129 Publikationen

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[129]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2710031
Mokbel, B., Paaßen, B., Schleif, F. - M., & Hammer, B. (2015). Metric learning for sequences in relational LVQ. Neurocomputing, 169(SI), 306-322. doi:10.1016/j.neucom.2014.11.082
PUB | PDF | DOI | Download (ext.) | WoS
 
[128]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2910619
Schleif, F. - M., Villmann, T., & Zhu, X. (2015). High Dimensional Matrix Relevance Learning. 2014 IEEE International Conference on Data Mining Workshop Piscataway, NJ: IEEE. doi:10.1109/icdmw.2014.15
PUB | DOI
 
[127]
2015 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2910885
Schleif, F. - M., Gisbrecht, A., & Tino, P. (2015). Large Scale Indefinite Kernel Fisher Discriminant. In A. Feragen, M. Pelillo, & M. Loog (Eds.), Lecture Notes in Computer Science: Vol. 9370. Similarity-Based Pattern Recognition. Similarity-Based Pattern Recognition : Third International Workshop, SIMBAD 2015, Proceedings (pp. 160-170). Cham: Springer International Publishing. doi:10.1007/978-3-319-24261-3_13
PUB | DOI
 
[126]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2772422
Gisbrecht, A., & Schleif, F. - M. (2015). Metric and non-metric proximity transformations at linear costs. Neurocomputing, 167, 643-657. doi:10.1016/j.neucom.2015.04.017
PUB | DOI | WoS
 
[125]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2759763
Schleif, F. - M., Zhu, X., & Hammer, B. (2015). Sparse conformal prediction for dissimilarity data. Annals of Mathematics and Artificial Intelligence, 74(1-2), 95-116. doi:10.1007/s10472-014-9402-1
PUB | DOI | WoS
 
[124]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2678214
Hofmann, D., Schleif, F. - M., Paaßen, B., & Hammer, B. (2014). Learning interpretable kernelized prototype-based models. Neurocomputing, 141, 84-96. doi:10.1016/j.neucom.2014.03.003
PUB | DOI | Download (ext.) | WoS
 
[123]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2615730
Hammer, B., Hofmann, D., Schleif, F. - M., & Zhu, X. (2014). Learning vector quantization for (dis-)similarities. NeuroComputing, 131, 43-51. doi:10.1016/j.neucom.2013.05.054
PUB | DOI | WoS
 
[122]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2690490
Strickert, M., Bunte, K., Schleif, F. - M., & Huellermeier, E. (2014). Correlation-based embedding of pairwise score data. Neurocomputing, 141, 97-109. doi:10.1016/j.neucom.2014.01.049
PUB | DOI | WoS
 
[121]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2672504
Zhu, X., Schleif, F. - M., & Hammer, B. (2014). Adaptive Conformal Semi-Supervised Vector Quantization for Dissimilarity Data. Pattern Recognition Lettters, 49, 138-145. doi:10.1016/j.patrec.2014.07.009
PUB | DOI | WoS
 
[120]
2013 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2612731
Micheli, A., Schleif, F. - M., & Tino, P. (2013). Novel approaches in machine learning and computational intelligence. Neurocomputing, 112, 1-3. doi:10.1016/j.neucom.2013.01.005
PUB | DOI | WoS
 
[119]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625202
Schleif, F. - M., Zhu, X., & Hammer, B. (2013). Sparse prototype representation by core sets. In et.al Hujun Yin (Ed.), IDEAL 2013
PUB
 
[118]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615717
Zhu, X., Schleif, F. - M., & Hammer, B. (2013). Secure Semi-supervised Vector Quantization for Dissimilarity Data. In I. Rojas, G. Joya, & J. Cabestany (Eds.), Lecture Notes in Computer Science: Vol. 7902. IWANN (1) (pp. 347-356). Springer. doi:10.1007/978-3-642-38679-4_34
PUB | DOI
 
[117]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615724
Schleif, F. - M., & Gisbrecht, A. (2013). Data Analysis of (Non-)Metric Proximities at Linear Costs. Proceedings of SIMBAD 2013, 59-74. doi:10.1007/978-3-642-39140-8_4
PUB | DOI
 
[116]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615701
Zhu, X., Schleif, F. - M., & Hammer, B. (2013). Semi-Supervised Vector Quantization for proximity data. Proceedings of ESANN 2013, 89-94
PUB
 
[115]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2625232
Gisbrecht, A., Mokbel, B., Schleif, F. - M., Zhu, X., & Hammer, B. (2012). Linear Time Relational Prototype Based Learning. Int. J. Neural Syst., 22(5). doi:10.1142/S0129065712500219
PUB | DOI | WoS | PubMed | Europe PMC
 
[114]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615745
Bunte, K., Schleif, F. - M., & Biehl, M. (2012). Adaptive Learning for complex-valued data. Proceedings of ESANN 2012, 387-392
PUB
 
[113]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534898
Biehl, M., Bunte, K., Schleif, F. - M., Schneider, P., & Villmann, T. (2012). Large margin linear discriminative visualization by Matrix Relevance Learning. IJCNN, 1-8. doi:10.1109/ijcnn.2012.6252627
PUB | DOI
 
[112]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615750
Schleif, F. - M., Zhu, X., Gisbrecht, A., & Hammer, B. (2012). Fast approximated relational and kernel clustering. Proceedings of ICPR 2012, 1229-1232
PUB
 
[111]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615756
Schleif, F. - M., Zhu, X., & Hammer, B. (2012). Soft Competitive Learning for large data sets. Proceedings of MCSD 2012, 141-151. doi:10.1007/978-3-642-32518-2_14
PUB | DOI
 
[110]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2534839
Gisbrecht, A., Mokbel, B., Schleif, F. - M., Zhu, X., & Hammer, B. (2012). Linear Time Relational Prototype Based Learning. Int. J. Neural Syst., 22(05), 1250021. doi:10.1142/S0129065712500219
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. (2012). Learning Relevant Time Points for Time-Series Data in the Life Sciences. ICANN (2), 7553, 531-539. doi:10.1007/978-3-642-33266-1_66
PUB | DOI
 
[108]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2489405
Bunte, K., Schneider, P., Hammer, B., Schleif, F. - M., Villmann, T., & Biehl, M. (2012). Limited Rank Matrix Learning, discriminative dimension reduction and visualization. Neural Networks, 26, 159-173. doi:10.1016/j.neunet.2011.10.001
PUB | DOI | WoS | PubMed | Europe PMC
 
[107]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534888
Schleif, F. - M., Zhu, X., & Hammer, B. (2012). A Conformal Classifier for Dissimilarity Data. AIAI (2), 234-243. doi:10.1007/978-3-642-33412-2_24
PUB | DOI
 
[106]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534910
Zhu, X., Schleif, F. - M., & Hammer, B. (2012). Patch Processing for Relational Learning Vector Quantization. ISNN (1), 55-63. doi:10.1007/978-3-642-31346-2_7
PUB | DOI
 
[105]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534868
Hammer, B., Mokbel, B., Schleif, F. - M., & Zhu, X. (2012). White Box Classification of Dissimilarity Data. HAIS (1), 309-321. doi:10.1007/978-3-642-28942-2_28
PUB | DOI | WoS
 
[104]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534905
Schleif, F. - M., Gisbrecht, A., & Hammer, B. (2012). Relevance learning for short high-dimensional time series in the life sciences. IJCNN, 1-8. doi:10.1109/ijcnn.2012.6252653
PUB | DOI
 
[103]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2509852
Zhu, X., Gisbrecht, A., Schleif, F. - M., & Hammer, B. (2012). Approximation techniques for clustering dissimilarity data. Neurocomputing, 90, 72-84. doi:10.1016/j.neucom.2012.01.033
PUB | DOI | WoS
 
[102]
2011 | Preprint | Veröffentlicht | PUB-ID: 2534994
Schleif, F. - M., Gisbrecht, A., & Hammer, B. (2011). Supervised learning of short and high-dimensional temporal sequences for life science measurements
PUB | arXiv
 
[101]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276480
Gisbrecht, A., Schleif, F. - M., Zhu, X., & Hammer, B. (2011). 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, 25-33. Berlin, Heidelberg: Springer. doi:10.1007/978-3-642-23878-9_4
PUB | DOI
 
[100]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276485
Hammer, B., Gisbrecht, A., Hasenfuss, A., Mokbel, B., Schleif, F. - M., & Zhu, X. (2011). Topographic Mapping of Dissimilarity Data. WSOM'11
PUB
 
[99]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276492
Schleif, F. - M., Gisbrecht, A., & Hammer, B. (2011). Accelerating Kernel Neural Gas. In S. Kaski, T. Honkela, M. Gitolami, & W. Dutch (Eds.), ICANN'2011
PUB
 
[98]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276644
Seiffert, U., Schleif, F. - M., & Zühlke, D. (2011). Recent Trends in Computational Intelligence in Life Science. Proceedings of ESANN 2011, 77-86.
PUB
 
[97]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276640
Bunte, K., Schleif, F. - M., & Villmann, T. (2011). Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization. Proceedings of ESANN 2011, 29-34. Ciaco - i6doc.com.
PUB
 
[96]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2290045
Lee, J. A., Schleif, F. - M., & Martinetz, T. (2011). Advances in artificial neural networks, machine learning, and computational intelligence. Neurocomputing, 74(9), 1299-1300. doi:10.1016/j.neucom.2011.02.003
PUB | DOI | WoS
 
[95]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2309980
Schleif, F. - M., Villmann, T., Hammer, B., & Schneider, P. (2011). Efficient Kernelized Prototype-based Classification. International Journal of Neural Systems, 21(06), 443-457. doi:10.1142/s012906571100295x
PUB | DOI | WoS | PubMed | Europe PMC
 
[94]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276522
Gisbrecht, A., Hammer, B., Schleif, F. - M., & Zhu, X. (2011). Accelerating dissimilarity clustering for biomedical data analysis. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pp.154-161
PUB
 
[93]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276654
Schleif, F. - M. (2011). Sparse Kernel Vector Quantization with Local Dependencies. Proceedings of IJCNN 2011, accepted
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., et al. (2011). Divergence based classification in Learning Vector Quantization. Neurocomputing, 74(9), 1429-1435. doi:10.1016/j.neucom.2010.10.016
PUB | DOI | WoS
 
