129 Publikationen

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[129]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2710031
Mokbel, B., Paaßen, B., Schleif, F.-M., Hammer, B.: Metric learning for sequences in relational LVQ. Neurocomputing. 169, 306-322 (2015).
PUB | PDF | DOI | Download (ext.) | WoS
 
[128]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2910619
Schleif, F.-M., Villmann, T., Zhu, X.: High Dimensional Matrix Relevance Learning. 2014 IEEE International Conference on Data Mining Workshop. IEEE, Piscataway, NJ (2015).
PUB | DOI
 
[127]
2015 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2910885
Schleif, F.-M., Gisbrecht, A., Tino, P.: Large Scale Indefinite Kernel Fisher Discriminant. In: Feragen, A., Pelillo, M., and Loog, M. (eds.) Similarity-Based Pattern Recognition. Similarity-Based Pattern Recognition : Third International Workshop, SIMBAD 2015, Proceedings. Lecture Notes in Computer Science. 9370, p. 160-170. Springer International Publishing, Cham (2015).
PUB | DOI
 
[126]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2772422
Gisbrecht, A., Schleif, F.-M.: Metric and non-metric proximity transformations at linear costs. Neurocomputing. 167, 643-657 (2015).
PUB | DOI | WoS
 
[125]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2759763
Schleif, F.-M., Zhu, X., Hammer, B.: Sparse conformal prediction for dissimilarity data. Annals of Mathematics and Artificial Intelligence. 74, 95-116 (2015).
PUB | DOI | WoS
 
[124]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2678214
Hofmann, D., Schleif, F.-M., Paaßen, B., Hammer, B.: Learning interpretable kernelized prototype-based models. Neurocomputing. 141, 84-96 (2014).
PUB | DOI | Download (ext.) | WoS
 
[123]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2615730
Hammer, B., Hofmann, D., Schleif, F.-M., Zhu, X.: Learning vector quantization for (dis-)similarities. NeuroComputing. 131, 43-51 (2014).
PUB | DOI | WoS
 
[122]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2690490
Strickert, M., Bunte, K., Schleif, F.-M., Huellermeier, E.: Correlation-based embedding of pairwise score data. Neurocomputing. 141, 97-109 (2014).
PUB | DOI | WoS
 
[121]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2672504
Zhu, X., Schleif, F.-M., Hammer, B.: Adaptive Conformal Semi-Supervised Vector Quantization for Dissimilarity Data. Pattern Recognition Lettters. 49, 138-145 (2014).
PUB | DOI | WoS
 
[120]
2013 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2612731
Micheli, A., Schleif, F.-M., Tino, P.: Novel approaches in machine learning and computational intelligence. Neurocomputing. 112, 1-3 (2013).
PUB | DOI | WoS
 
[119]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625202
Schleif, F.-M., Zhu, X., Hammer, B.: Sparse prototype representation by core sets. In: Hujun Yin, et.al (ed.) IDEAL 2013. (2013).
PUB
 
[118]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615717
Zhu, X., Schleif, F.-M., Hammer, B.: Secure Semi-supervised Vector Quantization for Dissimilarity Data. In: Rojas, I., Joya, G., and Cabestany, J. (eds.) IWANN (1). Lecture Notes in Computer Science. 7902, p. 347-356. Springer (2013).
PUB | DOI
 
[117]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615724
Schleif, F.-M., Gisbrecht, A.: Data Analysis of (Non-)Metric Proximities at Linear Costs. Proceedings of SIMBAD 2013. p. 59-74. Springer (2013).
PUB | DOI
 
[116]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615701
Zhu, X., Schleif, F.-M., Hammer, B.: Semi-Supervised Vector Quantization for proximity data. Proceedings of ESANN 2013. p. 89-94. (2013).
PUB
 
[115]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2625232
Gisbrecht, A., Mokbel, B., Schleif, F.-M., Zhu, X., Hammer, B.: Linear Time Relational Prototype Based Learning. Int. J. Neural Syst. 22, (2012).
PUB | DOI | WoS | PubMed | Europe PMC
 
[114]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615745
Bunte, K., Schleif, F.-M., Biehl, M.: Adaptive Learning for complex-valued data. Proceedings of ESANN 2012. p. 387-392. (2012).
PUB
 
[113]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534898
Biehl, M., Bunte, K., Schleif, F.-M., Schneider, P., Villmann, T.: Large margin linear discriminative visualization by Matrix Relevance Learning. IJCNN. p. 1-8. (2012).
PUB | DOI
 
[112]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615750
Schleif, F.-M., Zhu, X., Gisbrecht, A., Hammer, B.: Fast approximated relational and kernel clustering. Proceedings of ICPR 2012. p. 1229-1232. IEEE (2012).
PUB
 
[111]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615756
Schleif, F.-M., Zhu, X., Hammer, B.: Soft Competitive Learning for large data sets. Proceedings of MCSD 2012. p. 141-151. (2012).
PUB | DOI
 
[110]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2534839
Gisbrecht, A., Mokbel, B., Schleif, F.-M., Zhu, X., Hammer, B.: Linear Time Relational Prototype Based Learning. Int. J. Neural Syst. 22, 1250021 (2012).
PUB | DOI | WoS | PubMed | Europe PMC
 
[109]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534877
Schleif, F.-M., Mokbel, B., Gisbrecht, A., Theunissen, L., Dürr, V., Hammer, B.: Learning Relevant Time Points for Time-Series Data in the Life Sciences. ICANN (2). Lecture Notes in Computer Science. 7553, p. 531-539. (2012).
PUB | DOI
 
[108]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2489405
Bunte, K., Schneider, P., Hammer, B., Schleif, F.-M., Villmann, T., Biehl, M.: Limited Rank Matrix Learning, discriminative dimension reduction and visualization. Neural Networks. 26, 159-173 (2012).
PUB | DOI | WoS | PubMed | Europe PMC
 
[107]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534888
Schleif, F.-M., Zhu, X., Hammer, B.: A Conformal Classifier for Dissimilarity Data. AIAI (2). p. 234-243. (2012).
PUB | DOI
 
[106]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534910
Zhu, X., Schleif, F.-M., Hammer, B.: Patch Processing for Relational Learning Vector Quantization. ISNN (1). p. 55-63. (2012).
PUB | DOI
 
[105]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534868
Hammer, B., Mokbel, B., Schleif, F.-M., Zhu, X.: White Box Classification of Dissimilarity Data. HAIS (1). p. 309-321. (2012).
PUB | DOI | WoS
 
[104]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534905
Schleif, F.-M., Gisbrecht, A., Hammer, B.: Relevance learning for short high-dimensional time series in the life sciences. IJCNN. p. 1-8. (2012).
PUB | DOI
 
[103]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2509852
Zhu, X., Gisbrecht, A., Schleif, F.-M., Hammer, B.: Approximation techniques for clustering dissimilarity data. Neurocomputing. 90, 72-84 (2012).
PUB | DOI | WoS
 
[102]
2011 | Preprint | Veröffentlicht | PUB-ID: 2534994
Schleif, F.-M., Gisbrecht, A., Hammer, B.: Supervised learning of short and high-dimensional temporal sequences for life science measurements. (2011).
PUB | arXiv
 
[101]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276480
Gisbrecht, A., Schleif, F.-M., Zhu, X., Hammer, B.: Linear time heuristics for topographic mapping of dissimilarity data. Intelligent Data Engineering and Automated Learning - IDEAL 2011: IDEAL 2011, 12th international conference, Norwich, UK, September 7 - 9, 2011 ; proceedings. Lecture Notes in Computer Science. 6936, p. 25-33. Springer, Berlin, Heidelberg (2011).
PUB | DOI
 
[100]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276485
Hammer, B., Gisbrecht, A., Hasenfuss, A., Mokbel, B., Schleif, F.-M., Zhu, X.: Topographic Mapping of Dissimilarity Data. WSOM'11. (2011).
PUB
 
[99]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276492
Schleif, F.-M., Gisbrecht, A., Hammer, B.: Accelerating Kernel Neural Gas. In: Kaski, S., Honkela, T., Gitolami, M., and Dutch, W. (eds.) ICANN'2011. (2011).
PUB
 
[98]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276644
Seiffert, U., Schleif, F.-M., Zühlke, D.: Recent Trends in Computational Intelligence in Life Science. Proceedings of ESANN 2011. p. 77-86. (2011).
PUB
 
[97]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276640
Bunte, K., Schleif, F.-M., Villmann, T.: Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization. Proceedings of ESANN 2011. p. 29-34. Ciaco - i6doc.com (2011).
PUB
 
[96]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2290045
Lee, J.A., Schleif, F.-M., Martinetz, T.: Advances in artificial neural networks, machine learning, and computational intelligence. Neurocomputing. 74, 1299-1300 (2011).
PUB | DOI | WoS
 
[95]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2309980
Schleif, F.-M., Villmann, T., Hammer, B., Schneider, P.: Efficient Kernelized Prototype-based Classification. International Journal of Neural Systems. 21, 443-457 (2011).
PUB | DOI | WoS | PubMed | Europe PMC
 
[94]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276522
Gisbrecht, A., Hammer, B., Schleif, F.-M., Zhu, X.: Accelerating dissimilarity clustering for biomedical data analysis. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. p. pp.154-161. (2011).
PUB
 
[93]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276654
Schleif, F.-M.: Sparse Kernel Vector Quantization with Local Dependencies. Proceedings of IJCNN 2011. p. accepted. (2011).
PUB
 
[92]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992489
Mwebaze, E., Schneider, P., Schleif, F.-M., Aduwo, J.R., Quinn, J.A., Haase, S., Villmann, T., Biehl, M.: Divergence based classification in Learning Vector Quantization. Neurocomputing. 74, 1429-1435 (2011).
PUB | DOI | WoS
 
