Frank-Michael Schleif

fschleif@techfak.uni-bielefeld.de
ORCID logo https://orcid.org/0000-0002-7539-1283

PEVZ-ID
19373284

133 Publikationen

Alle markieren

  • [133]
    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.
    PUB | DOI | WoS
     
  • [132]
    2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2710031 OA
    Mokbel B, Paaßen B, Schleif F-M, Hammer B (2015)
    Metric learning for sequences in relational LVQ.
    Neurocomputing 169(SI): 306-322.
    PUB | PDF | DOI | Download (ext.) | WoS
     
  • [131]
    2015 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2910885
    Schleif F-M, Gisbrecht A, Tino P (2015)
    Large Scale Indefinite Kernel Fisher Discriminant.
    In: Similarity-Based Pattern Recognition. Similarity-Based Pattern Recognition : Third International Workshop, SIMBAD 2015, Proceedings. Feragen A, Pelillo M, Loog M (Eds); Lecture Notes in Computer Science, 9370. Cham: Springer International Publishing: 160-170.
    PUB | DOI
     
  • [130]
    2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2910619
    Schleif F-M, Villmann T, Zhu X (2015)
    High Dimensional Matrix Relevance Learning.
    In: 2014 IEEE International Conference on Data Mining Workshop. Piscataway, NJ: IEEE.
    PUB | DOI
     
  • [129]
    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.
    PUB | DOI | WoS
     
  • [128]
    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.
    PUB | DOI | Download (ext.) | WoS
     
  • [127]
    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 Letters 49: 138-145.
    PUB | DOI | WoS
     
  • [126]
    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.
    PUB | DOI | WoS
     
  • [125]
    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.
    PUB | DOI | WoS
     
  • [124]
    2013 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982105
    Schleif F-M, Zhu X, Hammer B (2013)
    Sparse Prototype Representation by Core Sets.
    In: Intelligent Data Engineering and Automated Learning – IDEAL 2013. Yin H, Tang K, Gao Y, Klawonn F, Lee M, Weise T, Li B, Yao X (Eds); Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg: 302-309.
    PUB | DOI
     
  • [123]
    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.
    PUB | DOI | WoS
     
  • [122]
    2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625202
    Schleif F-M, Zhu X, Hammer B (2013)
    Sparse prototype representation by core sets.
    In: IDEAL 2013. Hujun Yin et.al (Ed);.
    PUB
     
  • [121]
    2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615717
    Zhu X, Schleif F-M, Hammer B (2013)
    Secure Semi-supervised Vector Quantization for Dissimilarity Data.
    In: IWANN (1). Rojas I, Joya G, Cabestany J (Eds); Lecture Notes in Computer Science, 7902. Springer: 347-356.
    PUB | DOI
     
  • [120]
    2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615724
    Schleif F-M, Gisbrecht A (2013)
    Data Analysis of (Non-)Metric Proximities at Linear Costs.
    In: Proceedings of SIMBAD 2013. Berlin, Heidelberg: Springer: 59-74.
    PUB | DOI
     
  • [119]
    2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615701
    Zhu X, Schleif F-M, Hammer B (2013)
    Semi-Supervised Vector Quantization for proximity data.
    In: Proceedings of ESANN 2013. 89-94.
    PUB
     
  • [118]
    2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2625232
    Gisbrecht A, Mokbel B, Schleif F-M, Zhu X, Hammer B (2012)
    Linear Time Relational Prototype Based Learning.
    International Journal of Neural Systems 22(05): 1250021.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [117]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615745
    Bunte K, Schleif F-M, Biehl M (2012)
    Adaptive Learning for complex-valued data.
    In: Proceedings of ESANN 2012. 387-392.
    PUB
     
  • [116]
    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.
    In: IJCNN. IEEE Computational Intelligence Society, Institute of Electrical and Electronics Engineers (Eds); Piscataway, NJ: IEEE: 1-8.
    PUB | DOI
     
  • [115]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615750
    Schleif F-M, Zhu X, Gisbrecht A, Hammer B (2012)
    Fast approximated relational and kernel clustering.
    In: Proceedings of ICPR 2012. IEEE: 1229-1232.
    PUB
     