[91]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2094556
Schleif, F. - M., Riemer, T., Boerner, U., Schnapka-Hille, L., & Cross, M. (2011). Genetic algorithm for shift-uncertainty correction in 1-D NMR-based metabolite identifications and quantifications. Bioinformatics, 27(4), 524-533. doi:10.1093/bioinformatics/btq661
PUB | DOI | WoS | PubMed | Europe PMC
 
[90]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276636
Schleif, F. - M., Simmuteit, S., & Villmann, T. (2011). Hierarchical deconvolution of linear mixtures of high-dimensional mass spectra in micro-biology. Proceedings of AIA 2011, in press
PUB
 
[89]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276648
Schneider, P., Geweniger, T., Schleif, F. - M., Biehl, M., & Villmann, T. (2011). Multivariate class labeling in Robust Soft LVQ. Proceedings of ESANN 2011, 17-22
PUB
 
[88]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276626
Simmuteit, S., Schleif, F. - M., & Villmann, T. (2010). Hierarchical evolving trees together with global and local learning for large data sets in MALDI imaging. Proceedings of WCSB 2010, 103-106.
PUB
 
[87]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994127
Villmann, T., Haase, S., Schleif, F. - M., & Hammer, B. (2010). Divergence Based Online Learning in Vector Quantization. In L. Rutkowski, R. Scherer, R. Tadeusiewicz, L. Zadeh, & J. Zurada (Eds.), Artificial Intelligence and Soft Computing. Lecture Notes in Computer Science, 6113 (pp. 479-486). Berlin, Heidelberg: Springer. doi:10.1007/978-3-642-13208-7_60
PUB | DOI
 
[86]
2010 | Konferenzbeitrag | Im Druck | PUB-ID: 1992498
Mwebaze, E., Schneider, P., Schleif, F. - M., Haase, S., Villmann, T., & Biehl, M. (In Press). Divergence based Learning Vector Quantization. Proceedings of ESANN 2010
PUB
 
[85]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276630
Schleif, F. - M., Riemer, T., Boerner, U., Schnapka-Hille, L., & Cross, M. (2010). Efficient identification and quantification of metabolites in 1-H NMR measurements by a novel data encoding approach. Proceedings of WCSB 2010, 91-94
PUB
 
[84]
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992441
Angulo, C., Lee, J. A., & Schleif, F. - M. (2010). Advances in computational intelligence and learning. NeuroComputing, 73(7-9), 1049-1050. doi:10.1016/j.neucom.2009.12.020
PUB | DOI | WoS
 
[83]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993978
Schleif, F. - M., Villmann, T., Hammer, B., Schneider, P., & Biehl, M. (2010). Generalized derivative based Kernelized learning vector quantization. In C. Fyfe, P. Tino, D. Charles, C. Garcia-Osorio, & H. Yin (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2010 11th International Conference, Paisley, UK, September 1-3, 2010. Proceedings (pp. 21-28). Berlin u.a.: Springer. doi:10.1007/978-3-642-15381-5_3
PUB | DOI
 
[82]
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994034
Simmuteit, S., Schleif, F. - M., Villmann, T., & Hammer, B. (2010). Evolving trees for the retrieval of mass spectrometry-based bacteria fingerprints. Knowledge and Information Systems, 25(2), 327-343. doi:10.1007/s10115-009-0249-4
PUB | DOI | WoS
 
[81]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992623
Zühlke, D., Schleif, F. - M., Geweniger, T., & Villmann, T. (2010). Learning vector quantization for heterogeneous structured data. Proceedings of the 18th European Symposium on Artificial Neural Networks (ESANN) 2010
PUB
 
[80]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994138
Villmann, T., Haase, S., Schleif, F. - M., Hammer, B., & Biehl, M. (2010). The Mathematics of Divergence Based Online Learning in Vector Quanitzation. In N. El Gayar & F. Schwenker (Eds.), ANNPR'2010 (pp. 108-119). Berlin, Heidelberg: Springer.
PUB
 
[79]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994227
Villmann, T., Schleif, F. - M., & Hammer, B. (2010). Sparse representation of data. In M. Verleysen (Ed.), ESANN'10 (pp. 225-234). D side.
PUB
 
[78]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993984
Schleif, F. - M., Villmann, T., Kostrzewa, M., Hammer, B., & Gammerman, A. (2009). Cancer Informatics by Prototype-networks in Mass Spectrometry. Artificial Intelligence in Medicine, 45(2-3), 215-228. doi:10.1016/j.artmed.2008.07.018
PUB | DOI | WoS | PubMed | Europe PMC
 
[77]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992551
Schleif, F. - M., & Villmann, T. (2009). 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, 509-516. Evere, Belgium: d-side publications.
PUB
 
[76]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992570
Simmuteit, S., Schleif, F. - M., Villmann, T., & Kostrzewa, M. (2009). Hierarchical PCA using Tree-SOM for the Identification of Bacteria. In J. C. Príncipe & R. Miikkulainen (Eds.), Advances in Self-Organizing Maps. Proceedings of the 7th International Workshop on Self Organizing Maps WSOM 2009. LNCS, 5629 (pp. 272-280). Berlin: Springer. doi:10.1007/978-3-642-02397-2
PUB | DOI
 
[75]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992575
Simmuteit, S., Simmuteit, J., Schleif, F. - M., & Villmann, T. (2009). Deconvolution and Identification of Mass Spectra from mixed and pure colonies of bacteria. In J. Blazewicz, K. Ecker, & B. Hammer (Eds.), IfI-09-12. ICOLE 2009 (pp. 104-112). Clausthal-Zellerfeld, Germany: Technical University of Clausthal.
PUB
 
[74]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992607
Villmann, T., & Schleif, F. - M. (2009). Functional Vector Quantization by Neural Maps. Proceedings of Whispers 2009. doi:10.1109/whispers.2009.5289064
PUB | DOI
 
[73]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1994067
Strickert, M., Schleif, F. - M., Villmann, T., & Seiffert, U. (2009). Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data. In M. Biehl, B. Hammer, M. Verleysen, & T. Villmann (Eds.), LNAI, 5400. Similarity-based Clustering (pp. 70-91). Berlin: Springer. doi:10.1007/978-3-642-01805-3_5
PUB | DOI
 
[72]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992547
Schleif, F. - M., Biehl, M., & Vellido, A. (2009). Advances in machine learning and computational intelligence. NeuroComputing, 72(7-9), 1377-1378. doi:10.1016/j.neucom.2008.12.013
PUB | DOI | WoS
 
[71]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992580
Strickert, M., Keilwagen, J., Schleif, F. - M., T. Villmann, T., & Biehl, M. (2009). Matrix metric adaptation for improved linear discriminant analysis of biomedical data. In J. Cabestany, F. Sandoval, A. Prieto, & J. M. Corchado (Eds.), Bio-Inspired Systems: Computational and Ambient Intelligence, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Proceedings. LNCS, 5517 (Vol. Part 1, pp. 933-940). Berlin: Springer. doi:10.1007/978-3-642-02478-8
PUB | DOI
 
[70]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992526
Schleif, F. - M., Villmann, T., & Ongyerth, M. (2009). Supervised data analysis and reliability estimation for spectral data. NeuroComputing, 72(16-18), 3590-3601. doi:10.1016/j.neucom.2008.12.040
PUB | DOI | WoS
 
[69]
2009 | Report | Veröffentlicht | PUB-ID: 1993316
Biehl, M., Hammer, B., Schleif, F. - M., Schneider, P., & Villmann, T. (2009). Stationarity of Matrix Relevance Learning Vector Quantization (Machine Learning Reports). Leipzig: Universität Leipzig.
PUB
 
[68]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992534
Schleif, F. - M., Riemer, T., Boerner, U., & Cross, M. (2009). Extended Targeted Profiling to Identify and Quantify Metabolites in 1-H NMR measurements. In J. Blazewicz, K. Ecker, & B. Hammer (Eds.), IfI-09-12. ICOLE 2009 (pp. 89-103). Clausthal-Zellerfeld, Germany: Technical University of Clausthal.
PUB
 
[67]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992565
Simmuteit, S., Schleif, F. - M., Villmann, T., & Elssner, T. (2009). Tanimoto metric in Tree-SOM for improved representation of mass spectrometry data with an underlying taxonomic structure. Proceedings of ICMLA 2009, 563--567. doi:10.1109/ICMLA.2009.111
PUB | DOI
 
[66]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992517
Schleif, F. - M., Lindemann, M., Maass, P., Diaz, M., Decker, J., Elssner, T., Kuhn, M., et al. (2009). Support Vector Classification of Proteomic Profile Spectra based on Feature Extraction with the Bi-orthogonal Discrete Wavelet Transform. Computing and Visualization in Science, 12(4), 189-199. doi:10.1007/s00791-008-0087-z
PUB | DOI
 
[65]
2008 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1993939
Schleif, F. - M., Villmann, T., & Hammer, B. (2008). Pattern Recognition by Supervised Relevance Neural Gas and its Application to Spectral Data in Bioinformatics. In J. R. -n R. -al Dopico, J. Dorado, & A. Pazos (Eds.), Encyclopedia of Artificial Intelligence (pp. 1337-1342). IGI Global.
PUB
 
[64]
2008 | Report | Veröffentlicht | PUB-ID: 1993379
Bunte, K., Schneider, P., Hammer, B., Schleif, F. - M., Villmann, T., & Biehl, M. (2008). Discriminative Visualization by Limited Rank Matrix Learning (Machine Learning Reports). Leipzig: Universität Leipzig.
PUB
 
[63]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992530
Schleif, F. - M., Ongyerth, M., & Villmann, T. (2008). Sparse coding Neural Gas for analysis of Nuclear Magnetic Resonance Spectroscopy. Proceedings of the CBMS 2008, 620-625. doi:10.1109/cbms.2008.39
PUB | DOI
 
[62]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992554
Schneider, P., Schleif, F. - M., Villmann, T., & Biehl, M. (2008). Generalized Matrix Learning Vector Quantizer for the Analysis of Spectral Data. In M. Verleysen (Ed.), Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN) 2008 (pp. 451-456). Evere, Belgium: d-side publications.
PUB
 
