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1
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40949141347
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Automatic classification of the acrosome status of boar spermatozoa using digital image processing and LVQ
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Alegre, E., Biehl, M., Petkov, N., Sanchez, L.: Automatic classification of the acrosome status of boar spermatozoa using digital image processing and LVQ. Computers in Biology and Medicine 38, 461-468 (2008)
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Computers in Biology and Medicine
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Rademacher and Gaussian complexities: Risk bounds and structural risks
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3
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38449089802
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Analysis of Tiling Microarray Data by Learning Vector Quantization and Relevance Learning
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Yin, H, Tino, P, Corchado, E, Byrne, W, Yao, X, eds, IDEAL 2007, Springer, Heidelberg
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Biehl, M., Breitling, R., Li, Y.: Analysis of Tiling Microarray Data by Learning Vector Quantization and Relevance Learning. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds.) IDEAL 2007. LNCS, vol. 4881, pp. 880-889. Springer, Heidelberg (2007)
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LNCS
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Biehl, M.1
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4
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70350244915
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Statistical mechanics of on-line learning
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Biehl, M, Hammer, B, Verleysen, M, Villmann, T, eds, Springer, Heidelberg
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Biehl, M., Caticha, N., Riegler, P.: Statistical mechanics of on-line learning. In: Biehl, M., Hammer, B., Verleysen, M., Villmann, T. (eds.) Similarity-based clustering, biomedical applications, and beyond. Springer, Heidelberg (2009)
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Similarity-based clustering, biomedical applications, and beyond
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Biehl, M.1
Caticha, N.2
Riegler, P.3
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5
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33847216891
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Dynamics and generalization ability of LVQ algorithms
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Biehl, M., Gosh, A., Hammer, B.: Dynamics and generalization ability of LVQ algorithms. Journal of Machine Learning Research 8, 323-360 (2007)
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Journal of Machine Learning Research
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Biehl, M.1
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6
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70350241717
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Matrix Learning in Learning Vector Quantization
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Department of Computer Science, IfI-06-14
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Biehl, M., Hammer, B., Schneider, P.: Matrix Learning in Learning Vector Quantization, Technical Report Clausthal University of Technology, Department of Computer Science, IfI-06-14 (2006)
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Technical Report Clausthal University of Technology
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7
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56449089247
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Monitoring technical systems with prototype based clustering
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Verleysen, M, ed, D-side publications
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Bojer, T., Hammer, B., Koers, C.: Monitoring technical systems with prototype based clustering. In: Verleysen, M. (ed.) European Symposium on Artificial Neural Networks 2003, pp. 433-439. D-side publications (2003)
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Bojer, T.1
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8
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0002902870
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Relevance determination in learning vector quantization
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D facto publications
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Bojer, T., Hammer, B., Schunk, D., Tluk von Toschanowitz, K.: Relevance determination in learning vector quantization. In: Proc. of European Symposium on Artificial Neural Networks (ESANN 2001), pp. 271-276. D facto publications (2001)
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Bojer, T.1
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Tluk von Toschanowitz, K.4
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9
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70350241716
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submitted
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Bunte, K., Petkov, N., Bosman, H.H.W.J., Biehl, M., Jonkman, M.: Efficient color features for content based image retrieval in dermatolgoy (submitted, 2009)
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Efficient color features for content based image retrieval in dermatolgoy
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Bunte, K.1
Petkov, N.2
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Biehl, M.4
Jonkman, M.5
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10
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70350224023
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Bunte, K., Schneider, P., Hammer, B., Schleif, F.-M., Villmann, T., Biehl,M.: Discriminative visualization by limited rank matrix learning. Machine Learning Reports MLR-03-2008 (2008), http://www.uni-leipzig.de/ ~compint/mlr/mlr_03_2008.pdf, ISSN:1865-3960
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Bunte, K., Schneider, P., Hammer, B., Schleif, F.-M., Villmann, T., Biehl,M.: Discriminative visualization by limited rank matrix learning. Machine Learning Reports MLR-03-2008 (2008), http://www.uni-leipzig.de/ ~compint/mlr/mlr_03_2008.pdf, ISSN:1865-3960