[91]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2094556
Schleif, F.-M., Riemer, T., Boerner, U., Schnapka-Hille, L., Cross, M.: Genetic algorithm for shift-uncertainty correction in 1-D NMR-based metabolite identifications and quantifications. Bioinformatics. 27, 524-533 (2011).
PUB | DOI | WoS | PubMed | Europe PMC
 
[90]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276636
Schleif, F.-M., Simmuteit, S., Villmann, T.: Hierarchical deconvolution of linear mixtures of high-dimensional mass spectra in micro-biology. Proceedings of AIA 2011. p. in press. (2011).
PUB
 
[89]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276648
Schneider, P., Geweniger, T., Schleif, F.-M., Biehl, M., Villmann, T.: Multivariate class labeling in Robust Soft LVQ. Proceedings of ESANN 2011. p. 17-22. (2011).
PUB
 
[88]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276626
Simmuteit, S., Schleif, F.-M., Villmann, T.: Hierarchical evolving trees together with global and local learning for large data sets in MALDI imaging. Proceedings of WCSB 2010. p. 103-106. (2010).
PUB
 
[87]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994127
Villmann, T., Haase, S., Schleif, F.-M., Hammer, B.: Divergence Based Online Learning in Vector Quantization. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L., and Zurada, J. (eds.) Artificial Intelligence and Soft Computing. Lecture Notes in Computer Science, 6113. p. 479-486. Springer, Berlin, Heidelberg (2010).
PUB | DOI
 
[86]
2010 | Konferenzbeitrag | Im Druck | PUB-ID: 1992498
Mwebaze, E., Schneider, P., Schleif, F.-M., Haase, S., Villmann, T., Biehl, M.: Divergence based Learning Vector Quantization. Proceedings of ESANN 2010. (In Press).
PUB
 
[85]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276630
Schleif, F.-M., Riemer, T., Boerner, U., Schnapka-Hille, L., Cross, M.: Efficient identification and quantification of metabolites in 1-H NMR measurements by a novel data encoding approach. Proceedings of WCSB 2010. p. 91-94. (2010).
PUB
 
[84]
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992441
Angulo, C., Lee, J.A., Schleif, F.-M.: Advances in computational intelligence and learning. NeuroComputing. 73, 1049-1050 (2010).
PUB | DOI | WoS
 
[83]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993978
Schleif, F.-M., Villmann, T., Hammer, B., Schneider, P., Biehl, M.: Generalized derivative based Kernelized learning vector quantization. In: Fyfe, C., Tino, P., Charles, D., Garcia-Osorio, C., and Yin, H. (eds.) Intelligent Data Engineering and Automated Learning – IDEAL 2010 11th International Conference, Paisley, UK, September 1-3, 2010. Proceedings. p. 21-28. Springer, Berlin u.a. (2010).
PUB | DOI
 
[82]
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994034
Simmuteit, S., Schleif, F.-M., Villmann, T., Hammer, B.: Evolving trees for the retrieval of mass spectrometry-based bacteria fingerprints. Knowledge and Information Systems. 25, 327-343 (2010).
PUB | DOI | WoS
 
[81]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992623
Zühlke, D., Schleif, F.-M., Geweniger, T., Villmann, T.: Learning vector quantization for heterogeneous structured data. Proceedings of the 18th European Symposium on Artificial Neural Networks (ESANN) 2010. d-side publications, Evere, Belgium (2010).
PUB
 
[80]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994138
Villmann, T., Haase, S., Schleif, F.-M., Hammer, B., Biehl, M.: The Mathematics of Divergence Based Online Learning in Vector Quanitzation. In: El Gayar, N. and Schwenker, F. (eds.) ANNPR'2010. p. 108-119. Springer, Berlin, Heidelberg (2010).
PUB
 
[79]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994227
Villmann, T., Schleif, F.-M., Hammer, B.: Sparse representation of data. In: Verleysen, M. (ed.) ESANN'10. p. 225-234. D side (2010).
PUB
 
[78]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993984
Schleif, F.-M., Villmann, T., Kostrzewa, M., Hammer, B., Gammerman, A.: Cancer Informatics by Prototype-networks in Mass Spectrometry. Artificial Intelligence in Medicine. 45, 215-228 (2009).
PUB | DOI | WoS | PubMed | Europe PMC
 
[77]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992551
Schleif, F.-M., Villmann, T.: Neural Maps and Learning Vector Quantization - Theory and Applications. Proceedings of the ESANN 2009. European Symposium on Artificial Neural Networks. Advances in Computational Intelligence and Learning. p. 509-516. d-side publications, Evere, Belgium (2009).
PUB
 
[76]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992570
Simmuteit, S., Schleif, F.-M., Villmann, T., Kostrzewa, M.: Hierarchical PCA using Tree-SOM for the Identification of Bacteria. In: Príncipe, J.C. and Miikkulainen, R. (eds.) Advances in Self-Organizing Maps. Proceedings of the 7th International Workshop on Self Organizing Maps WSOM 2009. LNCS, 5629. p. 272-280. Springer, Berlin (2009).
PUB | DOI
 
[75]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992575
Simmuteit, S., Simmuteit, J., Schleif, F.-M., Villmann, T.: Deconvolution and Identification of Mass Spectra from mixed and pure colonies of bacteria. In: Blazewicz, J., Ecker, K., and Hammer, B. (eds.) ICOLE 2009. IfI-09-12. p. 104-112. Technical University of Clausthal, Clausthal-Zellerfeld, Germany (2009).
PUB
 
[74]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992607
Villmann, T., Schleif, F.-M.: Functional Vector Quantization by Neural Maps. Proceedings of Whispers 2009. (2009).
PUB | DOI
 
[73]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1994067
Strickert, M., Schleif, F.-M., Villmann, T., Seiffert, U.: Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data. In: Biehl, M., Hammer, B., Verleysen, M., and Villmann, T. (eds.) Similarity-based Clustering. LNAI, 5400. p. 70-91. Springer, Berlin (2009).
PUB | DOI
 
[72]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992547
Schleif, F.-M., Biehl, M., Vellido, A.: Advances in machine learning and computational intelligence. NeuroComputing. 72, 1377-1378 (2009).
PUB | DOI | WoS
 
[71]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992580
Strickert, M., Keilwagen, J., Schleif, F.-M., T. Villmann, T., Biehl, M.: Matrix metric adaptation for improved linear discriminant analysis of biomedical data. In: Cabestany, J., Sandoval, F., Prieto, A., and Corchado, J.M. (eds.) Bio-Inspired Systems: Computational and Ambient Intelligence, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Proceedings. LNCS, 5517. Part 1, p. 933-940. Springer, Berlin (2009).
PUB | DOI
 
[70]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992526
Schleif, F.-M., Villmann, T., Ongyerth, M.: Supervised data analysis and reliability estimation for spectral data. NeuroComputing. 72, 3590-3601 (2009).
PUB | DOI | WoS
 
[69]
2009 | Report | Veröffentlicht | PUB-ID: 1993316
Biehl, M., Hammer, B., Schleif, F.-M., Schneider, P., Villmann, T.: Stationarity of Matrix Relevance Learning Vector Quantization. Machine Learning Reports. Universität Leipzig, Leipzig (2009).
PUB
 
[68]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992534
Schleif, F.-M., Riemer, T., Boerner, U., Cross, M.: Extended Targeted Profiling to Identify and Quantify Metabolites in 1-H NMR measurements. In: Blazewicz, J., Ecker, K., and Hammer, B. (eds.) ICOLE 2009. IfI-09-12. p. 89-103. Technical University of Clausthal, Clausthal-Zellerfeld, Germany (2009).
PUB
 
[67]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992565
Simmuteit, S., Schleif, F.-M., Villmann, T., Elssner, T.: Tanimoto metric in Tree-SOM for improved representation of mass spectrometry data with an underlying taxonomic structure. Proceedings of ICMLA 2009. p. 563--567. IEEE Press (2009).
PUB | DOI
 
[66]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992517
Schleif, F.-M., Lindemann, M., Maass, P., Diaz, M., Decker, J., Elssner, T., Kuhn, M., Thiele, H.: Support Vector Classification of Proteomic Profile Spectra based on Feature Extraction with the Bi-orthogonal Discrete Wavelet Transform. Computing and Visualization in Science. 12, 189-199 (2009).
PUB | DOI
 
[65]
2008 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1993939
Schleif, F.-M., Villmann, T., Hammer, B.: Pattern Recognition by Supervised Relevance Neural Gas and its Application to Spectral Data in Bioinformatics. In: Dopico, J.R.-n R.-al, Dorado, J., and Pazos, A. (eds.) Encyclopedia of Artificial Intelligence. p. 1337-1342. IGI Global (2008).
PUB
 
[64]
2008 | Report | Veröffentlicht | PUB-ID: 1993379
Bunte, K., Schneider, P., Hammer, B., Schleif, F.-M., Villmann, T., Biehl, M.: Discriminative Visualization by Limited Rank Matrix Learning. Machine Learning Reports. Universität Leipzig, Leipzig (2008).
PUB
 
[63]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992530
Schleif, F.-M., Ongyerth, M., Villmann, T.: Sparse coding Neural Gas for analysis of Nuclear Magnetic Resonance Spectroscopy. Proceedings of the CBMS 2008. p. 620-625. (2008).
PUB | DOI
 
[62]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992554
Schneider, P., Schleif, F.-M., Villmann, T., Biehl, M.: Generalized Matrix Learning Vector Quantizer for the Analysis of Spectral Data. In: Verleysen, M. (ed.) Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN) 2008. p. 451-456. d-side publications, Evere, Belgium (2008).
PUB
 