[61]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992597
Strickert, M., Schleif, F. - M., & Villmann, T. (2008). Metric adaptation for supervised attribute rating. In M. Verleysen (Ed.), Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN) 2008 (pp. 31-36). Evere, Belgium: d-side publications.
PUB
 
[60]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993966
Schleif, F. - M., Villmann, T., & Hammer, B. (2008). Prototype based Fuzzy Classification in Clinical Proteomics. International Journal of Approximate Reasoning, 47(1), 4-16. doi:10.1016/j.ijar.2007.03.005
PUB | DOI | WoS
 
[59]
2008 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1993900
Schleif, F. - M., Hammer, B., & Villmann, T. (2008). Analysis of Spectral Data in Clinical Proteomics by use of Learning Vector Quantizers. In M. Van de Werff, A. Delder, & R. Tollenaar (Eds.), Computational Intelligence in Biomedicine and Bioinformatics: Current Trends and Applications (pp. 141-167). Berlin: Springer. doi:10.1007/978-3-540-70778-3_6
PUB | DOI
 
[58]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992539
Schleif, F. - M., Riemer, T., Cross, M., & Villmann, T. (2008). Automatic Identification and Quantification of Metabolites in H-NMR Measurements. Proceedings of the Workshop on Computational Systems Biology (WCSB) 2008, 165-168
PUB
 
[57]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992589
Strickert, M., Schleif, F. - M., & Seiffert, U. (2008). Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data. Ibero-American Journal of Artificial Intelligence, 37(12), 37-44.
PUB
 
[56]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994253
Villmann, T., Schleif, F. - M., Kostrzewa, M., Walch, A., & Hammer, B. (2008). Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings in Bioinformatics, 9(2), 129-143. doi:10.1093/bib/bbn009
PUB | DOI | WoS | PubMed | Europe PMC
 
[55]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2017617
Villmann, T., Hammer, B., Schleif, F. - M., Hermann, W., & Cottrell, M. (2008). Fuzzy Classification Using Information Theoretic Learning Vector Quantization. Neurocomputing, 71(16-18), 3070-3076. doi:10.1016/j.neucom.2008.04.048
PUB | DOI | WoS
 
[54]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2001836
Geweniger, T., Schleif, F. - M., Hasenfuss, A., Hammer, B., & Villmann, T. (2008). Comparison of cluster algorithms for the analysis of text data using Kolmogorov complexity. In M. Köppen, N. K. Kasabov, & G. G. Coghill (Eds.), ICONIP 2008 (pp. 61-69). Berlin, Heidelberg: Springer. doi:10.1007/978-3-642-03040-6_8
PUB | DOI
 
[53]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994267
Villmann, T., Schleif, F. - M., Merenyi, E., Strickert, M., & Hammer, B. (2007). Class imaging of hyperspectral satellite remote sensing data using FLSOM. Proceedings of 6th International Workshop on Self-Organizing Maps Bielefeld: Bielefeld University. doi:10.2390/biecoll-wsom2007-110
PUB | DOI
 
[52]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994016
Schneider, P., Biehl, M., Schleif, F. - M., & Hammer, B. (2007). Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data. Proceedings of 6th International Workshop on Self-Organizing Maps Bielefeld: Bielefeld University. doi:10.2390/biecoll-wsom2007-135
PUB | DOI
 
[51]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993547
Hammer, B., Hasenfuss, A., Schleif, F. - M., Villmann, T., Strickert, M., & Seiffert, U. (2007). Intuitive Clustering of Biological Data. Proceedings of International Joint Conference on Neural Networks, 1877-1882. IEEE. doi:10.1109/IJCNN.2007.4371244
PUB | DOI
 
[50]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993852
Schleif, F. - M. (2007). Advances in pre-processing and model generation for mass spectrometric data analysis. In M. Biehl, B. Hammer, M. Verleysen, & T. Villmann (Eds.), Similarity-based Clustering and its Application to Medicine and Biology. Dagstuhl Seminar Proceedings Dagstuhl, Germany: Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany.
PUB
 
[49]
2007 | Report | Veröffentlicht | PUB-ID: 1993922
Schleif, F. - M., Hasenfuss, A., & Hammer, B. (2007). Aggregation of multiple peak lists by use of an improved neural gas network. Leipzig: Universität Leipzig.
PUB
 
[48]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992602
Strickert, M., Schleif, F. - M., Villmann, T., & Seiffert, U. (2007). Derivatives of Pearson Correlation for Gradient based Analysis of Biomedical Data. Similarity based Clustering. Lecture Notes in Artificial Intelligence, 5400. doi:10.4114/ia.v12i37.956
PUB | DOI
 
[47]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993970
Schleif, F. - M., Villmann, T., & Hammer, B. (2007). Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing-Maps. In F. Masulli, S. Mitra, & G. Pasi (Eds.), Application of Fuzzy Sets Theory. Proceedings of the 7th International Workshop on Fuzzy Logic and Applications. LNAI 4578 (pp. 563-570). Berlin, Heidelberg: Springer. doi:10.1007/978-3-540-73400-0_72
PUB | DOI
 
[46]
2007 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992509
Schleif, F. - M. (2007). Prototypen basiertes maschinelles Lernen in der klinischen Proteomik. In D. Wagner (Ed.), GI-Edition Lecture Notes in Informatics. Dissertation: Vol. 7. Ausgezeichnete Informatikdissertationen 2006 (pp. 179-188). Bonn: Gesellschaft für Informatik.
PUB
 
[45]
2007 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993911
Schleif, F. - M., Hammer, B., & Villmann, T. (2007). Margin based Active Learning for LVQ Networks. Neurocomputing, 70(7-9), 1215-1224. doi:10.1016/j.neucom.2006.10.149
PUB | DOI | WoS
 
[44]
2007 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992507
Schleif, F. - M. (2007). Maschinelles Lernen mit Prototypmethoden in der klinischen Proteomik. KI - Künstliche Intelligenz(4), 65-67.
PUB
 
[43]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992610
Villmann, T., Schleif, F. - M., v.d.Werff, M., Deelder, A., & Tollenaar, R. (2007). Association learning in SOMs for Fuzzy-Classification. 6th International Conference on Machine Learning and Applications, 2007., 581-586. doi:10.1109/icmla.2007.29
PUB | DOI
 
[42]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992616
Villmann, T., Strickert, M., Brüß, C., Schleif, F. - M., & Seiffert, U. (2007). Visualization of fuzzy information in in fuzzy-classification for image sagmentation using MDS. In M. Verleysen (Ed.), Proceedings of the 15th European Symposium on Artificial Neural Networks (ESANN) 2007 (pp. 103-108). Evere, Belgium: d-side publications.
PUB
 
[41]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993811
Hasenfuss, A., Hammer, B., Schleif, F. - M., & Villmann, T. (2007). Neural gas clustering for dissimilarity data with continuous prototypes. In F. Sandoval, A. Prieto, J. Cabestany, & M. Grana (Eds.), Computational and Ambient Intelligence – Proceedings of the 9th Work-conference on Artificial Neural Networks. LNCS 4507 (pp. 539-546). Berlin: Springer. doi:10.1007/978-3-540-73007-1_66
PUB | DOI
 
[40]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992452
Deininger, S. - O., Gerhard, M., & Schleif, F. - M. (2007). Statistical Classification and Visualization of MALDI-Imaging Data. Proc. of CBMS 2007, 403-405
PUB
 
[39]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994258
Villmann, T., Schleif, F. - M., Merenyi, E., & Hammer, B. (2007). Fuzzy Labeled Self Organizing Map for Clasification of Spectra. In F. Sandoval, A. Prieto, J. Cabestany, & M. Grana (Eds.), Computational and Ambient Intelligence. Proceedings of the 9th Work-conference on Artificial Neural Networks. LNCS, 4507 (pp. 556-563). Berlin: Springer. doi:10.1007/978-3-540-73007-1_68
PUB | DOI
 
[38]
2007 | Report | Veröffentlicht | PUB-ID: 1992505
Schleif, F. - M. (2007). Preprocessing of Nuclear Magnetic Resonance Spectrometry Data (Machine Learning Reports). Leipzig: Universität Leipzig.
PUB
 
[37]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992586
Strickert, M., & Schleif, F. - M. (2007). Supervised Attribute Relevance Determination for Protein Identification in Stress Experiments. Proc. of MLSB 2007, 81-86
PUB
 
[36]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992593
Strickert, M., Schleif, F. - M., & Seiffert, U. (2007). Gradients of Pearson Correlation for Analysis of Biomedical Data. Proc. of ASAI 2007, 139-150
PUB
 
[35]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993820
Hasenfuss, A., Hammer, B., Schleif, F. - M., & Villmann, T. (2007). Neural gas clustering for sparse proximity data. In F. Sandoval, A. Prieto, J. Cabestany, & M. Grana (Eds.), Proceedings of the 9th International Work-Conference on Artificial Neural Networks.LNCS 4507 (pp. 539-546). Berlin, Heidelberg, Germany: Springer.
PUB
 
[34]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993907
Schleif, F. - M., Hammer, B., & Villmann, T. (2007). Supervised Neural Gas for Functional Data and its Application to the Analysis of Clinical Proteom Spectra. In F. Sandoval, A. Prieto, J. Cabestany, & M. Grana (Eds.), Computational and Ambient Intelligence. Proceedings of the 9th International Work-Conference on Artificial Neural Networks. LNCS, 4507 (pp. 1036-1044). Berlin, Heidelberg: Springer. doi:10.1007/978-3-540-73007-1_125
PUB | DOI
 
[33]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994184
Villmann, T., Hammer, B., Schleif, F. - M., Geweniger, T., Fischer, T., & Cottrell, M. (2006). Prototype based classification using information theoretic learning. In I. King, J. Wang, L. Chan, & D. L. L. Wang (Eds.), Lecture Notes in Computer Science, 4233: Vol. Part II. Neural Information Processing, 13th International Conference. Proceedings (pp. 40-49). Berlin: Springer.
PUB
 
[32]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994273
Villmann, T., Seiffert, U., Schleif, F. - M., Brüß, C., Geweniger, T., & Hammer, B. (2006). Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes. In F. Schwenker (Ed.), Proceedings of Conference Artificial Neural Networks in Pattern Recognition (pp. 46-56). Berlin: Springer. doi:10.1007/11829898_5
PUB | DOI
 