  • [114]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615756
    Schleif F-M, Zhu X, Hammer B (2012)
    Soft Competitive Learning for large data sets.
    In: Proceedings of MCSD 2012. Berlin, Heidelberg: Springer Berlin Heidelberg: 141-151.
    PUB | DOI
     
  • [113]
    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.
    In: ICANN (2). Lecture Notes in Computer Science, 7553. Berlin, Heidelberg: Springer Berlin Heidelberg: 531-539.
    PUB | DOI
     
  • [112]
    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.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [111]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534888
    Schleif F-M, Zhu X, Hammer B (2012)
    A Conformal Classifier for Dissimilarity Data.
    In: AIAI (2). Berlin, Heidelberg: Springer Berlin Heidelberg: 234-243.
    PUB | DOI
     
  • [110]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534910
    Zhu X, Schleif F-M, Hammer B (2012)
    Patch Processing for Relational Learning Vector Quantization.
    In: ISNN (1). Berlin, Heidelberg: Springer Berlin Heidelberg: 55-63.
    PUB | DOI
     
  • [109]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534868
    Hammer B, Mokbel B, Schleif F-M, Zhu X (2012)
    White Box Classification of Dissimilarity Data.
    In: HAIS (1). Berlin, Heidelberg: Springer Berlin Heidelberg: 309-321.
    PUB | DOI | WoS
     
  • [108]
    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.
    In: IJCNN. IEEE Computational Intelligence Society, Institute of Electrical and Electronics Engineers (Eds); Piscataway, NJ: IEEE: 1-8.
    PUB | DOI
     
  • [107]
    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.
    PUB | DOI | WoS
     
  • [106]
    2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982113
    Hammer B, Gisbrecht A, Hasenfuss A, Mokbel B, Schleif F-M, Zhu X (2011)
    Topographic Mapping of Dissimilarity Data.
    In: Advances in Self-Organizing Maps. Laaksonen J, Honkela T (Eds); Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg: 1-15.
    PUB | DOI
     
  • [105]
    2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982112
    Hammer B, Schleif F-M, Zhu X (2011)
    Relational Extensions of Learning Vector Quantization.
    In: Neural Information Processing. Lu B-L, Zhang L, Kwok J (Eds); Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg: 481-489.
    PUB | DOI
     
  • [104]
    2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982111
    Hammer B, Mokbel B, Schleif F-M, Zhu X (2011)
    Prototype-Based Classification of Dissimilarity Data.
    In: Advances in Intelligent Data Analysis X. Gama J, Bradley E, Hollmén J (Eds); Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg: 185-197.
    PUB | DOI
     
  • [103]
    2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982110
    Schleif F-M, Gisbrecht A, Hammer B (2011)
    Accelerating Kernel Neural Gas.
    In: Artificial Neural Networks and Machine Learning – ICANN 2011. Honkela T, Duch W, Girolami M, Kaski S (Eds); Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg: 150-158.
    PUB | DOI
     
  • [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.
    In: 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. Berlin, Heidelberg: Springer: 25-33.
    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.
    In: WSOM'11. .
    PUB
     
  • [99]
    2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276492
    Schleif F-M, Gisbrecht A, Hammer B (2011)
    Accelerating Kernel Neural Gas.
    In: ICANN'2011. Kaski S, Honkela T, Gitolami M, Dutch W (Eds);.
    PUB
     
  • [98]
    2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276644
    Seiffert U, Schleif F-M, Zühlke D (2011)
    Recent Trends in Computational Intelligence in Life Science.
    In: 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.
    In: Proceedings of ESANN 2011. Ciaco - i6doc.com: 29-34.
    PUB
     
  • [96]
    2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2290045
    Lee JA, Schleif F-M, Martinetz T (2011)
    Advances in artificial neural networks, machine learning, and computational intelligence.
    Neurocomputing 74(9): 1299-1300.
    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.
    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.
    In: 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.
    In: Proceedings of IJCNN 2011. accepted.
    PUB
     