[61]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992597
Strickert, M., Schleif, F.-M., Villmann, T.: Metric adaptation for supervised attribute rating. In: Verleysen, M. (ed.) Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN) 2008. p. 31-36. d-side publications, Evere, Belgium (2008).
PUB
 
[60]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993966
Schleif, F.-M., Villmann, T., Hammer, B.: Prototype based Fuzzy Classification in Clinical Proteomics. International Journal of Approximate Reasoning. 47, 4-16 (2008).
PUB | DOI | WoS
 
[59]
2008 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1993900
Schleif, F.-M., Hammer, B., Villmann, T.: Analysis of Spectral Data in Clinical Proteomics by use of Learning Vector Quantizers. In: Van de Werff, M., Delder, A., and Tollenaar, R. (eds.) Computational Intelligence in Biomedicine and Bioinformatics: Current Trends and Applications. p. 141-167. Springer, Berlin (2008).
PUB | DOI
 
[58]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992539
Schleif, F.-M., Riemer, T., Cross, M., Villmann, T.: Automatic Identification and Quantification of Metabolites in H-NMR Measurements. Proceedings of the Workshop on Computational Systems Biology (WCSB) 2008. p. 165-168. (2008).
PUB
 
[57]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992589
Strickert, M., Schleif, F.-M., Seiffert, U.: Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data. Ibero-American Journal of Artificial Intelligence. 37, 37-44 (2008).
PUB
 
[56]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994253
Villmann, T., Schleif, F.-M., Kostrzewa, M., Walch, A., Hammer, B.: Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings in Bioinformatics. 9, 129-143 (2008).
PUB | DOI | WoS | PubMed | Europe PMC
 
[55]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2017617
Villmann, T., Hammer, B., Schleif, F.-M., Hermann, W., Cottrell, M.: Fuzzy Classification Using Information Theoretic Learning Vector Quantization. Neurocomputing. 71, 3070-3076 (2008).
PUB | DOI | WoS
 
[54]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2001836
Geweniger, T., Schleif, F.-M., Hasenfuss, A., Hammer, B., Villmann, T.: Comparison of cluster algorithms for the analysis of text data using Kolmogorov complexity. In: Köppen, M., Kasabov, N.K., and Coghill, G.G. (eds.) ICONIP 2008. p. 61-69. Springer, Berlin, Heidelberg (2008).
PUB | DOI
 
[53]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994267
Villmann, T., Schleif, F.-M., Merenyi, E., Strickert, M., Hammer, B.: Class imaging of hyperspectral satellite remote sensing data using FLSOM. Proceedings of 6th International Workshop on Self-Organizing Maps. Bielefeld University, Bielefeld (2007).
PUB | DOI
 
[52]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994016
Schneider, P., Biehl, M., Schleif, F.-M., Hammer, B.: Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data. Proceedings of 6th International Workshop on Self-Organizing Maps. Bielefeld University, Bielefeld (2007).
PUB | DOI
 
[51]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993547
Hammer, B., Hasenfuss, A., Schleif, F.-M., Villmann, T., Strickert, M., Seiffert, U.: Intuitive Clustering of Biological Data. Proceedings of International Joint Conference on Neural Networks. p. 1877-1882. IEEE (2007).
PUB | DOI
 
[50]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993852
Schleif, F.-M.: Advances in pre-processing and model generation for mass spectrometric data analysis. In: Biehl, M., Hammer, B., Verleysen, M., and Villmann, T. (eds.) Similarity-based Clustering and its Application to Medicine and Biology. Dagstuhl Seminar Proceedings. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany, Dagstuhl, Germany (2007).
PUB
 
[49]
2007 | Report | Veröffentlicht | PUB-ID: 1993922
Schleif, F.-M., Hasenfuss, A., Hammer, B.: Aggregation of multiple peak lists by use of an improved neural gas network. Universität Leipzig, Leipzig (2007).
PUB
 
[48]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992602
Strickert, M., Schleif, F.-M., Villmann, T., Seiffert, U.: Derivatives of Pearson Correlation for Gradient based Analysis of Biomedical Data. Similarity based Clustering. Lecture Notes in Artificial Intelligence, 5400. (2007).
PUB | DOI
 
[47]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993970
Schleif, F.-M., Villmann, T., Hammer, B.: Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing-Maps. In: Masulli, F., Mitra, S., and Pasi, G. (eds.) Application of Fuzzy Sets Theory. Proceedings of the 7th International Workshop on Fuzzy Logic and Applications. LNAI 4578. p. 563-570. Springer, Berlin, Heidelberg (2007).
PUB | DOI
 
[46]
2007 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992509
Schleif, F.-M.: Prototypen basiertes maschinelles Lernen in der klinischen Proteomik. In: Wagner, D. (ed.) Ausgezeichnete Informatikdissertationen 2006. GI-Edition Lecture Notes in Informatics. Dissertation. 7, p. 179-188. Gesellschaft für Informatik, Bonn (2007).
PUB
 
[45]
2007 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993911
Schleif, F.-M., Hammer, B., Villmann, T.: Margin based Active Learning for LVQ Networks. Neurocomputing. 70, 1215-1224 (2007).
PUB | DOI | WoS
 
[44]
2007 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992507
Schleif, F.-M.: Maschinelles Lernen mit Prototypmethoden in der klinischen Proteomik. KI - Künstliche Intelligenz. 65-67 (2007).
PUB
 
[43]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992610
Villmann, T., Schleif, F.-M., v.d.Werff, M., Deelder, A., Tollenaar, R.: Association learning in SOMs for Fuzzy-Classification. 6th International Conference on Machine Learning and Applications, 2007. p. 581-586. (2007).
PUB | DOI
 
[42]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992616
Villmann, T., Strickert, M., Brüß, C., Schleif, F.-M., Seiffert, U.: Visualization of fuzzy information in in fuzzy-classification for image sagmentation using MDS. In: Verleysen, M. (ed.) Proceedings of the 15th European Symposium on Artificial Neural Networks (ESANN) 2007. p. 103-108. d-side publications, Evere, Belgium (2007).
PUB
 
[41]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993811
Hasenfuss, A., Hammer, B., Schleif, F.-M., Villmann, T.: Neural gas clustering for dissimilarity data with continuous prototypes. In: Sandoval, F., Prieto, A., Cabestany, J., and Grana, M. (eds.) Computational and Ambient Intelligence – Proceedings of the 9th Work-conference on Artificial Neural Networks. LNCS 4507. p. 539-546. Springer, Berlin (2007).
PUB | DOI
 
[40]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992452
Deininger, S.-O., Gerhard, M., Schleif, F.-M.: Statistical Classification and Visualization of MALDI-Imaging Data. Proc. of CBMS 2007. p. 403-405. (2007).
PUB
 
[39]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993820
Hasenfuss, A., Hammer, B., Schleif, F.-M., Villmann, T.: Neural gas clustering for sparse proximity data. In: Sandoval, F., Prieto, A., Cabestany, J., and Grana, M. (eds.) Proceedings of the 9th International Work-Conference on Artificial Neural Networks.LNCS 4507. p. 539-546. Springer, Berlin, Heidelberg, Germany (2007).
PUB
 
[38]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993907
Schleif, F.-M., Hammer, B., Villmann, T.: Supervised Neural Gas for Functional Data and its Application to the Analysis of Clinical Proteom Spectra. In: Sandoval, F., Prieto, A., Cabestany, J., and Grana, M. (eds.) Computational and Ambient Intelligence. Proceedings of the 9th International Work-Conference on Artificial Neural Networks. LNCS, 4507. p. 1036-1044. Springer, Berlin, Heidelberg (2007).
PUB | DOI
 
[37]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994258
Villmann, T., Schleif, F.-M., Merenyi, E., Hammer, B.: Fuzzy Labeled Self Organizing Map for Clasification of Spectra. In: Sandoval, F., Prieto, A., Cabestany, J., and Grana, M. (eds.) Computational and Ambient Intelligence. Proceedings of the 9th Work-conference on Artificial Neural Networks. LNCS, 4507. p. 556-563. Springer, Berlin (2007).
PUB | DOI
 
[36]
2007 | Report | Veröffentlicht | PUB-ID: 1992505
Schleif, F.-M.: Preprocessing of Nuclear Magnetic Resonance Spectrometry Data. Machine Learning Reports. Universität Leipzig, Leipzig (2007).
PUB
 
[35]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992586
Strickert, M., Schleif, F.-M.: Supervised Attribute Relevance Determination for Protein Identification in Stress Experiments. Proc. of MLSB 2007. p. 81-86. (2007).
PUB
 
[34]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992593
Strickert, M., Schleif, F.-M., Seiffert, U.: Gradients of Pearson Correlation for Analysis of Biomedical Data. Proc. of ASAI 2007. p. 139-150. (2007).
PUB
 
[33]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994184
Villmann, T., Hammer, B., Schleif, F.-M., Geweniger, T., Fischer, T., Cottrell, M.: Prototype based classification using information theoretic learning. In: King, I., Wang, J., Chan, L., and Wang, D.L.L. (eds.) Neural Information Processing, 13th International Conference. Proceedings. Lecture Notes in Computer Science, 4233. Part II, p. 40-49. Springer, Berlin (2006).
PUB
 
[32]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994273
Villmann, T., Seiffert, U., Schleif, F.-M., Brüß, C., Geweniger, T., Hammer, B.: Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes. In: Schwenker, F. (ed.) Proceedings of Conference Artificial Neural Networks in Pattern Recognition. p. 46-56. Springer, Berlin (2006).
PUB | DOI
 
[31]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993578
Hammer, B., Hasenfuss, A., Schleif, F.-M., Villmann, T.: Supervised Batch Neural Gas. In: Schwenker, F. (ed.) Proceedings of Conference Artificial Neural Networks in Pattern Recognition (ANNPR). p. 33-45. Springer Verlag, Berlin (2006).
PUB | DOI
 