[31]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993578
Hammer, B., Hasenfuss, A., Schleif, F. - M., & Villmann, T. (2006). Supervised Batch Neural Gas. In F. Schwenker (Ed.), Proceedings of Conference Artificial Neural Networks in Pattern Recognition (ANNPR) (pp. 33-45). Berlin: Springer Verlag. doi:10.1007/11829898_4
PUB | DOI
 
[30]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993895
Schleif, F. - M., Hammer, B., & Villmann, T. (2006). Margin based Active Learning for LVQ Networks. In M. Verleysen (Ed.), Proc. Of European Symposium on Artificial Neural Networks (pp. 539-544). Brussels, Belgium: d-side publications.
PUB
 
[29]
2006 | Dissertation | PUB-ID: 1992511
Schleif, F. - M. (2006). Prototype based Machine Learning for Clinical Proteomics. Clausthal-Zellerfeld, Germany: Technical University Clausthal.
PUB
 
[28]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993889
Schleif, F. - M., Elssner, T., Kostrzewa, M., Villmann, T., & Hammer, B. (2006). Machine Learning and Soft-Computing in Bioinformatics. A Short Journey. Proc. of FLINS 2006, 541-548. World Scientific Press.
PUB
 
[27]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994237
Villmann, T., Schleif, F. - M., & Hammer, B. (2006). Comparison of relevance learning vector quantization with other metric adaptive classification methods. Neural Networks, 19(5), 610-622. doi:10.1016/j.neunet.2005.07.013
PUB | DOI | WoS | PubMed | Europe PMC
 
[26]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993568
Hammer, B., Hasenfuss, A., Schleif, F. - M., & Villmann, T. (2006). Supervised median neural gas. In C. Dagli, A. Buczak, D. Enke, A. Embrechts, & O. Ersoy (Eds.), Smart Engineering System Design. Intelligent Engineering Systems Through Artificial Neural Networks, 16 (pp. 623-633). ASME Press.
PUB
 
[25]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993594
Hammer, B., Hasenfuss, A., Schleif, F. - M., & Villmann, T. (2006). Supervised median clustering. In C. H. Dagli (Ed.), ASME Press series on intelligent engineering systems through artificial neural networks, 16. 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) (pp. 623-632). New York, NY: ASME Press.
PUB
 
[24]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993878
Schleif, F. - M., Elssner, T., Kostrzewa, M., Villmann, T., & Hammer, B. (2006). Analysis and Visualization of Proteomic Data by Fuzzy labeled Self-Organizing Maps. In D. J. Lee, B. Nutter, S. Antani, S. Mitra, & J. Archibald (Eds.), 19th IEEE International Symposium on Computer- based Medical Systems (pp. 919-924). Los Alamitos: IEEE Computer Society Press. doi:10.1109/cbms.2006.44
PUB | DOI
 
[23]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992445
Brüß, C., Bollenbeck, F., Schleif, F. - M., Weschke, W., Villmann, T., & Seiffert, U. (2006). Fuzzy Image Segmentation with Fuzzy Labelled Neural Gas. Proc. of ESANN 2006, 563-569
PUB
 
[22]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994195
Villmann, T., Hammer, B., Schleif, F. - M., Geweniger, T., & Herrmann, W. (2006). Fuzzy Classification by Fuzzy Labeled Neural Gas. Neural Networks, 19(6-7), 772-779. doi:10.1016/j.neunet.2006.05.026
PUB | DOI | WoS | PubMed | Europe PMC
 
[21]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994241
Villmann, T., Schleif, F. - M., & Hammer, B. (2006). Prototype-based fuzzy classification with local relevance for proteomics. Neurocomputing, 69(16-18), 2425-2428. doi:10.1016/j.neucom.2006.02.003
PUB | DOI | WoS
 
[20]
2006 | Report | Veröffentlicht | PUB-ID: 1993584
Hammer, B., Hasenfuss, A., Schleif, F. - M., & Villmann, T. (2006). Supervised median clustering (IfI Technical reports). Clausthal-Zellerfeld: Clausthal University of Technology.
PUB
 
[19]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2017225
Hammer, B., Villmann, T., Schleif, F. - M., Albani, C., & Hermann, W. (2006). Learning vector quantization classification with local relevance determination for medical data. In L. Rutkowski, R. Tadeusiewicz, L. A. Zadeh, & J. Zurada (Eds.), Artificial Intelligence and Soft-Computing - Proceedings of ICAISC 2006. LNAI, 4029 (pp. 603-612). Berlin, Heidelberg: Springer. doi:10.1007/11785231_63
PUB | DOI
 
[18]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994172
Villmann, T., Hammer, B., Schleif, F. - M., & Geweniger, T. (2005). Fuzzy Labeled Neural GAS for Fuzzy Classification. In M. Cottrell (Ed.), Proceedings of the 5th Workshop on Self-Organizing Maps [on CD-ROM] (pp. 283-290). Paris, France: University Paris-1-Pantheon-Sorbonne.
PUB
 
[17]
2005 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992513
Schleif, F. - M. (2005). Plugins mit wxWidgets. Offene Systeme, 2005(1), 5-10.
PUB
 
[16]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994219
Villmann, T., Schleif, F. - M., & Hammer, B. (2005). Fuzzy Classification for Classification of Mass Spectrometric Data Based on Learning Vector Quantization. International Workshop on Integrative Bioinformatics
PUB
 
[15]
2005 | Report | Veröffentlicht | PUB-ID: 1993675
Hammer, B., Schleif, F. - M., & Villmann, T. (2005). On the Generalization Ability of Prototype-Based Classifiers with Local Relevance Determination (IfI Technical reports). Clausthal-Zellerfeld: Clausthal University of Technology.
PUB
 
[14]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994249
Villmann, T., Schleif, F. - M., & Hammer, B. (2005). Fuzzy labeled soft nearest neighbor classification with relevance learning. In M. A. Wani, K. J. Cios, & K. Hafeez (Eds.), Proceedings of the International Conference of Machine Learning Applications (pp. 11-15). Los Angeles: IEEE Press.
PUB
 
[13]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993974
Schleif, F. - M., Villmann, T., & Hammer, B. (2005). Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data. In I. Bloch, A. Petrosino, & A. G. B. Tettamanzi (Eds.), Proceedings of the 6th Workshop on Fuzzy Logic and Applications (pp. 290-296). Berlin, Heidelberg: Springer. doi:10.1007/11676935_36
PUB | DOI
 
[12]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994168
Villmann, T., Hammer, B., & Schleif, F. - M. (2004). Metrik Adaptation for Optimal Feature Classification in Learning Vector Quantization Applied to Environment Detection. In H. - M. Groß, K. Debes, & H. - J. Böhme (Eds.), Proceedings of Selbstorganisation Von Adaptivem Verfahren. Fortschritts-Berichte VDI Reihe 10, Nr. 742 (pp. 592-597). VDI Verlag.
PUB
 
[11]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994212
Villmann, T., Schleif, F. - M., & Hammer, B. (2004). Metric adaptation for optimal feature classification in learning vector quantization applied to environment detection. In H. - M. Groß, K. Debes, & H. - J. Böhme (Eds.), SOAVE 2004, 3rd Workshop on SelfOrganization of AdaptiVE Behavior VDI Verlag.
PUB
 
[10]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993870
Schleif, F. - M., Clauss, U., Villmann, T., & Hammer, B. (2004). Supervised Relevance Neural Gas and Unified Maximum Separability Analysis for Classification of Mass Spectrometric Data. In M. A. Wani, K. J. Cios, & K. Hafeez (Eds.), Proceedings of the 3rd International Conference on Machine Learning and Applications (ICMLA) 2004 (pp. 374-379). Los Alamitos, CA, USA: IEEE Press.
PUB
 
[9]
2003 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994223
Villmann, T., Schleif, F. - M., & Hammer, B. (2003). Supervised Neural Gas and Relevance Learning in Learning Vector Quantization. In T. Yamakawa (Ed.), Proceedings of the 4th Workshop on Self Organizing Maps [on CD-ROM] (pp. 47-52). Hibikino, Kitakyushu, Japan: Kyushu Institute of Technology.
PUB
 
[8]
2003 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992477
Köhler, M., Buchta, K., Schleif, F. - M., & Sommerfeld, E. (2003). A mission for the EEG coherence analysis: Is the task complex or difficult? Brain Topography, 15(4), 271.
PUB
 
[7]
2003 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992456
Dörfler, T., Simmel, A., Schleif, F. - M., & Sommerfeld, E. (2003). Working memory load and EEG coherence. Brain Topography, 15(4), 269.
PUB
 
[6]
2003 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992466
Gruhn, V., Hülder, M., Ijoui, R., & Schleif, F. - M. (2003). A distributed logistic support communication system. In H. Linger, J. Fisher, W. G. Wojtkowski, J. Zupancic, K. Vigo, & J. Arnold (Eds.), Proceedings of ISD 2003 - Constructing the Infrastructure for the Knowledge Economy - Methods and Tools, Theory and Practice (pp. 705-713). London: Kluwer Academic Publishers.
PUB
 
[5]
2002 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992544
Schleif, F. - M., & Stamer, H. (2002). {LaTeX} im studentischen Alltag. Gaotenblatt, 3-10.
PUB
 
[4]
2002 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992483
Köhler, M., Buchta, K., Schleif, F. - M., & Sommerfeld, E. (2002). Complexity and difficulty in memory based comparison. In J. A. da Silva, N. P. R. Filho, & E. H. Matsushima (Eds.), Proceedings of the 18th Meeting of the International Society for Psychophysics (pp. 433-439). Pabst Publishing.
PUB
 
[3]
2002 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992515
Schleif, F. - M. (2002). OCR mit statistischen Momenten. Gaotenblatt, 2002, 15-17.
PUB
 
[2]
2001 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992560
Simmel, A., Dörfler, T., Schleif, F. - M., & Sommerfeld, E. (2001). 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, 602-607
PUB
 
[1]
2001 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992461
Dörfler, T., Simmel, A., Schleif, F. - M., & Sommerfeld, E. (2001). Complexity - dependent synchronization of brain subsystems during memorization. Proceedings of the 17th Meeting of the International Society for Psychophysics, 343-348
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[129]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2710031
Mokbel, B., Paaßen, B., Schleif, F. - M., & Hammer, B. (2015). Metric learning for sequences in relational LVQ. Neurocomputing, 169(SI), 306-322. doi:10.1016/j.neucom.2014.11.082
PUB | PDF | DOI | Download (ext.) | WoS
 
