto, Alberto and Cabestany, Joan and Gra{\~n}a, Manuel}, doi = {10.1007/978-3-540-73007-1_66}, pages = {539 -- 546}, language = {en} } @inproceedings{VillmannSchleifMerenyietal., author = {Villmann, Thomas and Schleif, Frank-Michael and Mer{\´e}nyi, Erzs{\´e}bet and Hammer, Barbara}, title = {Fuzzy Labeled Self-Organizing Map for Classification of Spectra}, series = {Computational and Ambient Intelligence, 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebasti{\´a}n, Spain, June 20-22, 2007, Proceedings}, booktitle = {Computational and Ambient Intelligence, 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebasti{\´a}n, Spain, June 20-22, 2007, Proceedings}, editor = {Sandoval Hern{\´a}ndez, Francisco and Prieto, Alberto and Cabestany, Joan and Gra{\~n}a, Manuel}, doi = {10.1007/978-3-540-73007-1_68}, pages = {556 -- 563}, language = {en} } @inproceedings{SchleifClaussVillmannetal., author = {Schleif, Frank-Michael and Clauss, U. and Villmann, Thomas and Hammer, Barbara}, title = {Supervised relevance neural gas and unified maximum separability analysis for classification of mass spectrometric data}, series = {Proceedings of the 2004 International Conference on Machine Learning and Applications - ICMLA 2004, 16-18 December 2004, Louisville, KY, USA}, booktitle = {Proceedings of the 2004 International Conference on Machine Learning and Applications - ICMLA 2004, 16-18 December 2004, Louisville, KY, USA}, editor = {Kantardzic, Mehmed M. and Milanova, Mariofanna G. and Nasraoui, Olfa}, doi = {10.1109/ICMLA.2004.1383538}, pages = {374 -- 379}, language = {en} } @inproceedings{SchleifVillmannHammer, author = {Schleif, Frank-Michael and Villmann, Thomas and Hammer, Barbara}, title = {Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps}, series = {Applications of Fuzzy Sets Theory, 7th International Workshop on Fuzzy Logic and Applications, WILF 2007, Camogli, Italy, July 7-10, 2007, Proceedings}, booktitle = {Applications of Fuzzy Sets Theory, 7th International Workshop on Fuzzy Logic and Applications, WILF 2007, Camogli, Italy, July 7-10, 2007, Proceedings}, editor = {Masulli, Francesco and Mitra, Sushmita and Pasi, Gabriella}, doi = {10.1007/978-3-540-73400-0_72}, pages = {563 -- 570}, language = {en} } @inproceedings{HammerHasenfussSchleifetal., author = {Hammer, Barbara and Hasenfuss, Alexander and Schleif, Frank-Michael and Villmann, Thomas and Strickert, Marc and Seiffert, Udo}, title = {Intuitive Clustering of Biological Data}, series = {Proceedings of the International Joint Conference on Neural Networks, IJCNN 2007, Celebrating 20 years of neural networks, Orlando, Florida, USA, August 12-17, 2007}, booktitle = {Proceedings of the International Joint Conference on Neural Networks, IJCNN 2007, Celebrating 20 years of neural networks, Orlando, Florida, USA, August 12-17, 2007}, doi = {10.1109/IJCNN.2007.4371244}, pages = {1877 -- 1882}, language = {en} } @inproceedings{VillmannStrickertBruessetal., author = {Villmann, Thomas and Strickert, Marc and Br{\"u}ß, Cornelia and Schleif, Frank-Michael and Seiffert, Udo}, title = {Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS}, series = {15th European Symposium on Artificial Neural Networks, ESANN 2007, Bruges, Belgium, April 25-27, 2007, Proceedings}, booktitle = {15th European Symposium on Artificial Neural Networks, ESANN 2007, Bruges, Belgium, April 25-27, 2007, Proceedings}, pages = {103 -- 108}, language = {en} } @inproceedings{StrickertKeilwagenSchleifetal., author = {Strickert, Marc and Keilwagen, Jens and Schleif, Frank-Michael and Villmann, Thomas and Biehl, Michael}, title = {Matrix Metric Adaptation for Improved Linear Discriminant Analysis of Biomedical Data}, series = {Bio-Inspired Systems: Computational and Ambient Intelligence, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain, June 10-12, 2009. Proceedings, Part I}, booktitle = {Bio-Inspired Systems: Computational and Ambient Intelligence, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain, June 10-12, 2009. Proceedings, Part I}, editor = {Cabestany, Joan and Sandoval Hern{\´a}ndez, Francisco and Prieto, Alberto and Corchado, Juan M.}, doi = {10.1007/978-3-642-02478-8_117}, pages = {933 -- 940}, language = {en} } @inproceedings{SimmuteitSchleifVillmannetal., author = {Simmuteit, Stephan and Schleif, Frank-Michael and Villmann, Thomas and Kostrzewa, Markus}, title = {Hierarchical PCA Using Tree-SOM for the Identification of Bacteria}, series = {Advances in Self-Organizing Maps, 7th International Workshop, WSOM 2009, St. Augustine, FL, USA, June 8-10, 2009. Proceedings}, booktitle = {Advances in Self-Organizing Maps, 7th International Workshop, WSOM 2009, St. Augustine, FL, USA, June 8-10, 2009. Proceedings}, editor = {Carlos Pr{\i}́ncipe, Jos{\´e} and Miikkulainen, Risto}, doi = {10.1007/978-3-642-02397-2_31}, pages = {272 -- 280}, language = {en} } @inproceedings{VillmannSchleif, author = {Villmann, Thomas and Schleif, Frank-Michael}, title = {Functional vector quantization by neural maps}, series = {First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2009, Grenoble, France, August 26-28, 2009}, booktitle = {First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2009, Grenoble, France, August 26-28, 2009}, doi = {10.1109/WHISPERS.2009.5289064}, pages = {1 -- 4}, language = {en} } @inproceedings{SchleifVillmann, author = {Schleif, Frank-Michael and Villmann, Thomas}, title = {Neural Maps and Learning Vector Quantization - Theory and Applications}, series = {17th European Symposium on Artificial Neural Networks, ESANN 2009, Bruges, Belgium, April 22-24, 2009, Proceedings}, booktitle = {17th European Symposium on Artificial Neural Networks, ESANN 2009, Bruges, Belgium, April 22-24, 2009, Proceedings}, language = {en} } @inproceedings{KoepingMuehsamOfenbergetal., author = {K{\"o}ping, Lukas and M{\"u}hsam, Thomas and Ofenberg, Christian and Czech, Bernhard and Bernard, Michael and Schmer, Jens and Deinzer, Frank}, title = {Indoor Naviagtion Using Step and Turn Detection Together With Floor Map Information}, series = {Proceedings of the 1st International Workshop on Uncertainty in Ambient Intelligence}, booktitle = {Proceedings of the 1st International Workshop on Uncertainty in Ambient Intelligence}, language = {en} } @inproceedings{BogetGregorovaKalousis, author = {Boget, Yoann and Gregorov{\´a}, Magda and Kalousis, Alexandros}, title = {Permutation Equivariant Generative Adversarial Networks for Graphs}, series = {Neural Compression Workshop (CoRR)}, volume = {abs/2112.03621}, booktitle = {Neural Compression Workshop (CoRR)}, doi = {10.48550/arXiv.2112.03621}, abstract = {One of the most discussed issues in graph generative modeling is the ordering of the representation. One solution consists of using equivariant generative functions, which ensure the ordering invariance. After having discussed some properties of such functions, we propose 3G-GAN, a 3-stages model relying on GANs and equivariant functions. The model is still under development. However, we present some encouraging exploratory experiments and discuss the issues still to be addressed.}, language = {en} } @inproceedings{BogetGregorovaKalousis, author = {Boget, Yoann and Gregorov{\´a}, Magda and Kalousis, Alexandros}, title = {Graph annotation generative adversarial networks}, series = {Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India}, volume = {189}, booktitle = {Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India}, editor = {Balasubramanian, Vineeth N. and Tsang, Ivor W.}, doi = {10.48550/arXiv.2212.00449}, pages = {16 -- 16}, abstract = {We consider the problem of modelling high-dimensional distributions and generating new examples of data with complex relational feature structure coherent with a graph skeleton. The model we propose tackles the problem of generating the data features constrained by the specific graph structure of each data point by splitting the task into two phases. In the first it models the distribution of features associated with the nodes of the given graph, in the second it complements the edge features conditionally on the node features. We follow the strategy of implicit distribution modelling via generative adversarial network (GAN) combined with permutation equivariant message passing architecture operating over the sets of nodes and edges. This enables generating the feature vectors of all the graph objects in one go (in 2 phases) as opposed to a much slower one-by-one generations of sequential models, prevents the need for expensive graph matching procedures usually needed for likelihood-based generative models, and uses efficiently the network capacity by being insensitive to the particular node ordering in the graph representation. To the best of our knowledge, this is the first method that models the feature distribution along the graph skeleton allowing for generations of annotated graphs with user specified structures. Our experiments demonstrate the ability of our model to learn complex structured distributions through quantitative evaluation over three annotated graph datasets.}, language = {en} } @inproceedings{AdemolaReichGregorova, author = {Ademola, Esther and Reich, Martin and Gregorov{\´a}, Magda}, title = {An Investigative Study Exploring Machine Learning Approaches for Optimizing Deep Brain Stimulation Programming}, series = {Modelling and Development of Intelligent Systems - 9th International Conference, MDIS 2024, Sibiu, Romania, October 17-19, 2024, Revised Selected Papers}, volume = {2486}, booktitle = {Modelling and Development of Intelligent Systems - 9th International Conference, MDIS 2024, Sibiu, Romania, October 17-19, 2024, Revised Selected Papers}, editor = {Simian, Dana and Florentina Stoica, Laura}, doi = {10.1007/978-3-031-87386-7_6}, pages = {75 -- 89}, language = {en} }