[30]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993895
Schleif, F.-M., Hammer, B., Villmann, T.: Margin based Active Learning for LVQ Networks. In: Verleysen, M. (ed.) Proc. Of European Symposium on Artificial Neural Networks. p. 539-544. d-side publications, Brussels, Belgium (2006).
PUB
 
[29]
2006 | Dissertation | PUB-ID: 1992511
Schleif, F.-M.: Prototype based Machine Learning for Clinical Proteomics. Technical University Clausthal, Clausthal-Zellerfeld, Germany (2006).
PUB
 
[28]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993889
Schleif, F.-M., Elssner, T., Kostrzewa, M., Villmann, T., Hammer, B.: Machine Learning and Soft-Computing in Bioinformatics. A Short Journey. Proc. of FLINS 2006. p. 541-548. World Scientific Press (2006).
PUB
 
[27]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993568
Hammer, B., Hasenfuss, A., Schleif, F.-M., Villmann, T.: Supervised median neural gas. In: Dagli, C., Buczak, A., Enke, D., Embrechts, A., and Ersoy, O. (eds.) Smart Engineering System Design. Intelligent Engineering Systems Through Artificial Neural Networks, 16. p. 623-633. ASME Press (2006).
PUB
 
[26]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993594
Hammer, B., Hasenfuss, A., Schleif, F.-M., Villmann, T.: Supervised median clustering. In: Dagli, C.H. (ed.) Smart systems engineering : infra-structure systems engineering, bio-informatics and computational biology and evolutionary computation : proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE 2006). ASME Press series on intelligent engineering systems through artificial neural networks, 16. p. 623-632. ASME Press, New York, NY (2006).
PUB
 
[25]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993878
Schleif, F.-M., Elssner, T., Kostrzewa, M., Villmann, T., Hammer, B.: Analysis and Visualization of Proteomic Data by Fuzzy labeled Self-Organizing Maps. In: Lee, D.J., Nutter, B., Antani, S., Mitra, S., and Archibald, J. (eds.) 19th IEEE International Symposium on Computer- based Medical Systems. p. 919-924. IEEE Computer Society Press, Los Alamitos (2006).
PUB | DOI
 
[24]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994237
Villmann, T., Schleif, F.-M., Hammer, B.: Comparison of relevance learning vector quantization with other metric adaptive classification methods. Neural Networks. 19, 610-622 (2006).
PUB | DOI | WoS | PubMed | Europe PMC
 
[23]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992445
Brüß, C., Bollenbeck, F., Schleif, F.-M., Weschke, W., Villmann, T., Seiffert, U.: Fuzzy Image Segmentation with Fuzzy Labelled Neural Gas. Proc. of ESANN 2006. p. 563-569. (2006).
PUB
 
[22]
2006 | Report | Veröffentlicht | PUB-ID: 1993584
Hammer, B., Hasenfuss, A., Schleif, F.-M., Villmann, T.: Supervised median clustering. IfI Technical reports. Clausthal University of Technology, Clausthal-Zellerfeld (2006).
PUB
 
[21]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994195
Villmann, T., Hammer, B., Schleif, F.-M., Geweniger, T., Herrmann, W.: Fuzzy Classification by Fuzzy Labeled Neural Gas. Neural Networks. 19, 772-779 (2006).
PUB | DOI | WoS | PubMed | Europe PMC
 
[20]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994241
Villmann, T., Schleif, F.-M., Hammer, B.: Prototype-based fuzzy classification with local relevance for proteomics. Neurocomputing. 69, 2425-2428 (2006).
PUB | DOI | WoS
 
[19]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2017225
Hammer, B., Villmann, T., Schleif, F.-M., Albani, C., Hermann, W.: Learning vector quantization classification with local relevance determination for medical data. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., and Zurada, J. (eds.) Artificial Intelligence and Soft-Computing - Proceedings of ICAISC 2006. LNAI, 4029. p. 603-612. Springer, Berlin, Heidelberg (2006).
PUB | DOI
 
[18]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994172
Villmann, T., Hammer, B., Schleif, F.-M., Geweniger, T.: Fuzzy Labeled Neural GAS for Fuzzy Classification. In: Cottrell, M. (ed.) Proceedings of the 5th Workshop on Self-Organizing Maps [on CD-ROM]. p. 283-290. University Paris-1-Pantheon-Sorbonne, Paris, France (2005).
PUB
 
[17]
2005 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992513
Schleif, F.-M.: Plugins mit wxWidgets. Offene Systeme. 2005, 5-10 (2005).
PUB
 
[16]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994219
Villmann, T., Schleif, F.-M., Hammer, B.: Fuzzy Classification for Classification of Mass Spectrometric Data Based on Learning Vector Quantization. International Workshop on Integrative Bioinformatics. (2005).
PUB
 
[15]
2005 | Report | Veröffentlicht | PUB-ID: 1993675
Hammer, B., Schleif, F.-M., Villmann, T.: On the Generalization Ability of Prototype-Based Classifiers with Local Relevance Determination. IfI Technical reports. Clausthal University of Technology, Clausthal-Zellerfeld (2005).
PUB
 
[14]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993974
Schleif, F.-M., Villmann, T., Hammer, B.: Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data. In: Bloch, I., Petrosino, A., and Tettamanzi, A.G.B. (eds.) Proceedings of the 6th Workshop on Fuzzy Logic and Applications. p. 290-296. Springer, Berlin, Heidelberg (2005).
PUB | DOI
 
[13]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994249
Villmann, T., Schleif, F.-M., Hammer, B.: Fuzzy labeled soft nearest neighbor classification with relevance learning. In: Wani, M.A., Cios, K.J., and Hafeez, K. (eds.) Proceedings of the International Conference of Machine Learning Applications. p. 11-15. IEEE Press, Los Angeles (2005).
PUB
 
[12]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994168
Villmann, T., Hammer, B., Schleif, F.-M.: Metrik Adaptation for Optimal Feature Classification in Learning Vector Quantization Applied to Environment Detection. In: Groß, H.-M., Debes, K., and Böhme, H.-J. (eds.) Proceedings of Selbstorganisation Von Adaptivem Verfahren. Fortschritts-Berichte VDI Reihe 10, Nr. 742. p. 592-597. VDI Verlag (2004).
PUB
 
[11]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994212
Villmann, T., Schleif, F.-M., Hammer, B.: Metric adaptation for optimal feature classification in learning vector quantization applied to environment detection. In: Groß, H.-M., Debes, K., and Böhme, H.-J. (eds.) SOAVE 2004, 3rd Workshop on SelfOrganization of AdaptiVE Behavior. VDI Verlag (2004).
PUB
 
[10]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993870
Schleif, F.-M., Clauss, U., Villmann, T., Hammer, B.: Supervised Relevance Neural Gas and Unified Maximum Separability Analysis for Classification of Mass Spectrometric Data. In: Wani, M.A., Cios, K.J., and Hafeez, K. (eds.) Proceedings of the 3rd International Conference on Machine Learning and Applications (ICMLA) 2004. p. 374-379. IEEE Press, Los Alamitos, CA, USA (2004).
PUB
 
[9]
2003 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994223
Villmann, T., Schleif, F.-M., Hammer, B.: Supervised Neural Gas and Relevance Learning in Learning Vector Quantization. In: Yamakawa, T. (ed.) Proceedings of the 4th Workshop on Self Organizing Maps [on CD-ROM]. p. 47-52. Kyushu Institute of Technology, Hibikino, Kitakyushu, Japan (2003).
PUB
 
[8]
2003 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992477
Köhler, M., Buchta, K., Schleif, F.-M., Sommerfeld, E.: A mission for the EEG coherence analysis: Is the task complex or difficult? Brain Topography. 15, 271 (2003).
PUB
 
[7]
2003 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992456
Dörfler, T., Simmel, A., Schleif, F.-M., Sommerfeld, E.: Working memory load and EEG coherence. Brain Topography. 15, 269 (2003).
PUB
 
[6]
2003 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992466
Gruhn, V., Hülder, M., Ijoui, R., Schleif, F.-M.: A distributed logistic support communication system. In: Linger, H., Fisher, J., Wojtkowski, W.G., Zupancic, J., Vigo, K., and Arnold, J. (eds.) Proceedings of ISD 2003 - Constructing the Infrastructure for the Knowledge Economy - Methods and Tools, Theory and Practice. p. 705-713. Kluwer Academic Publishers, London (2003).
PUB
 
[5]
2002 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992544
Schleif, F.-M., Stamer, H.: {LaTeX} im studentischen Alltag. Gaotenblatt. 3-10 (2002).
PUB
 
[4]
2002 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992483
Köhler, M., Buchta, K., Schleif, F.-M., Sommerfeld, E.: Complexity and difficulty in memory based comparison. In: da Silva, J.A., Filho, N.P.R., and Matsushima, E.H. (eds.) Proceedings of the 18th Meeting of the International Society for Psychophysics. p. 433-439. Pabst Publishing (2002).
PUB
 
[3]
2002 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992515
Schleif, F.-M.: OCR mit statistischen Momenten. Gaotenblatt. 2002, 15-17 (2002).
PUB
 
[2]
2001 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992560
Simmel, A., Dörfler, T., Schleif, F.-M., Sommerfeld, E.: An analysis of connections between internal and external learning process indicators using EEG coherence analysis. Proceedings of the 17th Meeting of the International Society for Psychophysics. p. 602-607. Pabst Publishing (2001).
PUB
 
[1]
2001 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992461
Dörfler, T., Simmel, A., Schleif, F.-M., Sommerfeld, E.: Complexity - dependent synchronization of brain subsystems during memorization. Proceedings of the 17th Meeting of the International Society for Psychophysics. p. 343-348. Pabst Publishing (2001).
PUB
 