[128]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2910619
Schleif, F. - M., Villmann, T., & Zhu, X. (2015). High Dimensional Matrix Relevance Learning. 2014 IEEE International Conference on Data Mining Workshop Piscataway, NJ: IEEE. doi:10.1109/icdmw.2014.15
PUB | DOI
 
[127]
2015 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2910885
Schleif, F. - M., Gisbrecht, A., & Tino, P. (2015). Large Scale Indefinite Kernel Fisher Discriminant. In A. Feragen, M. Pelillo, & M. Loog (Eds.), Lecture Notes in Computer Science: Vol. 9370. Similarity-Based Pattern Recognition. Similarity-Based Pattern Recognition : Third International Workshop, SIMBAD 2015, Proceedings (pp. 160-170). Cham: Springer International Publishing. doi:10.1007/978-3-319-24261-3_13
PUB | DOI
 
[126]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2772422
Gisbrecht, A., & Schleif, F. - M. (2015). Metric and non-metric proximity transformations at linear costs. Neurocomputing, 167, 643-657. doi:10.1016/j.neucom.2015.04.017
PUB | DOI | WoS
 
[125]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2759763
Schleif, F. - M., Zhu, X., & Hammer, B. (2015). Sparse conformal prediction for dissimilarity data. Annals of Mathematics and Artificial Intelligence, 74(1-2), 95-116. doi:10.1007/s10472-014-9402-1
PUB | DOI | WoS
 
[124]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2678214
Hofmann, D., Schleif, F. - M., Paaßen, B., & Hammer, B. (2014). Learning interpretable kernelized prototype-based models. Neurocomputing, 141, 84-96. doi:10.1016/j.neucom.2014.03.003
PUB | DOI | Download (ext.) | WoS
 
[123]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2615730
Hammer, B., Hofmann, D., Schleif, F. - M., & Zhu, X. (2014). Learning vector quantization for (dis-)similarities. NeuroComputing, 131, 43-51. doi:10.1016/j.neucom.2013.05.054
PUB | DOI | WoS
 
[122]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2690490
Strickert, M., Bunte, K., Schleif, F. - M., & Huellermeier, E. (2014). Correlation-based embedding of pairwise score data. Neurocomputing, 141, 97-109. doi:10.1016/j.neucom.2014.01.049
PUB | DOI | WoS
 
[121]
2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2672504
Zhu, X., Schleif, F. - M., & Hammer, B. (2014). Adaptive Conformal Semi-Supervised Vector Quantization for Dissimilarity Data. Pattern Recognition Lettters, 49, 138-145. doi:10.1016/j.patrec.2014.07.009
PUB | DOI | WoS
 
[120]
2013 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2612731
Micheli, A., Schleif, F. - M., & Tino, P. (2013). Novel approaches in machine learning and computational intelligence. Neurocomputing, 112, 1-3. doi:10.1016/j.neucom.2013.01.005
PUB | DOI | WoS
 
[119]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625202
Schleif, F. - M., Zhu, X., & Hammer, B. (2013). Sparse prototype representation by core sets. In et.al Hujun Yin (Ed.), IDEAL 2013
PUB
 
[118]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615717
Zhu, X., Schleif, F. - M., & Hammer, B. (2013). Secure Semi-supervised Vector Quantization for Dissimilarity Data. In I. Rojas, G. Joya, & J. Cabestany (Eds.), Lecture Notes in Computer Science: Vol. 7902. IWANN (1) (pp. 347-356). Springer. doi:10.1007/978-3-642-38679-4_34
PUB | DOI
 
[117]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615724
Schleif, F. - M., & Gisbrecht, A. (2013). Data Analysis of (Non-)Metric Proximities at Linear Costs. Proceedings of SIMBAD 2013, 59-74. doi:10.1007/978-3-642-39140-8_4
PUB | DOI
 
[116]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615701
Zhu, X., Schleif, F. - M., & Hammer, B. (2013). Semi-Supervised Vector Quantization for proximity data. Proceedings of ESANN 2013, 89-94
PUB
 
[115]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2625232
Gisbrecht, A., Mokbel, B., Schleif, F. - M., Zhu, X., & Hammer, B. (2012). Linear Time Relational Prototype Based Learning. Int. J. Neural Syst., 22(5). doi:10.1142/S0129065712500219
PUB | DOI | WoS | PubMed | Europe PMC
 
[114]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615745
Bunte, K., Schleif, F. - M., & Biehl, M. (2012). Adaptive Learning for complex-valued data. Proceedings of ESANN 2012, 387-392
PUB
 
[113]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534898
Biehl, M., Bunte, K., Schleif, F. - M., Schneider, P., & Villmann, T. (2012). Large margin linear discriminative visualization by Matrix Relevance Learning. IJCNN, 1-8. doi:10.1109/ijcnn.2012.6252627
PUB | DOI
 
[112]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615750
Schleif, F. - M., Zhu, X., Gisbrecht, A., & Hammer, B. (2012). Fast approximated relational and kernel clustering. Proceedings of ICPR 2012, 1229-1232
PUB
 
[111]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615756
Schleif, F. - M., Zhu, X., & Hammer, B. (2012). Soft Competitive Learning for large data sets. Proceedings of MCSD 2012, 141-151. doi:10.1007/978-3-642-32518-2_14
PUB | DOI
 
[110]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2534839
Gisbrecht, A., Mokbel, B., Schleif, F. - M., Zhu, X., & Hammer, B. (2012). Linear Time Relational Prototype Based Learning. Int. J. Neural Syst., 22(05), 1250021. doi:10.1142/S0129065712500219
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. (2012). Learning Relevant Time Points for Time-Series Data in the Life Sciences. ICANN (2), 7553, 531-539. doi:10.1007/978-3-642-33266-1_66
PUB | DOI
 
[108]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2489405
Bunte, K., Schneider, P., Hammer, B., Schleif, F. - M., Villmann, T., & Biehl, M. (2012). Limited Rank Matrix Learning, discriminative dimension reduction and visualization. Neural Networks, 26, 159-173. doi:10.1016/j.neunet.2011.10.001
PUB | DOI | WoS | PubMed | Europe PMC
 
[107]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534888
Schleif, F. - M., Zhu, X., & Hammer, B. (2012). A Conformal Classifier for Dissimilarity Data. AIAI (2), 234-243. doi:10.1007/978-3-642-33412-2_24
PUB | DOI
 
[106]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534910
Zhu, X., Schleif, F. - M., & Hammer, B. (2012). Patch Processing for Relational Learning Vector Quantization. ISNN (1), 55-63. doi:10.1007/978-3-642-31346-2_7
PUB | DOI
 
[105]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534868
Hammer, B., Mokbel, B., Schleif, F. - M., & Zhu, X. (2012). White Box Classification of Dissimilarity Data. HAIS (1), 309-321. doi:10.1007/978-3-642-28942-2_28
PUB | DOI | WoS
 
[104]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534905
Schleif, F. - M., Gisbrecht, A., & Hammer, B. (2012). Relevance learning for short high-dimensional time series in the life sciences. IJCNN, 1-8. doi:10.1109/ijcnn.2012.6252653
PUB | DOI
 
[103]
2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2509852
Zhu, X., Gisbrecht, A., Schleif, F. - M., & Hammer, B. (2012). Approximation techniques for clustering dissimilarity data. Neurocomputing, 90, 72-84. doi:10.1016/j.neucom.2012.01.033
PUB | DOI | WoS
 
[102]
2011 | Preprint | Veröffentlicht | PUB-ID: 2534994
Schleif, F. - M., Gisbrecht, A., & Hammer, B. (2011). Supervised learning of short and high-dimensional temporal sequences for life science measurements
PUB | arXiv
 
[101]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276480
Gisbrecht, A., Schleif, F. - M., Zhu, X., & Hammer, B. (2011). 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, 25-33. Berlin, Heidelberg: Springer. doi:10.1007/978-3-642-23878-9_4
PUB | DOI
 
[100]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276485
Hammer, B., Gisbrecht, A., Hasenfuss, A., Mokbel, B., Schleif, F. - M., & Zhu, X. (2011). Topographic Mapping of Dissimilarity Data. WSOM'11
PUB
 
[99]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276492
Schleif, F. - M., Gisbrecht, A., & Hammer, B. (2011). Accelerating Kernel Neural Gas. In S. Kaski, T. Honkela, M. Gitolami, & W. Dutch (Eds.), ICANN'2011
PUB
 
[98]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276644
Seiffert, U., Schleif, F. - M., & Zühlke, D. (2011). Recent Trends in Computational Intelligence in Life Science. Proceedings of ESANN 2011, 77-86.
PUB
 
[97]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276640
Bunte, K., Schleif, F. - M., & Villmann, T. (2011). Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization. Proceedings of ESANN 2011, 29-34. Ciaco - i6doc.com.
PUB
 
[96]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2290045
Lee, J. A., Schleif, F. - M., & Martinetz, T. (2011). Advances in artificial neural networks, machine learning, and computational intelligence. Neurocomputing, 74(9), 1299-1300. doi:10.1016/j.neucom.2011.02.003
PUB | DOI | WoS
 
[95]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2309980
Schleif, F. - M., Villmann, T., Hammer, B., & Schneider, P. (2011). Efficient Kernelized Prototype-based Classification. International Journal of Neural Systems, 21(06), 443-457. doi:10.1142/s012906571100295x
PUB | DOI | WoS | PubMed | Europe PMC
 
[94]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276522
Gisbrecht, A., Hammer, B., Schleif, F. - M., & Zhu, X. (2011). Accelerating dissimilarity clustering for biomedical data analysis. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pp.154-161
PUB
 
[93]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276654
Schleif, F. - M. (2011). Sparse Kernel Vector Quantization with Local Dependencies. Proceedings of IJCNN 2011, accepted
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., et al. (2011). Divergence based classification in Learning Vector Quantization. Neurocomputing, 74(9), 1429-1435. doi:10.1016/j.neucom.2010.10.016
PUB | DOI | WoS
 