  • [92]
    2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992489
    Mwebaze E, Schneider P, Schleif F-M, Aduwo JR, Quinn JA, Haase S, Villmann T, Biehl M (2011)
    Divergence based classification in Learning Vector Quantization.
    Neurocomputing 74(9): 1429-1435.
    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.
    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.
    In: 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.
    In: 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.
    In: 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: Artificial Intelligence and Soft Computing. Lecture Notes in Computer Science, 6113. Rutkowski L, Scherer R, Tadeusiewicz R, Zadeh L, Zurada J (Eds); Berlin, Heidelberg: Springer: 479-486.
    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.
    In: 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.
    In: Proceedings of WCSB 2010. 91-94.
    PUB
     
  • [84]
    2010 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1992441
    Angulo C, Lee JA, Schleif F-M (2010)
    Advances in computational intelligence and learning.
    NeuroComputing 73(7-9): 1049-1050.
    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: Intelligent Data Engineering and Automated Learning – IDEAL 2010 11th International Conference, Paisley, UK, September 1-3, 2010. Proceedings. Fyfe C, Tino P, Charles D, Garcia-Osorio C, Yin H (Eds); Berlin u.a.: Springer: 21-28.
    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.
    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.
    In: Proceedings of the 18th European Symposium on Artificial Neural Networks (ESANN) 2010. Evere, Belgium: d-side publications.
    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: ANNPR'2010. El Gayar N, Schwenker F (Eds); Berlin, Heidelberg: Springer: 108-119.
    PUB
     
  • [79]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994227
    Villmann T, Schleif F-M, Hammer B (2010)
    Sparse representation of data.
    In: ESANN'10. Verleysen M (Ed); D side: 225-234.
    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.
    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.
    In: Proceedings of the ESANN 2009. European Symposium on Artificial Neural Networks. Advances in Computational Intelligence and Learning. Evere, Belgium: d-side publications: 509-516.
    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: Advances in Self-Organizing Maps. Proceedings of the 7th International Workshop on Self Organizing Maps WSOM 2009. LNCS, 5629. Príncipe JC, Miikkulainen R (Eds); Berlin: Springer: 272-280.
    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: ICOLE 2009. Blazewicz J, Ecker K, Hammer B (Eds); IfI-09-12, Clausthal-Zellerfeld, Germany: Technical University of Clausthal: 104-112.
    PUB
     
  • [74]
    2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992607
    Villmann T, Schleif F-M (2009)
    Functional Vector Quantization by Neural Maps.
    In: Proceedings of Whispers 2009. Institute of Electrical and Electronics Engineers (Ed); Piscataway, NJ: IEEE: 636.
    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: Similarity-based Clustering. Biehl M, Hammer B, Verleysen M, Villmann T (Eds); LNAI, 5400, Berlin: Springer: 70-91.
    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.
    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: Bio-Inspired Systems: Computational and Ambient Intelligence, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Proceedings. LNCS, 5517. Cabestany J, Sandoval F, Prieto A, Corchado JM (Eds);Part 1. Berlin: Springer: 933-940.
    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.
    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: ICOLE 2009. Blazewicz J, Ecker K, Hammer B (Eds); IfI-09-12, Clausthal-Zellerfeld, Germany: Technical University of Clausthal: 89-103.
    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.
    In: Proceedings of ICMLA 2009. IEEE Press: 563--567.
    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 (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.
    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: Encyclopedia of Artificial Intelligence. Dopico JR-n R-al, Dorado J, Pazos A (Eds); IGI Global: 1337-1342.
    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.
    In: Proceedings of the CBMS 2008. IEEE: 620-625.
    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: Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN) 2008. Verleysen M (Ed); Evere, Belgium: d-side publications: 451-456.
    PUB
     
  • [61]
    2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992597
    Strickert M, Schleif F-M, Villmann T (2008)
    Metric adaptation for supervised attribute rating.
    In: Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN) 2008. Verleysen M (Ed); Evere, Belgium: d-side publications: 31-36.
    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.
    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: Computational Intelligence in Biomedicine and Bioinformatics: Current Trends and Applications. Van de Werff M, Delder A, Tollenaar R (Eds); Berlin: Springer: 141-167.
    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.
    In: 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.
    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.
    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: ICONIP 2008. Köppen M, Kasabov NK, Coghill GG (Eds); Berlin, Heidelberg: Springer: 61-69.
    PUB | DOI
     
  • [53]
    2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994016 OA
    Schneider P, Biehl M, Schleif F-M, Hammer B (2007)
    Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data.
    In: Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007). Bielefeld: Bielefeld University.
    PUB | PDF | DOI
     