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[129]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2710031
Mokbel, B., Paaßen, B., Schleif, F.-M., Hammer, B.: Metric learning for sequences in relational LVQ. Neurocomputing. 169, 306-322 (2015).
PUB | PDF | DOI | Download (ext.) | WoS
 
[128]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2910619
Schleif, F.-M., Villmann, T., Zhu, X.: High Dimensional Matrix Relevance Learning. 2014 IEEE International Conference on Data Mining Workshop. IEEE, Piscataway, NJ (2015).
PUB | DOI
 
[127]
2015 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2910885
Schleif, F.-M., Gisbrecht, A., Tino, P.: Large Scale Indefinite Kernel Fisher Discriminant. In: Feragen, A., Pelillo, M., and Loog, M. (eds.) Similarity-Based Pattern Recognition. Similarity-Based Pattern Recognition : Third International Workshop, SIMBAD 2015, Proceedings. Lecture Notes in Computer Science. 9370, p. 160-170. Springer International Publishing, Cham (2015).
PUB | DOI
 
[126]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2772422
Gisbrecht, A., Schleif, F.-M.: Metric and non-metric proximity transformations at linear costs. Neurocomputing. 167, 643-657 (2015).
PUB | DOI | WoS
 
[125]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2759763
Schleif, F.-M., Zhu, X., Hammer, B.: Sparse conformal prediction for dissimilarity data. Annals of Mathematics and Artificial Intelligence. 74, 95-116 (2015).
PUB | DOI | WoS
 
[124]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2678214
Hofmann, D., Schleif, F.-M., Paaßen, B., Hammer, B.: Learning interpretable kernelized prototype-based models. Neurocomputing. 141, 84-96 (2014).
PUB | DOI | Download (ext.) | WoS
 
[123]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2615730
Hammer, B., Hofmann, D., Schleif, F.-M., Zhu, X.: Learning vector quantization for (dis-)similarities. NeuroComputing. 131, 43-51 (2014).
PUB | DOI | WoS
 
[122]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2690490
Strickert, M., Bunte, K., Schleif, F.-M., Huellermeier, E.: Correlation-based embedding of pairwise score data. Neurocomputing. 141, 97-109 (2014).
PUB | DOI | WoS
 
[121]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2672504
Zhu, X., Schleif, F.-M., Hammer, B.: Adaptive Conformal Semi-Supervised Vector Quantization for Dissimilarity Data. Pattern Recognition Lettters. 49, 138-145 (2014).
PUB | DOI | WoS
 
[120]
2013 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2612731
Micheli, A., Schleif, F.-M., Tino, P.: Novel approaches in machine learning and computational intelligence. Neurocomputing. 112, 1-3 (2013).
PUB | DOI | WoS
 
[119]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625202
Schleif, F.-M., Zhu, X., Hammer, B.: Sparse prototype representation by core sets. In: Hujun Yin, et.al (ed.) IDEAL 2013. (2013).
PUB
 
[118]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615717
Zhu, X., Schleif, F.-M., Hammer, B.: Secure Semi-supervised Vector Quantization for Dissimilarity Data. In: Rojas, I., Joya, G., and Cabestany, J. (eds.) IWANN (1). Lecture Notes in Computer Science. 7902, p. 347-356. Springer (2013).
PUB | DOI
 
[117]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615724
Schleif, F.-M., Gisbrecht, A.: Data Analysis of (Non-)Metric Proximities at Linear Costs. Proceedings of SIMBAD 2013. p. 59-74. Springer (2013).
PUB | DOI
 
[116]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615701
Zhu, X., Schleif, F.-M., Hammer, B.: Semi-Supervised Vector Quantization for proximity data. Proceedings of ESANN 2013. p. 89-94. (2013).
PUB
 
[115]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2625232
Gisbrecht, A., Mokbel, B., Schleif, F.-M., Zhu, X., Hammer, B.: Linear Time Relational Prototype Based Learning. Int. J. Neural Syst. 22, (2012).
PUB | DOI | WoS | PubMed | Europe PMC
 
[114]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615745
Bunte, K., Schleif, F.-M., Biehl, M.: Adaptive Learning for complex-valued data. Proceedings of ESANN 2012. p. 387-392. (2012).
PUB
 
[113]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534898
Biehl, M., Bunte, K., Schleif, F.-M., Schneider, P., Villmann, T.: Large margin linear discriminative visualization by Matrix Relevance Learning. IJCNN. p. 1-8. (2012).
PUB | DOI
 
[112]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615750
Schleif, F.-M., Zhu, X., Gisbrecht, A., Hammer, B.: Fast approximated relational and kernel clustering. Proceedings of ICPR 2012. p. 1229-1232. IEEE (2012).
PUB
 
[111]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615756
Schleif, F.-M., Zhu, X., Hammer, B.: Soft Competitive Learning for large data sets. Proceedings of MCSD 2012. p. 141-151. (2012).
PUB | DOI
 
[110]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2534839
Gisbrecht, A., Mokbel, B., Schleif, F.-M., Zhu, X., Hammer, B.: Linear Time Relational Prototype Based Learning. Int. J. Neural Syst. 22, 1250021 (2012).
PUB | DOI | WoS | PubMed | Europe PMC
 
[109]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534877
Schleif, F.-M., Mokbel, B., Gisbrecht, A., Theunissen, L., Dürr, V., Hammer, B.: Learning Relevant Time Points for Time-Series Data in the Life Sciences. ICANN (2). Lecture Notes in Computer Science. 7553, p. 531-539. (2012).
PUB | DOI
 
[108]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2489405
Bunte, K., Schneider, P., Hammer, B., Schleif, F.-M., Villmann, T., Biehl, M.: Limited Rank Matrix Learning, discriminative dimension reduction and visualization. Neural Networks. 26, 159-173 (2012).
PUB | DOI | WoS | PubMed | Europe PMC
 
[107]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534888
Schleif, F.-M., Zhu, X., Hammer, B.: A Conformal Classifier for Dissimilarity Data. AIAI (2). p. 234-243. (2012).
PUB | DOI
 
[106]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534910
Zhu, X., Schleif, F.-M., Hammer, B.: Patch Processing for Relational Learning Vector Quantization. ISNN (1). p. 55-63. (2012).
PUB | DOI
 
[105]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534868
Hammer, B., Mokbel, B., Schleif, F.-M., Zhu, X.: White Box Classification of Dissimilarity Data. HAIS (1). p. 309-321. (2012).
PUB | DOI | WoS
 
[104]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534905
Schleif, F.-M., Gisbrecht, A., Hammer, B.: Relevance learning for short high-dimensional time series in the life sciences. IJCNN. p. 1-8. (2012).
PUB | DOI
 
[103]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2509852
Zhu, X., Gisbrecht, A., Schleif, F.-M., Hammer, B.: Approximation techniques for clustering dissimilarity data. Neurocomputing. 90, 72-84 (2012).
PUB | DOI | WoS
 
[102]
2011 | Preprint | Veröffentlicht | PUB-ID: 2534994
Schleif, F.-M., Gisbrecht, A., Hammer, B.: Supervised learning of short and high-dimensional temporal sequences for life science measurements. (2011).
PUB | arXiv
 
[101]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276480
Gisbrecht, A., Schleif, F.-M., Zhu, X., Hammer, B.: Linear time heuristics for topographic mapping of dissimilarity data. Intelligent Data Engineering and Automated Learning - IDEAL 2011: IDEAL 2011, 12th international conference, Norwich, UK, September 7 - 9, 2011 ; proceedings. Lecture Notes in Computer Science. 6936, p. 25-33. Springer, Berlin, Heidelberg (2011).
PUB | DOI
 
[100]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276485
Hammer, B., Gisbrecht, A., Hasenfuss, A., Mokbel, B., Schleif, F.-M., Zhu, X.: Topographic Mapping of Dissimilarity Data. WSOM'11. (2011).
PUB
 
[99]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276492
Schleif, F.-M., Gisbrecht, A., Hammer, B.: Accelerating Kernel Neural Gas. In: Kaski, S., Honkela, T., Gitolami, M., and Dutch, W. (eds.) ICANN'2011. (2011).
PUB
 
[98]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276644
Seiffert, U., Schleif, F.-M., Zühlke, D.: Recent Trends in Computational Intelligence in Life Science. Proceedings of ESANN 2011. p. 77-86. (2011).
PUB
 
[97]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276640
Bunte, K., Schleif, F.-M., Villmann, T.: Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization. Proceedings of ESANN 2011. p. 29-34. Ciaco - i6doc.com (2011).
PUB
 
[96]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2290045
Lee, J.A., Schleif, F.-M., Martinetz, T.: Advances in artificial neural networks, machine learning, and computational intelligence. Neurocomputing. 74, 1299-1300 (2011).
PUB | DOI | WoS
 
[95]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2309980
Schleif, F.-M., Villmann, T., Hammer, B., Schneider, P.: Efficient Kernelized Prototype-based Classification. International Journal of Neural Systems. 21, 443-457 (2011).
PUB | DOI | WoS | PubMed | Europe PMC
 
[94]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276522
Gisbrecht, A., Hammer, B., Schleif, F.-M., Zhu, X.: Accelerating dissimilarity clustering for biomedical data analysis. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. p. pp.154-161. (2011).
PUB
 
[93]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276654
Schleif, F.-M.: Sparse Kernel Vector Quantization with Local Dependencies. Proceedings of IJCNN 2011. p. accepted. (2011).
PUB
 
[92]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992489
Mwebaze, E., Schneider, P., Schleif, F.-M., Aduwo, J.R., Quinn, J.A., Haase, S., Villmann, T., Biehl, M.: Divergence based classification in Learning Vector Quantization. Neurocomputing. 74, 1429-1435 (2011).
PUB | DOI | WoS
 