[91]
2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2094556
Schleif, F. - M., Riemer, T., Boerner, U., Schnapka-Hille, L., & Cross, M. (2011). Genetic algorithm for shift-uncertainty correction in 1-D NMR-based metabolite identifications and quantifications. Bioinformatics, 27(4), 524-533. doi:10.1093/bioinformatics/btq661
PUB | DOI | WoS | PubMed | Europe PMC
 
[90]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276636
Schleif, F. - M., Simmuteit, S., & Villmann, T. (2011). Hierarchical deconvolution of linear mixtures of high-dimensional mass spectra in micro-biology. Proceedings of AIA 2011, in press
PUB
 
[89]
2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276648
Schneider, P., Geweniger, T., Schleif, F. - M., Biehl, M., & Villmann, T. (2011). Multivariate class labeling in Robust Soft LVQ. Proceedings of ESANN 2011, 17-22
PUB
 
[88]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276626
Simmuteit, S., Schleif, F. - M., & Villmann, T. (2010). Hierarchical evolving trees together with global and local learning for large data sets in MALDI imaging. Proceedings of WCSB 2010, 103-106.
PUB
 
[87]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994127
Villmann, T., Haase, S., Schleif, F. - M., & Hammer, B. (2010). Divergence Based Online Learning in Vector Quantization. In L. Rutkowski, R. Scherer, R. Tadeusiewicz, L. Zadeh, & J. Zurada (Eds.), Artificial Intelligence and Soft Computing. Lecture Notes in Computer Science, 6113 (pp. 479-486). Berlin, Heidelberg: Springer. doi:10.1007/978-3-642-13208-7_60
PUB | DOI
 
[86]
2010 | Konferenzbeitrag | Im Druck | PUB-ID: 1992498
Mwebaze, E., Schneider, P., Schleif, F. - M., Haase, S., Villmann, T., & Biehl, M. (In Press). Divergence based Learning Vector Quantization. Proceedings of ESANN 2010
PUB
 
[85]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276630
Schleif, F. - M., Riemer, T., Boerner, U., Schnapka-Hille, L., & Cross, M. (2010). Efficient identification and quantification of metabolites in 1-H NMR measurements by a novel data encoding approach. Proceedings of WCSB 2010, 91-94
PUB
 
[84]
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992441
Angulo, C., Lee, J. A., & Schleif, F. - M. (2010). Advances in computational intelligence and learning. NeuroComputing, 73(7-9), 1049-1050. doi:10.1016/j.neucom.2009.12.020
PUB | DOI | WoS
 
[83]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993978
Schleif, F. - M., Villmann, T., Hammer, B., Schneider, P., & Biehl, M. (2010). Generalized derivative based Kernelized learning vector quantization. In C. Fyfe, P. Tino, D. Charles, C. Garcia-Osorio, & H. Yin (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2010 11th International Conference, Paisley, UK, September 1-3, 2010. Proceedings (pp. 21-28). Berlin u.a.: Springer. doi:10.1007/978-3-642-15381-5_3
PUB | DOI
 
[82]
2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994034
Simmuteit, S., Schleif, F. - M., Villmann, T., & Hammer, B. (2010). Evolving trees for the retrieval of mass spectrometry-based bacteria fingerprints. Knowledge and Information Systems, 25(2), 327-343. doi:10.1007/s10115-009-0249-4
PUB | DOI | WoS
 
[81]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992623
Zühlke, D., Schleif, F. - M., Geweniger, T., & Villmann, T. (2010). Learning vector quantization for heterogeneous structured data. Proceedings of the 18th European Symposium on Artificial Neural Networks (ESANN) 2010
PUB
 
[80]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994138
Villmann, T., Haase, S., Schleif, F. - M., Hammer, B., & Biehl, M. (2010). The Mathematics of Divergence Based Online Learning in Vector Quanitzation. In N. El Gayar & F. Schwenker (Eds.), ANNPR'2010 (pp. 108-119). Berlin, Heidelberg: Springer.
PUB
 
[79]
2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994227
Villmann, T., Schleif, F. - M., & Hammer, B. (2010). Sparse representation of data. In M. Verleysen (Ed.), ESANN'10 (pp. 225-234). D side.
PUB
 
[78]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993984
Schleif, F. - M., Villmann, T., Kostrzewa, M., Hammer, B., & Gammerman, A. (2009). Cancer Informatics by Prototype-networks in Mass Spectrometry. Artificial Intelligence in Medicine, 45(2-3), 215-228. doi:10.1016/j.artmed.2008.07.018
PUB | DOI | WoS | PubMed | Europe PMC
 
[77]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992551
Schleif, F. - M., & Villmann, T. (2009). 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, 509-516. Evere, Belgium: d-side publications.
PUB
 
[76]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992570
Simmuteit, S., Schleif, F. - M., Villmann, T., & Kostrzewa, M. (2009). Hierarchical PCA using Tree-SOM for the Identification of Bacteria. In J. C. Príncipe & R. Miikkulainen (Eds.), Advances in Self-Organizing Maps. Proceedings of the 7th International Workshop on Self Organizing Maps WSOM 2009. LNCS, 5629 (pp. 272-280). Berlin: Springer. doi:10.1007/978-3-642-02397-2
PUB | DOI
 
[75]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992575
Simmuteit, S., Simmuteit, J., Schleif, F. - M., & Villmann, T. (2009). Deconvolution and Identification of Mass Spectra from mixed and pure colonies of bacteria. In J. Blazewicz, K. Ecker, & B. Hammer (Eds.), IfI-09-12. ICOLE 2009 (pp. 104-112). Clausthal-Zellerfeld, Germany: Technical University of Clausthal.
PUB
 
[74]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992607
Villmann, T., & Schleif, F. - M. (2009). Functional Vector Quantization by Neural Maps. Proceedings of Whispers 2009. doi:10.1109/whispers.2009.5289064
PUB | DOI
 
[73]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1994067
Strickert, M., Schleif, F. - M., Villmann, T., & Seiffert, U. (2009). Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data. In M. Biehl, B. Hammer, M. Verleysen, & T. Villmann (Eds.), LNAI, 5400. Similarity-based Clustering (pp. 70-91). Berlin: Springer. doi:10.1007/978-3-642-01805-3_5
PUB | DOI
 
[72]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992547
Schleif, F. - M., Biehl, M., & Vellido, A. (2009). Advances in machine learning and computational intelligence. NeuroComputing, 72(7-9), 1377-1378. doi:10.1016/j.neucom.2008.12.013
PUB | DOI | WoS
 
[71]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992580
Strickert, M., Keilwagen, J., Schleif, F. - M., T. Villmann, T., & Biehl, M. (2009). Matrix metric adaptation for improved linear discriminant analysis of biomedical data. In J. Cabestany, F. Sandoval, A. Prieto, & J. M. Corchado (Eds.), Bio-Inspired Systems: Computational and Ambient Intelligence, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Proceedings. LNCS, 5517 (Vol. Part 1, pp. 933-940). Berlin: Springer. doi:10.1007/978-3-642-02478-8
PUB | DOI
 
[70]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992526
Schleif, F. - M., Villmann, T., & Ongyerth, M. (2009). Supervised data analysis and reliability estimation for spectral data. NeuroComputing, 72(16-18), 3590-3601. doi:10.1016/j.neucom.2008.12.040
PUB | DOI | WoS
 
[69]
2009 | Report | Veröffentlicht | PUB-ID: 1993316
Biehl, M., Hammer, B., Schleif, F. - M., Schneider, P., & Villmann, T. (2009). Stationarity of Matrix Relevance Learning Vector Quantization (Machine Learning Reports). Leipzig: Universität Leipzig.
PUB
 
[68]
2009 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992534
Schleif, F. - M., Riemer, T., Boerner, U., & Cross, M. (2009). Extended Targeted Profiling to Identify and Quantify Metabolites in 1-H NMR measurements. In J. Blazewicz, K. Ecker, & B. Hammer (Eds.), IfI-09-12. ICOLE 2009 (pp. 89-103). Clausthal-Zellerfeld, Germany: Technical University of Clausthal.
PUB
 
[67]
2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992565
Simmuteit, S., Schleif, F. - M., Villmann, T., & Elssner, T. (2009). Tanimoto metric in Tree-SOM for improved representation of mass spectrometry data with an underlying taxonomic structure. Proceedings of ICMLA 2009, 563--567. doi:10.1109/ICMLA.2009.111
PUB | DOI
 
[66]
2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992517
Schleif, F. - M., Lindemann, M., Maass, P., Diaz, M., Decker, J., Elssner, T., Kuhn, M., et al. (2009). Support Vector Classification of Proteomic Profile Spectra based on Feature Extraction with the Bi-orthogonal Discrete Wavelet Transform. Computing and Visualization in Science, 12(4), 189-199. doi:10.1007/s00791-008-0087-z
PUB | DOI
 
[65]
2008 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1993939
Schleif, F. - M., Villmann, T., & Hammer, B. (2008). Pattern Recognition by Supervised Relevance Neural Gas and its Application to Spectral Data in Bioinformatics. In J. R. -n R. -al Dopico, J. Dorado, & A. Pazos (Eds.), Encyclopedia of Artificial Intelligence (pp. 1337-1342). IGI Global.
PUB
 
[64]
2008 | Report | Veröffentlicht | PUB-ID: 1993379
Bunte, K., Schneider, P., Hammer, B., Schleif, F. - M., Villmann, T., & Biehl, M. (2008). Discriminative Visualization by Limited Rank Matrix Learning (Machine Learning Reports). Leipzig: Universität Leipzig.
PUB
 
[63]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992530
Schleif, F. - M., Ongyerth, M., & Villmann, T. (2008). Sparse coding Neural Gas for analysis of Nuclear Magnetic Resonance Spectroscopy. Proceedings of the CBMS 2008, 620-625. doi:10.1109/cbms.2008.39
PUB | DOI
 
[62]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992554
Schneider, P., Schleif, F. - M., Villmann, T., & Biehl, M. (2008). Generalized Matrix Learning Vector Quantizer for the Analysis of Spectral Data. In M. Verleysen (Ed.), Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN) 2008 (pp. 451-456). Evere, Belgium: d-side publications.
PUB
 
