@article{RaabSchleif, author = {Raab, Christoph and Schleif, Frank-Michael}, title = {Transfer learning extensions for the probabilistic classification vector machine}, series = {Neurocomputing}, volume = {397}, journal = {Neurocomputing}, doi = {10.1016/j.neucom.2019.09.104}, pages = {320 -- 330}, language = {en} } @article{MicheliSchleifTino, author = {Micheli, Alessio and Schleif, Frank-Michael and Ti{\~n}o, Peter}, title = {Novel approaches in machine learning and computational intelligence}, series = {Neurocomputing}, volume = {112}, journal = {Neurocomputing}, doi = {10.1016/j.neucom.2013.01.005}, pages = {1 -- 3}, language = {en} } @inproceedings{Schleif, author = {Schleif, Frank-Michael}, title = {Proximity learning for non-standard big 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{RaabVaethMeieretal., author = {Raab, Christoph and V{\"a}th, Philipp and Meier, Peter and Schleif, Frank-Michael}, title = {Bridging Adversarial and Statistical Domain Transfer via Spectral Adaptation Networks}, series = {Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, Revised Selected Papers, Part III}, booktitle = {Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, Revised Selected Papers, Part III}, editor = {Ishikawa, Hiroshi and Liu, Cheng-Lin and Pajdla, Tom{\´a}s and Shi, Jianbo}, doi = {10.1007/978-3-030-69535-4_28}, pages = {457 -- 473}, language = {en} } @inproceedings{Schleif, author = {Schleif, Frank-Michael}, title = {Advances in pre-processing and model generation for mass spectrometric data analysis}, series = {Similarity-based Clustering and its Application to Medicine and Biology, 25.03. - 30.03.2007}, booktitle = {Similarity-based Clustering and its Application to Medicine and Biology, 25.03. - 30.03.2007}, editor = {Biehl, Michael and Hammer, Barbara and Verleysen, Michel and Villmann, Thomas}, language = {en} } @inproceedings{SchleifGisbrecht, author = {Schleif, Frank-Michael and Gisbrecht, Andrej}, title = {Data Analysis of (Non-)Metric Proximities at Linear Costs}, series = {Similarity-Based Pattern Recognition - Second International Workshop, SIMBAD 2013, York, UK, July 3-5, 2013. Proceedings}, booktitle = {Similarity-Based Pattern Recognition - Second International Workshop, SIMBAD 2013, York, UK, July 3-5, 2013. Proceedings}, editor = {Hancock, Edwin R. and Pelillo, Marcello}, doi = {10.1007/978-3-642-39140-8_4}, pages = {59 -- 74}, language = {en} } @article{VillmannSchleifKostrzewaetal., author = {Villmann, Thomas and Schleif, Frank-Michael and Kostrzewa, Markus and Walch, Axel and Hammer, Barbara}, title = {Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods}, series = {Briefings in Bioinformatics}, volume = {9}, journal = {Briefings in Bioinformatics}, number = {2}, doi = {10.1093/bib/bbn009}, pages = {129 -- 143}, language = {en} } @article{StrickertSchleifSeiffertetal., author = {Strickert, Marc and Schleif, Frank-Michael and Seiffert, Udo and Villmann, Thomas}, title = {Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data}, series = {Inteligencia Artificial}, volume = {12}, journal = {Inteligencia Artificial}, number = {37}, pages = {37 -- 44}, language = {en} } @article{GisbrechtMokbelSchleifetal., author = {Gisbrecht, Andrej and Mokbel, Bassam and Schleif, Frank-Michael and Zhu, Xibin and Hammer, Barbara}, title = {Linear Time Relational Prototype Based Learning}, series = {International Journal of Neural Systems}, volume = {22}, journal = {International Journal of Neural Systems}, number = {5}, doi = {10.1142/S0129065712500219}, language = {en} } @inproceedings{RaabMeierSchleif, author = {Raab, Christoph and Meier, Peter and Schleif, Frank-Michael}, title = {Domain Invariant Representations with Deep Spectral Alignment}, series = {28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2020, Bruges, Belgium, October 2-4, 2020}, booktitle = {28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2020, Bruges, Belgium, October 2-4, 2020}, pages = {509 -- 514}, language = {en} } @phdthesis{Schleif, author = {Schleif, Frank-Michael}, title = {Prototype based machine learning for clinical proteomics}, language = {en} } @incollection{SchleifVillmannHammer, author = {Schleif, Frank-Michael and Villmann, Thomas and Hammer, Barbara}, title = {Prototype Based Classification in Bioinformatics}, series = {Encyclopedia of Artificial Intelligence (3 Volumes)}, booktitle = {Encyclopedia of Artificial Intelligence (3 Volumes)}, editor = {Rabu{\~n}al, Juan R. and Dorado, Juli{\´a}n and Pazos, Alejandro}, pages = {1337 -- 1342}, language = {en} } @inproceedings{VillmannSeiffertSchleifetal., author = {Villmann, Thomas and Seiffert, Udo and Schleif, Frank-Michael and Br{\"u}ß, Cornelia and Geweniger, Tina and Hammer, Barbara}, title = {Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes}, series = {Artificial Neural Networks in Pattern Recognition, Second IAPR Workshop, ANNPR 2006, Ulm, Germany, August 31-September 2, 2006, Proceedings}, booktitle = {Artificial Neural Networks in Pattern Recognition, Second IAPR Workshop, ANNPR 2006, Ulm, Germany, August 31-September 2, 2006, Proceedings}, editor = {Schwenker, Friedhelm and Marinai, Simone}, doi = {10.1007/11829898_5}, pages = {46 -- 56}, language = {en} }