[91]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2094556
Schleif, F.-M., Riemer, T., Boerner, U., Schnapka-Hille, L., Cross, M.: Genetic algorithm for shift-uncertainty correction in 1-D NMR-based metabolite identifications and quantifications. Bioinformatics. 27, 524-533 (2011).
PUB | DOI | WoS | PubMed | Europe PMC
 
[90]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276636
Schleif, F.-M., Simmuteit, S., Villmann, T.: Hierarchical deconvolution of linear mixtures of high-dimensional mass spectra in micro-biology. Proceedings of AIA 2011. p. in press. (2011).
PUB
 
[89]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276648
Schneider, P., Geweniger, T., Schleif, F.-M., Biehl, M., Villmann, T.: Multivariate class labeling in Robust Soft LVQ. Proceedings of ESANN 2011. p. 17-22. (2011).
PUB
 
[88]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276626
Simmuteit, S., Schleif, F.-M., Villmann, T.: Hierarchical evolving trees together with global and local learning for large data sets in MALDI imaging. Proceedings of WCSB 2010. p. 103-106. (2010).
PUB
 
[87]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994127
Villmann, T., Haase, S., Schleif, F.-M., Hammer, B.: Divergence Based Online Learning in Vector Quantization. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L., and Zurada, J. (eds.) Artificial Intelligence and Soft Computing. Lecture Notes in Computer Science, 6113. p. 479-486. Springer, Berlin, Heidelberg (2010).
PUB | DOI
 
[86]
2010 | Konferenzbeitrag | Im Druck | PUB-ID: 1992498
Mwebaze, E., Schneider, P., Schleif, F.-M., Haase, S., Villmann, T., Biehl, M.: Divergence based Learning Vector Quantization. Proceedings of ESANN 2010. (In Press).
PUB
 
[85]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276630
Schleif, F.-M., Riemer, T., Boerner, U., Schnapka-Hille, L., Cross, M.: Efficient identification and quantification of metabolites in 1-H NMR measurements by a novel data encoding approach. Proceedings of WCSB 2010. p. 91-94. (2010).
PUB
 
[84]
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992441
Angulo, C., Lee, J.A., Schleif, F.-M.: Advances in computational intelligence and learning. NeuroComputing. 73, 1049-1050 (2010).
PUB | DOI | WoS
 
[83]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993978
Schleif, F.-M., Villmann, T., Hammer, B., Schneider, P., Biehl, M.: Generalized derivative based Kernelized learning vector quantization. In: Fyfe, C., Tino, P., Charles, D., Garcia-Osorio, C., and Yin, H. (eds.) Intelligent Data Engineering and Automated Learning – IDEAL 2010 11th International Conference, Paisley, UK, September 1-3, 2010. Proceedings. p. 21-28. Springer, Berlin u.a. (2010).
PUB | DOI
 
[82]
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994034
Simmuteit, S., Schleif, F.-M., Villmann, T., Hammer, B.: Evolving trees for the retrieval of mass spectrometry-based bacteria fingerprints. Knowledge and Information Systems. 25, 327-343 (2010).
PUB | DOI | WoS
 
[81]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992623
Zühlke, D., Schleif, F.-M., Geweniger, T., Villmann, T.: Learning vector quantization for heterogeneous structured data. Proceedings of the 18th European Symposium on Artificial Neural Networks (ESANN) 2010. d-side publications, Evere, Belgium (2010).
PUB
 
[80]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994138
Villmann, T., Haase, S., Schleif, F.-M., Hammer, B., Biehl, M.: The Mathematics of Divergence Based Online Learning in Vector Quanitzation. In: El Gayar, N. and Schwenker, F. (eds.) ANNPR'2010. p. 108-119. Springer, Berlin, Heidelberg (2010).
PUB
 
[79]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994227
Villmann, T., Schleif, F.-M., Hammer, B.: Sparse representation of data. In: Verleysen, M. (ed.) ESANN'10. p. 225-234. D side (2010).
PUB
 
[78]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993984
Schleif, F.-M., Villmann, T., Kostrzewa, M., Hammer, B., Gammerman, A.: Cancer Informatics by Prototype-networks in Mass Spectrometry. Artificial Intelligence in Medicine. 45, 215-228 (2009).
PUB | DOI | WoS | PubMed | Europe PMC
 
[77]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992551
Schleif, F.-M., Villmann, T.: Neural Maps and Learning Vector Quantization - Theory and Applications. Proceedings of the ESANN 2009. European Symposium on Artificial Neural Networks. Advances in Computational Intelligence and Learning. p. 509-516. d-side publications, Evere, Belgium (2009).
PUB
 
[76]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992570
Simmuteit, S., Schleif, F.-M., Villmann, T., Kostrzewa, M.: Hierarchical PCA using Tree-SOM for the Identification of Bacteria. In: Príncipe, J.C. and Miikkulainen, R. (eds.) Advances in Self-Organizing Maps. Proceedings of the 7th International Workshop on Self Organizing Maps WSOM 2009. LNCS, 5629. p. 272-280. Springer, Berlin (2009).
PUB | DOI
 
[75]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992575
Simmuteit, S., Simmuteit, J., Schleif, F.-M., Villmann, T.: Deconvolution and Identification of Mass Spectra from mixed and pure colonies of bacteria. In: Blazewicz, J., Ecker, K., and Hammer, B. (eds.) ICOLE 2009. IfI-09-12. p. 104-112. Technical University of Clausthal, Clausthal-Zellerfeld, Germany (2009).
PUB
 
[74]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992607
Villmann, T., Schleif, F.-M.: Functional Vector Quantization by Neural Maps. Proceedings of Whispers 2009. (2009).
PUB | DOI
 
[73]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1994067
Strickert, M., Schleif, F.-M., Villmann, T., Seiffert, U.: Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data. In: Biehl, M., Hammer, B., Verleysen, M., and Villmann, T. (eds.) Similarity-based Clustering. LNAI, 5400. p. 70-91. Springer, Berlin (2009).
PUB | DOI
 
[72]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992547
Schleif, F.-M., Biehl, M., Vellido, A.: Advances in machine learning and computational intelligence. NeuroComputing. 72, 1377-1378 (2009).
PUB | DOI | WoS
 
[71]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992580
Strickert, M., Keilwagen, J., Schleif, F.-M., T. Villmann, T., Biehl, M.: Matrix metric adaptation for improved linear discriminant analysis of biomedical data. In: Cabestany, J., Sandoval, F., Prieto, A., and Corchado, J.M. (eds.) Bio-Inspired Systems: Computational and Ambient Intelligence, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Proceedings. LNCS, 5517. Part 1, p. 933-940. Springer, Berlin (2009).
PUB | DOI
 
[70]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992526
Schleif, F.-M., Villmann, T., Ongyerth, M.: Supervised data analysis and reliability estimation for spectral data. NeuroComputing. 72, 3590-3601 (2009).
PUB | DOI | WoS
 
[69]
2009 | Report | Veröffentlicht | PUB-ID: 1993316
Biehl, M., Hammer, B., Schleif, F.-M., Schneider, P., Villmann, T.: Stationarity of Matrix Relevance Learning Vector Quantization. Machine Learning Reports. Universität Leipzig, Leipzig (2009).
PUB
 
[68]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992534
Schleif, F.-M., Riemer, T., Boerner, U., Cross, M.: Extended Targeted Profiling to Identify and Quantify Metabolites in 1-H NMR measurements. In: Blazewicz, J., Ecker, K., and Hammer, B. (eds.) ICOLE 2009. IfI-09-12. p. 89-103. Technical University of Clausthal, Clausthal-Zellerfeld, Germany (2009).
PUB
 
[67]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992565
Simmuteit, S., Schleif, F.-M., Villmann, T., Elssner, T.: Tanimoto metric in Tree-SOM for improved representation of mass spectrometry data with an underlying taxonomic structure. Proceedings of ICMLA 2009. p. 563--567. IEEE Press (2009).
PUB | DOI
 
[66]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992517
Schleif, F.-M., Lindemann, M., Maass, P., Diaz, M., Decker, J., Elssner, T., Kuhn, M., Thiele, H.: Support Vector Classification of Proteomic Profile Spectra based on Feature Extraction with the Bi-orthogonal Discrete Wavelet Transform. Computing and Visualization in Science. 12, 189-199 (2009).
PUB | DOI
 
[65]
2008 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1993939
Schleif, F.-M., Villmann, T., Hammer, B.: Pattern Recognition by Supervised Relevance Neural Gas and its Application to Spectral Data in Bioinformatics. In: Dopico, J.R.-n R.-al, Dorado, J., and Pazos, A. (eds.) Encyclopedia of Artificial Intelligence. p. 1337-1342. IGI Global (2008).
PUB
 
[64]
2008 | Report | Veröffentlicht | PUB-ID: 1993379
Bunte, K., Schneider, P., Hammer, B., Schleif, F.-M., Villmann, T., Biehl, M.: Discriminative Visualization by Limited Rank Matrix Learning. Machine Learning Reports. Universität Leipzig, Leipzig (2008).
PUB
 
[63]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992530
Schleif, F.-M., Ongyerth, M., Villmann, T.: Sparse coding Neural Gas for analysis of Nuclear Magnetic Resonance Spectroscopy. Proceedings of the CBMS 2008. p. 620-625. (2008).
PUB | DOI
 
[62]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992554
Schneider, P., Schleif, F.-M., Villmann, T., Biehl, M.: Generalized Matrix Learning Vector Quantizer for the Analysis of Spectral Data. In: Verleysen, M. (ed.) Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN) 2008. p. 451-456. d-side publications, Evere, Belgium (2008).
PUB
 