[61]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992597
Strickert, M., Schleif, F. - M., & Villmann, T. (2008). Metric adaptation for supervised attribute rating. In M. Verleysen (Ed.), Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN) 2008 (pp. 31-36). Evere, Belgium: d-side publications.
PUB
 
[60]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993966
Schleif, F. - M., Villmann, T., & Hammer, B. (2008). Prototype based Fuzzy Classification in Clinical Proteomics. International Journal of Approximate Reasoning, 47(1), 4-16. doi:10.1016/j.ijar.2007.03.005
PUB | DOI | WoS
 
[59]
2008 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1993900
Schleif, F. - M., Hammer, B., & Villmann, T. (2008). Analysis of Spectral Data in Clinical Proteomics by use of Learning Vector Quantizers. In M. Van de Werff, A. Delder, & R. Tollenaar (Eds.), Computational Intelligence in Biomedicine and Bioinformatics: Current Trends and Applications (pp. 141-167). Berlin: Springer. doi:10.1007/978-3-540-70778-3_6
PUB | DOI
 
[58]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992539
Schleif, F. - M., Riemer, T., Cross, M., & Villmann, T. (2008). Automatic Identification and Quantification of Metabolites in H-NMR Measurements. Proceedings of the Workshop on Computational Systems Biology (WCSB) 2008, 165-168
PUB
 
[57]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992589
Strickert, M., Schleif, F. - M., & Seiffert, U. (2008). Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data. Ibero-American Journal of Artificial Intelligence, 37(12), 37-44.
PUB
 
[56]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994253
Villmann, T., Schleif, F. - M., Kostrzewa, M., Walch, A., & Hammer, B. (2008). Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings in Bioinformatics, 9(2), 129-143. doi:10.1093/bib/bbn009
PUB | DOI | WoS | PubMed | Europe PMC
 
[55]
2008 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2017617
Villmann, T., Hammer, B., Schleif, F. - M., Hermann, W., & Cottrell, M. (2008). Fuzzy Classification Using Information Theoretic Learning Vector Quantization. Neurocomputing, 71(16-18), 3070-3076. doi:10.1016/j.neucom.2008.04.048
PUB | DOI | WoS
 
[54]
2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2001836
Geweniger, T., Schleif, F. - M., Hasenfuss, A., Hammer, B., & Villmann, T. (2008). Comparison of cluster algorithms for the analysis of text data using Kolmogorov complexity. In M. Köppen, N. K. Kasabov, & G. G. Coghill (Eds.), ICONIP 2008 (pp. 61-69). Berlin, Heidelberg: Springer. doi:10.1007/978-3-642-03040-6_8
PUB | DOI
 
[53]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994267
Villmann, T., Schleif, F. - M., Merenyi, E., Strickert, M., & Hammer, B. (2007). Class imaging of hyperspectral satellite remote sensing data using FLSOM. Proceedings of 6th International Workshop on Self-Organizing Maps Bielefeld: Bielefeld University. doi:10.2390/biecoll-wsom2007-110
PUB | DOI
 
[52]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994016
Schneider, P., Biehl, M., Schleif, F. - M., & Hammer, B. (2007). Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data. Proceedings of 6th International Workshop on Self-Organizing Maps Bielefeld: Bielefeld University. doi:10.2390/biecoll-wsom2007-135
PUB | DOI
 
[51]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993547
Hammer, B., Hasenfuss, A., Schleif, F. - M., Villmann, T., Strickert, M., & Seiffert, U. (2007). Intuitive Clustering of Biological Data. Proceedings of International Joint Conference on Neural Networks, 1877-1882. IEEE. doi:10.1109/IJCNN.2007.4371244
PUB | DOI
 
[50]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993852
Schleif, F. - M. (2007). Advances in pre-processing and model generation for mass spectrometric data analysis. In M. Biehl, B. Hammer, M. Verleysen, & T. Villmann (Eds.), Similarity-based Clustering and its Application to Medicine and Biology. Dagstuhl Seminar Proceedings Dagstuhl, Germany: Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany.
PUB
 
[49]
2007 | Report | Veröffentlicht | PUB-ID: 1993922
Schleif, F. - M., Hasenfuss, A., & Hammer, B. (2007). Aggregation of multiple peak lists by use of an improved neural gas network. Leipzig: Universität Leipzig.
PUB
 
[48]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992602
Strickert, M., Schleif, F. - M., Villmann, T., & Seiffert, U. (2007). Derivatives of Pearson Correlation for Gradient based Analysis of Biomedical Data. Similarity based Clustering. Lecture Notes in Artificial Intelligence, 5400. doi:10.4114/ia.v12i37.956
PUB | DOI
 
[47]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993970
Schleif, F. - M., Villmann, T., & Hammer, B. (2007). Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing-Maps. In F. Masulli, S. Mitra, & G. Pasi (Eds.), Application of Fuzzy Sets Theory. Proceedings of the 7th International Workshop on Fuzzy Logic and Applications. LNAI 4578 (pp. 563-570). Berlin, Heidelberg: Springer. doi:10.1007/978-3-540-73400-0_72
PUB | DOI
 
[46]
2007 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992509
Schleif, F. - M. (2007). Prototypen basiertes maschinelles Lernen in der klinischen Proteomik. In D. Wagner (Ed.), GI-Edition Lecture Notes in Informatics. Dissertation: Vol. 7. Ausgezeichnete Informatikdissertationen 2006 (pp. 179-188). Bonn: Gesellschaft für Informatik.
PUB
 
[45]
2007 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1993911
Schleif, F. - M., Hammer, B., & Villmann, T. (2007). Margin based Active Learning for LVQ Networks. Neurocomputing, 70(7-9), 1215-1224. doi:10.1016/j.neucom.2006.10.149
PUB | DOI | WoS
 
[44]
2007 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992507
Schleif, F. - M. (2007). Maschinelles Lernen mit Prototypmethoden in der klinischen Proteomik. KI - Künstliche Intelligenz(4), 65-67.
PUB
 
[43]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992610
Villmann, T., Schleif, F. - M., v.d.Werff, M., Deelder, A., & Tollenaar, R. (2007). Association learning in SOMs for Fuzzy-Classification. 6th International Conference on Machine Learning and Applications, 2007., 581-586. doi:10.1109/icmla.2007.29
PUB | DOI
 
[42]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992616
Villmann, T., Strickert, M., Brüß, C., Schleif, F. - M., & Seiffert, U. (2007). Visualization of fuzzy information in in fuzzy-classification for image sagmentation using MDS. In M. Verleysen (Ed.), Proceedings of the 15th European Symposium on Artificial Neural Networks (ESANN) 2007 (pp. 103-108). Evere, Belgium: d-side publications.
PUB
 
[41]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993811
Hasenfuss, A., Hammer, B., Schleif, F. - M., & Villmann, T. (2007). Neural gas clustering for dissimilarity data with continuous prototypes. In F. Sandoval, A. Prieto, J. Cabestany, & M. Grana (Eds.), Computational and Ambient Intelligence – Proceedings of the 9th Work-conference on Artificial Neural Networks. LNCS 4507 (pp. 539-546). Berlin: Springer. doi:10.1007/978-3-540-73007-1_66
PUB | DOI
 
[40]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992452
Deininger, S. - O., Gerhard, M., & Schleif, F. - M. (2007). Statistical Classification and Visualization of MALDI-Imaging Data. Proc. of CBMS 2007, 403-405
PUB
 
[39]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994258
Villmann, T., Schleif, F. - M., Merenyi, E., & Hammer, B. (2007). Fuzzy Labeled Self Organizing Map for Clasification of Spectra. In F. Sandoval, A. Prieto, J. Cabestany, & M. Grana (Eds.), Computational and Ambient Intelligence. Proceedings of the 9th Work-conference on Artificial Neural Networks. LNCS, 4507 (pp. 556-563). Berlin: Springer. doi:10.1007/978-3-540-73007-1_68
PUB | DOI
 
[38]
2007 | Report | Veröffentlicht | PUB-ID: 1992505
Schleif, F. - M. (2007). Preprocessing of Nuclear Magnetic Resonance Spectrometry Data (Machine Learning Reports). Leipzig: Universität Leipzig.
PUB
 
[37]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992586
Strickert, M., & Schleif, F. - M. (2007). Supervised Attribute Relevance Determination for Protein Identification in Stress Experiments. Proc. of MLSB 2007, 81-86
PUB
 
[36]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992593
Strickert, M., Schleif, F. - M., & Seiffert, U. (2007). Gradients of Pearson Correlation for Analysis of Biomedical Data. Proc. of ASAI 2007, 139-150
PUB
 
[35]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993820
Hasenfuss, A., Hammer, B., Schleif, F. - M., & Villmann, T. (2007). Neural gas clustering for sparse proximity data. In F. Sandoval, A. Prieto, J. Cabestany, & M. Grana (Eds.), Proceedings of the 9th International Work-Conference on Artificial Neural Networks.LNCS 4507 (pp. 539-546). Berlin, Heidelberg, Germany: Springer.
PUB
 
[34]
2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993907
Schleif, F. - M., Hammer, B., & Villmann, T. (2007). Supervised Neural Gas for Functional Data and its Application to the Analysis of Clinical Proteom Spectra. In F. Sandoval, A. Prieto, J. Cabestany, & M. Grana (Eds.), Computational and Ambient Intelligence. Proceedings of the 9th International Work-Conference on Artificial Neural Networks. LNCS, 4507 (pp. 1036-1044). Berlin, Heidelberg: Springer. doi:10.1007/978-3-540-73007-1_125
PUB | DOI
 
[33]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994184
Villmann, T., Hammer, B., Schleif, F. - M., Geweniger, T., Fischer, T., & Cottrell, M. (2006). Prototype based classification using information theoretic learning. In I. King, J. Wang, L. Chan, & D. L. L. Wang (Eds.), Lecture Notes in Computer Science, 4233: Vol. Part II. Neural Information Processing, 13th International Conference. Proceedings (pp. 40-49). Berlin: Springer.
PUB
 
[32]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994273
Villmann, T., Seiffert, U., Schleif, F. - M., Brüß, C., Geweniger, T., & Hammer, B. (2006). Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes. In F. Schwenker (Ed.), Proceedings of Conference Artificial Neural Networks in Pattern Recognition (pp. 46-56). Berlin: Springer. doi:10.1007/11829898_5
PUB | DOI
 