  • [52]
    2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1994267 OA
    Villmann T, Schleif F-M, Merenyi E, Strickert M, Hammer B (2007)
    Class imaging of hyperspectral satellite remote sensing data using FLSOM.
    In: Proceedings of 6th International Workshop on Self-Organizing Maps (WSOM 2007). Bielefeld: Bielefeld University.
    PUB | PDF | 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.
    In: Proceedings of International Joint Conference on Neural Networks. IEEE: 1877-1882.
    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: Similarity-based Clustering and its Application to Medicine and Biology. Dagstuhl Seminar Proceedings. Biehl M, Hammer B, Verleysen M, Villmann T (Eds); 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.
    In: Similarity based Clustering. Lecture Notes in Artificial Intelligence, 5400. 12. IBERAMIA: Sociedad Iberoamericana de Inteligencia Artificial.
    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: Application of Fuzzy Sets Theory. Proceedings of the 7th International Workshop on Fuzzy Logic and Applications. LNAI 4578. Masulli F, Mitra S, Pasi G (Eds); Berlin, Heidelberg: Springer: 563-570.
    PUB | DOI
     
  • [46]
    2007 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 1992509
    Schleif F-M (2007)
    Prototypen basiertes maschinelles Lernen in der klinischen Proteomik.
    In: Ausgezeichnete Informatikdissertationen 2006. Wagner D (Ed); GI-Edition Lecture Notes in Informatics. Dissertation, 7. Bonn: Gesellschaft für Informatik: 179-188.
    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.
    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.
    In: 6th International Conference on Machine Learning and Applications, 2007. 581-586.
    PUB | DOI
     
  • [42]
    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: Computational and Ambient Intelligence – Proceedings of the 9th Work-conference on Artificial Neural Networks. LNCS 4507. Sandoval F, Prieto A, Cabestany J, Grana M (Eds); Berlin: Springer: 539-546.
    PUB | DOI
     
  • [41]
    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: Proceedings of the 15th European Symposium on Artificial Neural Networks (ESANN) 2007. Verleysen M (Ed); Evere, Belgium: d-side publications: 103-108.
    PUB
     
  • [40]
    2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992452
    Deininger S-O, Gerhard M, Schleif F-M (2007)
    Statistical Classification and Visualization of MALDI-Imaging Data.
    In: 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: Computational and Ambient Intelligence. Proceedings of the 9th Work-conference on Artificial Neural Networks. LNCS, 4507. Sandoval F, Prieto A, Cabestany J, Grana M (Eds); Berlin: Springer: 556-563.
    PUB | DOI
     
  • [38]
    2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993820
    Hasenfuss A, Hammer B, Schleif F-M, Villmann T (2007)
    Neural gas clustering for sparse proximity data.
    In: Proceedings of the 9th International Work-Conference on Artificial Neural Networks.LNCS 4507. Sandoval F, Prieto A, Cabestany J, Grana M (Eds); Berlin, Heidelberg, Germany: Springer: 539-546.
    PUB
     
  • [37]
    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: Computational and Ambient Intelligence. Proceedings of the 9th International Work-Conference on Artificial Neural Networks. LNCS, 4507. Sandoval F, Prieto A, Cabestany J, Grana M (Eds); Berlin, Heidelberg: Springer: 1036-1044.
    PUB | DOI
     
  • [36]
    2007 | Report | Veröffentlicht | PUB-ID: 1992505
    Schleif F-M (2007)
    Preprocessing of Nuclear Magnetic Resonance Spectrometry Data. Machine Learning Reports.
    Leipzig: Universität Leipzig.
    PUB
     
  • [35]
    2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992586
    Strickert M, Schleif F-M (2007)
    Supervised Attribute Relevance Determination for Protein Identification in Stress Experiments.
    In: Proc. of MLSB 2007. 81-86.
    PUB
     
  • [34]
    2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1992593
    Strickert M, Schleif F-M, Seiffert U (2007)
    Gradients of Pearson Correlation for Analysis of Biomedical Data.
    In: Proc. of ASAI 2007. 139-150.
    PUB
     