[61]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992597
Strickert, M., Schleif, F.-M., Villmann, T.: Metric adaptation for supervised attribute rating. In: Verleysen, M. (ed.) Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN) 2008. p. 31-36. d-side publications, Evere, Belgium (2008).
PUB
 
[60]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993966
Schleif, F.-M., Villmann, T., Hammer, B.: Prototype based Fuzzy Classification in Clinical Proteomics. International Journal of Approximate Reasoning. 47, 4-16 (2008).
PUB | DOI | WoS
 
[59]
2008 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1993900
Schleif, F.-M., Hammer, B., Villmann, T.: Analysis of Spectral Data in Clinical Proteomics by use of Learning Vector Quantizers. In: Van de Werff, M., Delder, A., and Tollenaar, R. (eds.) Computational Intelligence in Biomedicine and Bioinformatics: Current Trends and Applications. p. 141-167. Springer, Berlin (2008).
PUB | DOI
 
[58]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992539
Schleif, F.-M., Riemer, T., Cross, M., Villmann, T.: Automatic Identification and Quantification of Metabolites in H-NMR Measurements. Proceedings of the Workshop on Computational Systems Biology (WCSB) 2008. p. 165-168. (2008).
PUB
 
[57]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992589
Strickert, M., Schleif, F.-M., Seiffert, U.: Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data. Ibero-American Journal of Artificial Intelligence. 37, 37-44 (2008).
PUB
 
[56]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994253
Villmann, T., Schleif, F.-M., Kostrzewa, M., Walch, A., Hammer, B.: Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings in Bioinformatics. 9, 129-143 (2008).
PUB | DOI | WoS | PubMed | Europe PMC
 
[55]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2017617
Villmann, T., Hammer, B., Schleif, F.-M., Hermann, W., Cottrell, M.: Fuzzy Classification Using Information Theoretic Learning Vector Quantization. Neurocomputing. 71, 3070-3076 (2008).
PUB | DOI | WoS
 
[54]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2001836
Geweniger, T., Schleif, F.-M., Hasenfuss, A., Hammer, B., Villmann, T.: Comparison of cluster algorithms for the analysis of text data using Kolmogorov complexity. In: Köppen, M., Kasabov, N.K., and Coghill, G.G. (eds.) ICONIP 2008. p. 61-69. Springer, Berlin, Heidelberg (2008).
PUB | DOI
 
[53]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994267
Villmann, T., Schleif, F.-M., Merenyi, E., Strickert, M., Hammer, B.: Class imaging of hyperspectral satellite remote sensing data using FLSOM. Proceedings of 6th International Workshop on Self-Organizing Maps. Bielefeld University, Bielefeld (2007).
PUB | DOI
 
[52]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994016
Schneider, P., Biehl, M., Schleif, F.-M., Hammer, B.: Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data. Proceedings of 6th International Workshop on Self-Organizing Maps. Bielefeld University, Bielefeld (2007).
PUB | DOI
 
[51]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993547
Hammer, B., Hasenfuss, A., Schleif, F.-M., Villmann, T., Strickert, M., Seiffert, U.: Intuitive Clustering of Biological Data. Proceedings of International Joint Conference on Neural Networks. p. 1877-1882. IEEE (2007).
PUB | DOI
 
[50]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993852
Schleif, F.-M.: Advances in pre-processing and model generation for mass spectrometric data analysis. In: Biehl, M., Hammer, B., Verleysen, M., and Villmann, T. (eds.) Similarity-based Clustering and its Application to Medicine and Biology. Dagstuhl Seminar Proceedings. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany, Dagstuhl, Germany (2007).
PUB
 
[49]
2007 | Report | Veröffentlicht | PUB-ID: 1993922
Schleif, F.-M., Hasenfuss, A., Hammer, B.: Aggregation of multiple peak lists by use of an improved neural gas network. Universität Leipzig, Leipzig (2007).
PUB
 
[48]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992602
Strickert, M., Schleif, F.-M., Villmann, T., Seiffert, U.: Derivatives of Pearson Correlation for Gradient based Analysis of Biomedical Data. Similarity based Clustering. Lecture Notes in Artificial Intelligence, 5400. (2007).
PUB | DOI
 
[47]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993970
Schleif, F.-M., Villmann, T., Hammer, B.: Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing-Maps. In: Masulli, F., Mitra, S., and Pasi, G. (eds.) Application of Fuzzy Sets Theory. Proceedings of the 7th International Workshop on Fuzzy Logic and Applications. LNAI 4578. p. 563-570. Springer, Berlin, Heidelberg (2007).
PUB | DOI
 
[46]
2007 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992509
Schleif, F.-M.: Prototypen basiertes maschinelles Lernen in der klinischen Proteomik. In: Wagner, D. (ed.) Ausgezeichnete Informatikdissertationen 2006. GI-Edition Lecture Notes in Informatics. Dissertation. 7, p. 179-188. Gesellschaft für Informatik, Bonn (2007).
PUB
 
[45]
2007 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993911
Schleif, F.-M., Hammer, B., Villmann, T.: Margin based Active Learning for LVQ Networks. Neurocomputing. 70, 1215-1224 (2007).
PUB | DOI | WoS
 
[44]
2007 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992507
Schleif, F.-M.: Maschinelles Lernen mit Prototypmethoden in der klinischen Proteomik. KI - Künstliche Intelligenz. 65-67 (2007).
PUB
 
[43]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992610
Villmann, T., Schleif, F.-M., v.d.Werff, M., Deelder, A., Tollenaar, R.: Association learning in SOMs for Fuzzy-Classification. 6th International Conference on Machine Learning and Applications, 2007. p. 581-586. (2007).
PUB | DOI
 
[42]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992616
Villmann, T., Strickert, M., Brüß, C., Schleif, F.-M., Seiffert, U.: Visualization of fuzzy information in in fuzzy-classification for image sagmentation using MDS. In: Verleysen, M. (ed.) Proceedings of the 15th European Symposium on Artificial Neural Networks (ESANN) 2007. p. 103-108. d-side publications, Evere, Belgium (2007).
PUB
 
[41]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993811
Hasenfuss, A., Hammer, B., Schleif, F.-M., Villmann, T.: Neural gas clustering for dissimilarity data with continuous prototypes. In: Sandoval, F., Prieto, A., Cabestany, J., and Grana, M. (eds.) Computational and Ambient Intelligence – Proceedings of the 9th Work-conference on Artificial Neural Networks. LNCS 4507. p. 539-546. Springer, Berlin (2007).
PUB | DOI
 
[40]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992452
Deininger, S.-O., Gerhard, M., Schleif, F.-M.: Statistical Classification and Visualization of MALDI-Imaging Data. Proc. of CBMS 2007. p. 403-405. (2007).
PUB
 
[39]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993820
Hasenfuss, A., Hammer, B., Schleif, F.-M., Villmann, T.: Neural gas clustering for sparse proximity data. In: Sandoval, F., Prieto, A., Cabestany, J., and Grana, M. (eds.) Proceedings of the 9th International Work-Conference on Artificial Neural Networks.LNCS 4507. p. 539-546. Springer, Berlin, Heidelberg, Germany (2007).
PUB
 
[38]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993907
Schleif, F.-M., Hammer, B., Villmann, T.: Supervised Neural Gas for Functional Data and its Application to the Analysis of Clinical Proteom Spectra. In: Sandoval, F., Prieto, A., Cabestany, J., and Grana, M. (eds.) Computational and Ambient Intelligence. Proceedings of the 9th International Work-Conference on Artificial Neural Networks. LNCS, 4507. p. 1036-1044. Springer, Berlin, Heidelberg (2007).
PUB | DOI
 
[37]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994258
Villmann, T., Schleif, F.-M., Merenyi, E., Hammer, B.: Fuzzy Labeled Self Organizing Map for Clasification of Spectra. In: Sandoval, F., Prieto, A., Cabestany, J., and Grana, M. (eds.) Computational and Ambient Intelligence. Proceedings of the 9th Work-conference on Artificial Neural Networks. LNCS, 4507. p. 556-563. Springer, Berlin (2007).
PUB | DOI
 
[36]
2007 | Report | Veröffentlicht | PUB-ID: 1992505
Schleif, F.-M.: Preprocessing of Nuclear Magnetic Resonance Spectrometry Data. Machine Learning Reports. Universität Leipzig, Leipzig (2007).
PUB
 
[35]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992586
Strickert, M., Schleif, F.-M.: Supervised Attribute Relevance Determination for Protein Identification in Stress Experiments. Proc. of MLSB 2007. p. 81-86. (2007).
PUB
 
[34]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992593
Strickert, M., Schleif, F.-M., Seiffert, U.: Gradients of Pearson Correlation for Analysis of Biomedical Data. Proc. of ASAI 2007. p. 139-150. (2007).
PUB
 
[33]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994184
Villmann, T., Hammer, B., Schleif, F.-M., Geweniger, T., Fischer, T., Cottrell, M.: Prototype based classification using information theoretic learning. In: King, I., Wang, J., Chan, L., and Wang, D.L.L. (eds.) Neural Information Processing, 13th International Conference. Proceedings. Lecture Notes in Computer Science, 4233. Part II, p. 40-49. Springer, Berlin (2006).
PUB
 
[32]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994273
Villmann, T., Seiffert, U., Schleif, F.-M., Brüß, C., Geweniger, T., Hammer, B.: Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes. In: Schwenker, F. (ed.) Proceedings of Conference Artificial Neural Networks in Pattern Recognition. p. 46-56. Springer, Berlin (2006).
PUB | DOI
 
[31]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993578
Hammer, B., Hasenfuss, A., Schleif, F.-M., Villmann, T.: Supervised Batch Neural Gas. In: Schwenker, F. (ed.) Proceedings of Conference Artificial Neural Networks in Pattern Recognition (ANNPR). p. 33-45. Springer Verlag, Berlin (2006).
PUB | DOI
 