[31]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993578
Hammer, B., Hasenfuss, A., Schleif, F. - M., & Villmann, T. (2006). Supervised Batch Neural Gas. In F. Schwenker (Ed.), Proceedings of Conference Artificial Neural Networks in Pattern Recognition (ANNPR) (pp. 33-45). Berlin: Springer Verlag. doi:10.1007/11829898_4
PUB | DOI
 
[30]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993895
Schleif, F. - M., Hammer, B., & Villmann, T. (2006). Margin based Active Learning for LVQ Networks. In M. Verleysen (Ed.), Proc. Of European Symposium on Artificial Neural Networks (pp. 539-544). Brussels, Belgium: d-side publications.
PUB
 
[29]
2006 | Dissertation | PUB-ID: 1992511
Schleif, F. - M. (2006). Prototype based Machine Learning for Clinical Proteomics. Clausthal-Zellerfeld, Germany: Technical University Clausthal.
PUB
 
[28]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993889
Schleif, F. - M., Elssner, T., Kostrzewa, M., Villmann, T., & Hammer, B. (2006). Machine Learning and Soft-Computing in Bioinformatics. A Short Journey. Proc. of FLINS 2006, 541-548. World Scientific Press.
PUB
 
[27]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994237
Villmann, T., Schleif, F. - M., & Hammer, B. (2006). Comparison of relevance learning vector quantization with other metric adaptive classification methods. Neural Networks, 19(5), 610-622. doi:10.1016/j.neunet.2005.07.013
PUB | DOI | WoS | PubMed | Europe PMC
 
[26]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993568
Hammer, B., Hasenfuss, A., Schleif, F. - M., & Villmann, T. (2006). Supervised median neural gas. In C. Dagli, A. Buczak, D. Enke, A. Embrechts, & O. Ersoy (Eds.), Smart Engineering System Design. Intelligent Engineering Systems Through Artificial Neural Networks, 16 (pp. 623-633). ASME Press.
PUB
 
[25]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993594
Hammer, B., Hasenfuss, A., Schleif, F. - M., & Villmann, T. (2006). Supervised median clustering. In C. H. Dagli (Ed.), ASME Press series on intelligent engineering systems through artificial neural networks, 16. 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) (pp. 623-632). New York, NY: ASME Press.
PUB
 
[24]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993878
Schleif, F. - M., Elssner, T., Kostrzewa, M., Villmann, T., & Hammer, B. (2006). Analysis and Visualization of Proteomic Data by Fuzzy labeled Self-Organizing Maps. In D. J. Lee, B. Nutter, S. Antani, S. Mitra, & J. Archibald (Eds.), 19th IEEE International Symposium on Computer- based Medical Systems (pp. 919-924). Los Alamitos: IEEE Computer Society Press. doi:10.1109/cbms.2006.44
PUB | DOI
 
[23]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992445
Brüß, C., Bollenbeck, F., Schleif, F. - M., Weschke, W., Villmann, T., & Seiffert, U. (2006). Fuzzy Image Segmentation with Fuzzy Labelled Neural Gas. Proc. of ESANN 2006, 563-569
PUB
 
[22]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994195
Villmann, T., Hammer, B., Schleif, F. - M., Geweniger, T., & Herrmann, W. (2006). Fuzzy Classification by Fuzzy Labeled Neural Gas. Neural Networks, 19(6-7), 772-779. doi:10.1016/j.neunet.2006.05.026
PUB | DOI | WoS | PubMed | Europe PMC
 
[21]
2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1994241
Villmann, T., Schleif, F. - M., & Hammer, B. (2006). Prototype-based fuzzy classification with local relevance for proteomics. Neurocomputing, 69(16-18), 2425-2428. doi:10.1016/j.neucom.2006.02.003
PUB | DOI | WoS
 
[20]
2006 | Report | Veröffentlicht | PUB-ID: 1993584
Hammer, B., Hasenfuss, A., Schleif, F. - M., & Villmann, T. (2006). Supervised median clustering (IfI Technical reports). Clausthal-Zellerfeld: Clausthal University of Technology.
PUB
 
[19]
2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2017225
Hammer, B., Villmann, T., Schleif, F. - M., Albani, C., & Hermann, W. (2006). Learning vector quantization classification with local relevance determination for medical data. In L. Rutkowski, R. Tadeusiewicz, L. A. Zadeh, & J. Zurada (Eds.), Artificial Intelligence and Soft-Computing - Proceedings of ICAISC 2006. LNAI, 4029 (pp. 603-612). Berlin, Heidelberg: Springer. doi:10.1007/11785231_63
PUB | DOI
 
[18]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994172
Villmann, T., Hammer, B., Schleif, F. - M., & Geweniger, T. (2005). Fuzzy Labeled Neural GAS for Fuzzy Classification. In M. Cottrell (Ed.), Proceedings of the 5th Workshop on Self-Organizing Maps [on CD-ROM] (pp. 283-290). Paris, France: University Paris-1-Pantheon-Sorbonne.
PUB
 
[17]
2005 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992513
Schleif, F. - M. (2005). Plugins mit wxWidgets. Offene Systeme, 2005(1), 5-10.
PUB
 
[16]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994219
Villmann, T., Schleif, F. - M., & Hammer, B. (2005). Fuzzy Classification for Classification of Mass Spectrometric Data Based on Learning Vector Quantization. International Workshop on Integrative Bioinformatics
PUB
 
[15]
2005 | Report | Veröffentlicht | PUB-ID: 1993675
Hammer, B., Schleif, F. - M., & Villmann, T. (2005). On the Generalization Ability of Prototype-Based Classifiers with Local Relevance Determination (IfI Technical reports). Clausthal-Zellerfeld: Clausthal University of Technology.
PUB
 
[14]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994249
Villmann, T., Schleif, F. - M., & Hammer, B. (2005). Fuzzy labeled soft nearest neighbor classification with relevance learning. In M. A. Wani, K. J. Cios, & K. Hafeez (Eds.), Proceedings of the International Conference of Machine Learning Applications (pp. 11-15). Los Angeles: IEEE Press.
PUB
 
[13]
2005 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993974
Schleif, F. - M., Villmann, T., & Hammer, B. (2005). Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data. In I. Bloch, A. Petrosino, & A. G. B. Tettamanzi (Eds.), Proceedings of the 6th Workshop on Fuzzy Logic and Applications (pp. 290-296). Berlin, Heidelberg: Springer. doi:10.1007/11676935_36
PUB | DOI
 
[12]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994168
Villmann, T., Hammer, B., & Schleif, F. - M. (2004). Metrik Adaptation for Optimal Feature Classification in Learning Vector Quantization Applied to Environment Detection. In H. - M. Groß, K. Debes, & H. - J. Böhme (Eds.), Proceedings of Selbstorganisation Von Adaptivem Verfahren. Fortschritts-Berichte VDI Reihe 10, Nr. 742 (pp. 592-597). VDI Verlag.
PUB
 
[11]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994212
Villmann, T., Schleif, F. - M., & Hammer, B. (2004). Metric adaptation for optimal feature classification in learning vector quantization applied to environment detection. In H. - M. Groß, K. Debes, & H. - J. Böhme (Eds.), SOAVE 2004, 3rd Workshop on SelfOrganization of AdaptiVE Behavior VDI Verlag.
PUB
 
[10]
2004 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993870
Schleif, F. - M., Clauss, U., Villmann, T., & Hammer, B. (2004). Supervised Relevance Neural Gas and Unified Maximum Separability Analysis for Classification of Mass Spectrometric Data. In M. A. Wani, K. J. Cios, & K. Hafeez (Eds.), Proceedings of the 3rd International Conference on Machine Learning and Applications (ICMLA) 2004 (pp. 374-379). Los Alamitos, CA, USA: IEEE Press.
PUB
 
[9]
2003 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994223
Villmann, T., Schleif, F. - M., & Hammer, B. (2003). Supervised Neural Gas and Relevance Learning in Learning Vector Quantization. In T. Yamakawa (Ed.), Proceedings of the 4th Workshop on Self Organizing Maps [on CD-ROM] (pp. 47-52). Hibikino, Kitakyushu, Japan: Kyushu Institute of Technology.
PUB
 
[8]
2003 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992477
Köhler, M., Buchta, K., Schleif, F. - M., & Sommerfeld, E. (2003). A mission for the EEG coherence analysis: Is the task complex or difficult? Brain Topography, 15(4), 271.
PUB
 
[7]
2003 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992456
Dörfler, T., Simmel, A., Schleif, F. - M., & Sommerfeld, E. (2003). Working memory load and EEG coherence. Brain Topography, 15(4), 269.
PUB
 
[6]
2003 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992466
Gruhn, V., Hülder, M., Ijoui, R., & Schleif, F. - M. (2003). A distributed logistic support communication system. In H. Linger, J. Fisher, W. G. Wojtkowski, J. Zupancic, K. Vigo, & J. Arnold (Eds.), Proceedings of ISD 2003 - Constructing the Infrastructure for the Knowledge Economy - Methods and Tools, Theory and Practice (pp. 705-713). London: Kluwer Academic Publishers.
PUB
 
[5]
2002 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992544
Schleif, F. - M., & Stamer, H. (2002). {LaTeX} im studentischen Alltag. Gaotenblatt, 3-10.
PUB
 
[4]
2002 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992483
Köhler, M., Buchta, K., Schleif, F. - M., & Sommerfeld, E. (2002). Complexity and difficulty in memory based comparison. In J. A. da Silva, N. P. R. Filho, & E. H. Matsushima (Eds.), Proceedings of the 18th Meeting of the International Society for Psychophysics (pp. 433-439). Pabst Publishing.
PUB
 
[3]
2002 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992515
Schleif, F. - M. (2002). OCR mit statistischen Momenten. Gaotenblatt, 2002, 15-17.
PUB
 
[2]
2001 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992560
Simmel, A., Dörfler, T., Schleif, F. - M., & Sommerfeld, E. (2001). 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, 602-607
PUB
 
[1]
2001 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992461
Dörfler, T., Simmel, A., Schleif, F. - M., & Sommerfeld, E. (2001). Complexity - dependent synchronization of brain subsystems during memorization. Proceedings of the 17th Meeting of the International Society for Psychophysics, 343-348
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