  • [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: Neural Information Processing, 13th International Conference. Proceedings. King I, Wang J, Chan L, Wang DLL (Eds); Lecture Notes in Computer Science, 4233, Part II. Berlin: Springer: 40-49.
    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: Proceedings of Conference Artificial Neural Networks in Pattern Recognition. Schwenker F (Ed); Berlin: Springer: 46-56.
    PUB | DOI
     
  • [31]
    2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993578
    Hammer B, Hasenfuss A, Schleif F-M, Villmann T (2006)
    Supervised Batch Neural Gas.
    In: Proceedings of Conference Artificial Neural Networks in Pattern Recognition (ANNPR). Schwenker F (Ed); Berlin: Springer Verlag: 33-45.
    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: Proc. Of European Symposium on Artificial Neural Networks. Verleysen M (Ed); Brussels, Belgium: d-side publications: 539-544.
    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.
    In: Proc. of FLINS 2006. World Scientific Press: 541-548.
    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.
    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: Smart Engineering System Design. Intelligent Engineering Systems Through Artificial Neural Networks, 16. Dagli C, Buczak A, Enke D, Embrechts A, Ersoy O (Eds); ASME Press: 623-633.
    PUB
     
  • [25]
    2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993594
    Hammer B, Hasenfuss A, Schleif F-M, Villmann T (2006)
    Supervised median clustering.
    In: 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). Dagli CH (Ed); ASME Press series on intelligent engineering systems through artificial neural networks, 16, New York, NY: ASME Press: 623-632.
    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: 19th IEEE International Symposium on Computer- based Medical Systems. Lee DJ, Nutter B, Antani S, Mitra S, Archibald J (Eds); Los Alamitos: IEEE Computer Society Press: 919-924.
    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.
    In: 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.
    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.
    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: Artificial Intelligence and Soft-Computing - Proceedings of ICAISC 2006. LNAI, 4029. Rutkowski L, Tadeusiewicz R, Zadeh LA, Zurada J (Eds); Lecture notes in computer science ; 4029 : Lecture notes in artificial intelligence, 4029. Berlin, Heidelberg: Springer: 603-612.
    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: Proceedings of the 5th Workshop on Self-Organizing Maps [on CD-ROM]. Cottrell M (Ed); Paris, France: University Paris-1-Pantheon-Sorbonne: 283-290.
    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.
    In: 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: Proceedings of the International Conference of Machine Learning Applications. Wani MA, Cios KJ, Hafeez K (Eds); Los Angeles: IEEE Press: 11-15.
    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: Proceedings of the 6th Workshop on Fuzzy Logic and Applications. Bloch I, Petrosino A, Tettamanzi AGB (Eds); Berlin, Heidelberg: Springer: 290-296.
    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: Proceedings of Selbstorganisation Von Adaptivem Verfahren. Fortschritts-Berichte VDI Reihe 10, Nr. 742. Groß H-M, Debes K, Böhme H-J (Eds); VDI Verlag: 592-597.
    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: SOAVE 2004, 3rd Workshop on SelfOrganization of AdaptiVE Behavior. Groß H-M, Debes K, Böhme H-J (Eds); 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: Proceedings of the 3rd International Conference on Machine Learning and Applications (ICMLA) 2004. Wani MA, Cios KJ, Hafeez K (Eds); Los Alamitos, CA, USA: IEEE Press: 374-379.
    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: Proceedings of the 4th Workshop on Self Organizing Maps [on CD-ROM]. Yamakawa T (Ed); Hibikino, Kitakyushu, Japan: Kyushu Institute of Technology: 47-52.
    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: Proceedings of ISD 2003 - Constructing the Infrastructure for the Knowledge Economy - Methods and Tools, Theory and Practice. Linger H, Fisher J, Wojtkowski WG, Zupancic J, Vigo K, Arnold J (Eds); London: Kluwer Academic Publishers: 705-713.
    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: Proceedings of the 18th Meeting of the International Society for Psychophysics. da Silva JA, Filho NPR, Matsushima EH (Eds); Pabst Publishing: 433-439.
    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.
    In: Proceedings of the 17th Meeting of the International Society for Psychophysics. Pabst Publishing: 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.
    In: Proceedings of the 17th Meeting of the International Society for Psychophysics. Pabst Publishing: 343-348.
    PUB
     
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