[30]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993895
Schleif, F.-M., Hammer, B., Villmann, T.: Margin based Active Learning for LVQ Networks. In: Verleysen, M. (ed.) Proc. Of European Symposium on Artificial Neural Networks. p. 539-544. d-side publications, Brussels, Belgium (2006).
PUB
 
[29]
2006 | Dissertation | PUB-ID: 1992511
Schleif, F.-M.: Prototype based Machine Learning for Clinical Proteomics. Technical University Clausthal, Clausthal-Zellerfeld, Germany (2006).
PUB
 
[28]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993889
Schleif, F.-M., Elssner, T., Kostrzewa, M., Villmann, T., Hammer, B.: Machine Learning and Soft-Computing in Bioinformatics. A Short Journey. Proc. of FLINS 2006. p. 541-548. World Scientific Press (2006).
PUB
 
[27]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993568
Hammer, B., Hasenfuss, A., Schleif, F.-M., Villmann, T.: Supervised median neural gas. In: Dagli, C., Buczak, A., Enke, D., Embrechts, A., and Ersoy, O. (eds.) Smart Engineering System Design. Intelligent Engineering Systems Through Artificial Neural Networks, 16. p. 623-633. ASME Press (2006).
PUB
 
[26]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993594
Hammer, B., Hasenfuss, A., Schleif, F.-M., Villmann, T.: Supervised median clustering. In: Dagli, C.H. (ed.) Smart systems engineering : infra-structure systems engineering, bio-informatics and computational biology and evolutionary computation : proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE 2006). ASME Press series on intelligent engineering systems through artificial neural networks, 16. p. 623-632. ASME Press, New York, NY (2006).
PUB
 
[25]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993878
Schleif, F.-M., Elssner, T., Kostrzewa, M., Villmann, T., Hammer, B.: Analysis and Visualization of Proteomic Data by Fuzzy labeled Self-Organizing Maps. In: Lee, D.J., Nutter, B., Antani, S., Mitra, S., and Archibald, J. (eds.) 19th IEEE International Symposium on Computer- based Medical Systems. p. 919-924. IEEE Computer Society Press, Los Alamitos (2006).
PUB | DOI
 
[24]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994237
Villmann, T., Schleif, F.-M., Hammer, B.: Comparison of relevance learning vector quantization with other metric adaptive classification methods. Neural Networks. 19, 610-622 (2006).
PUB | DOI | WoS | PubMed | Europe PMC
 
[23]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992445
Brüß, C., Bollenbeck, F., Schleif, F.-M., Weschke, W., Villmann, T., Seiffert, U.: Fuzzy Image Segmentation with Fuzzy Labelled Neural Gas. Proc. of ESANN 2006. p. 563-569. (2006).
PUB
 
[22]
2006 | Report | Veröffentlicht | PUB-ID: 1993584
Hammer, B., Hasenfuss, A., Schleif, F.-M., Villmann, T.: Supervised median clustering. IfI Technical reports. Clausthal University of Technology, Clausthal-Zellerfeld (2006).
PUB
 
[21]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994195
Villmann, T., Hammer, B., Schleif, F.-M., Geweniger, T., Herrmann, W.: Fuzzy Classification by Fuzzy Labeled Neural Gas. Neural Networks. 19, 772-779 (2006).
PUB | DOI | WoS | PubMed | Europe PMC
 
[20]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994241
Villmann, T., Schleif, F.-M., Hammer, B.: Prototype-based fuzzy classification with local relevance for proteomics. Neurocomputing. 69, 2425-2428 (2006).
PUB | DOI | WoS
 
[19]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2017225
Hammer, B., Villmann, T., Schleif, F.-M., Albani, C., Hermann, W.: Learning vector quantization classification with local relevance determination for medical data. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., and Zurada, J. (eds.) Artificial Intelligence and Soft-Computing - Proceedings of ICAISC 2006. LNAI, 4029. p. 603-612. Springer, Berlin, Heidelberg (2006).
PUB | DOI
 
[18]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994172
Villmann, T., Hammer, B., Schleif, F.-M., Geweniger, T.: Fuzzy Labeled Neural GAS for Fuzzy Classification. In: Cottrell, M. (ed.) Proceedings of the 5th Workshop on Self-Organizing Maps [on CD-ROM]. p. 283-290. University Paris-1-Pantheon-Sorbonne, Paris, France (2005).
PUB
 
[17]
2005 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992513
Schleif, F.-M.: Plugins mit wxWidgets. Offene Systeme. 2005, 5-10 (2005).
PUB
 
[16]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994219
Villmann, T., Schleif, F.-M., Hammer, B.: Fuzzy Classification for Classification of Mass Spectrometric Data Based on Learning Vector Quantization. International Workshop on Integrative Bioinformatics. (2005).
PUB
 
[15]
2005 | Report | Veröffentlicht | PUB-ID: 1993675
Hammer, B., Schleif, F.-M., Villmann, T.: On the Generalization Ability of Prototype-Based Classifiers with Local Relevance Determination. IfI Technical reports. Clausthal University of Technology, Clausthal-Zellerfeld (2005).
PUB
 
[14]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993974
Schleif, F.-M., Villmann, T., Hammer, B.: Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data. In: Bloch, I., Petrosino, A., and Tettamanzi, A.G.B. (eds.) Proceedings of the 6th Workshop on Fuzzy Logic and Applications. p. 290-296. Springer, Berlin, Heidelberg (2005).
PUB | DOI
 
[13]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994249
Villmann, T., Schleif, F.-M., Hammer, B.: Fuzzy labeled soft nearest neighbor classification with relevance learning. In: Wani, M.A., Cios, K.J., and Hafeez, K. (eds.) Proceedings of the International Conference of Machine Learning Applications. p. 11-15. IEEE Press, Los Angeles (2005).
PUB
 
[12]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994168
Villmann, T., Hammer, B., Schleif, F.-M.: Metrik Adaptation for Optimal Feature Classification in Learning Vector Quantization Applied to Environment Detection. In: Groß, H.-M., Debes, K., and Böhme, H.-J. (eds.) Proceedings of Selbstorganisation Von Adaptivem Verfahren. Fortschritts-Berichte VDI Reihe 10, Nr. 742. p. 592-597. VDI Verlag (2004).
PUB
 
[11]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994212
Villmann, T., Schleif, F.-M., Hammer, B.: Metric adaptation for optimal feature classification in learning vector quantization applied to environment detection. In: Groß, H.-M., Debes, K., and Böhme, H.-J. (eds.) SOAVE 2004, 3rd Workshop on SelfOrganization of AdaptiVE Behavior. VDI Verlag (2004).
PUB
 
[10]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993870
Schleif, F.-M., Clauss, U., Villmann, T., Hammer, B.: Supervised Relevance Neural Gas and Unified Maximum Separability Analysis for Classification of Mass Spectrometric Data. In: Wani, M.A., Cios, K.J., and Hafeez, K. (eds.) Proceedings of the 3rd International Conference on Machine Learning and Applications (ICMLA) 2004. p. 374-379. IEEE Press, Los Alamitos, CA, USA (2004).
PUB
 
[9]
2003 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994223
Villmann, T., Schleif, F.-M., Hammer, B.: Supervised Neural Gas and Relevance Learning in Learning Vector Quantization. In: Yamakawa, T. (ed.) Proceedings of the 4th Workshop on Self Organizing Maps [on CD-ROM]. p. 47-52. Kyushu Institute of Technology, Hibikino, Kitakyushu, Japan (2003).
PUB
 
[8]
2003 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992477
Köhler, M., Buchta, K., Schleif, F.-M., Sommerfeld, E.: A mission for the EEG coherence analysis: Is the task complex or difficult? Brain Topography. 15, 271 (2003).
PUB
 
[7]
2003 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992456
Dörfler, T., Simmel, A., Schleif, F.-M., Sommerfeld, E.: Working memory load and EEG coherence. Brain Topography. 15, 269 (2003).
PUB
 
[6]
2003 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992466
Gruhn, V., Hülder, M., Ijoui, R., Schleif, F.-M.: A distributed logistic support communication system. In: Linger, H., Fisher, J., Wojtkowski, W.G., Zupancic, J., Vigo, K., and Arnold, J. (eds.) Proceedings of ISD 2003 - Constructing the Infrastructure for the Knowledge Economy - Methods and Tools, Theory and Practice. p. 705-713. Kluwer Academic Publishers, London (2003).
PUB
 
[5]
2002 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992544
Schleif, F.-M., Stamer, H.: {LaTeX} im studentischen Alltag. Gaotenblatt. 3-10 (2002).
PUB
 
[4]
2002 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992483
Köhler, M., Buchta, K., Schleif, F.-M., Sommerfeld, E.: Complexity and difficulty in memory based comparison. In: da Silva, J.A., Filho, N.P.R., and Matsushima, E.H. (eds.) Proceedings of the 18th Meeting of the International Society for Psychophysics. p. 433-439. Pabst Publishing (2002).
PUB
 
[3]
2002 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992515
Schleif, F.-M.: OCR mit statistischen Momenten. Gaotenblatt. 2002, 15-17 (2002).
PUB
 
[2]
2001 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992560
Simmel, A., Dörfler, T., Schleif, F.-M., Sommerfeld, E.: An analysis of connections between internal and external learning process indicators using EEG coherence analysis. Proceedings of the 17th Meeting of the International Society for Psychophysics. p. 602-607. Pabst Publishing (2001).
PUB
 
[1]
2001 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992461
Dörfler, T., Simmel, A., Schleif, F.-M., Sommerfeld, E.: Complexity - dependent synchronization of brain subsystems during memorization. Proceedings of the 17th Meeting of the International Society for Psychophysics. p. 343-348. Pabst Publishing (2001).
PUB
 

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