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11
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85156210264
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Margin analysis of the LVQ algorithm
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Crammer, K., Gilad-Bachrach, R., Navot, A., Tishby, A.: Margin analysis of the LVQ algorithm. In: Advances of Neural Information Processing Systems (2002)
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Crammer, K.1
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12
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submitted
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Denecke, A., Wersing, H., Steil, J.J., Körner, E.: Robust object segmentation by adaptive metrics in Generalized LVQ (submitted, 2009)
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Robust object segmentation by adaptive metrics in Generalized LVQ
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Denecke, A.1
Wersing, H.2
Steil, J.J.3
Körner, E.4
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13
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Wiley, Chichester
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Duda, R.O., Hart, P.E., Storck, D.G.: Pattern Classification. Wiley, Chichester (2001)
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Pattern Classification
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Duda, R.O.1
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14
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Anisotropic noise injection for input variable relevance determination
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16
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On the generalization ability of GRLVQ networks
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Hammer, B., Strickert, M., Villmann, T.: On the generalization ability of GRLVQ networks. Neural Processing Letters 21(2), 109-120 (2005)
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Neural Processing Letters
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12844250052
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Supervised neural gas with general similarity measure
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Hammer, B., Strickert, M., Villmann, T.: Supervised neural gas with general similarity measure. Neural Processing Letters 21(1), 21-44 (2005)
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Neural Processing Letters
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0036791938
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Generalized relevance learning vector quantization
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Hammer, B., Villmann, T.: Generalized relevance learning vector quantization. Neural Networks 15, 1059-1068 (2002)
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Neural Networks
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Automated feature selection with distinction sensitive learning vector quantization
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Sato, A.S., Yamada, K.: An analysis of convergence in generalized LVQ. In: Niklasson, L., Boden, M., Ziemke, T. (eds.) ICANN 1998, pp. 172-176. Springer, Heidelberg (1998)
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Sato, A.S., Yamada, K.: An analysis of convergence in generalized LVQ. In: Niklasson, L., Boden, M., Ziemke, T. (eds.) ICANN 1998, pp. 172-176. Springer, Heidelberg (1998)
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42049122152
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Exploration of Mass-Spectrometric Data in Clinical Proteomics Using Learning Vector Quantization Methods
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Schleif, F.-M., Hammer, B., Kostrzewa,M., Villmann, T.: Exploration of Mass-Spectrometric Data in Clinical Proteomics Using Learning Vector Quantization Methods. Briefings in Bioinformatics 9(2), 129-143 (2007)
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Briefings in Bioinformatics
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70350214860
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Matrix adaptation in discriminative vector quantization
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Department of Computer Science, IfI-08-08
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Schneider, P., Biehl, M., Hammer, B.: Matrix adaptation in discriminative vector quantization. Technical Report Clausthal University of Technology, Department of Computer Science, IfI-08-08 (2008)
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Technical Report Clausthal University of Technology
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Regularization in matrix relevance learning
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Soft nearest prototype classification
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Generalized Relevance LVQ (GRLVQ) with Correlation Measures for Gene Expression Data
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Strickert, M., Seiffert, U., Sreenivasulu, N., Weschke, W., Villmann, T., Hammer, B.: Generalized Relevance LVQ (GRLVQ) with Correlation Measures for Gene Expression Data. Neurocomputing 69, 651-659 (2006)
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Neurocomputing
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Strickert, M.1
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0021518106
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A Theory of the Learnable
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0037379640
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Neural maps in remote sensing image analysis
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Villmann, T.,Merenyi, E., Hammer, B.: Neural maps in remote sensing image analysis. Neural Networks 16(3-4), 389-403 (2003)
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Neural Networks
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33745684650
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Comparison of Relevance Learning Vector Quantization with other Metric Adaptive Classification Methods
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Villmann, T., Schleif, F.-M., Hammer, B.: Comparison of Relevance Learning Vector Quantization with other Metric Adaptive Classification Methods. Neural Networks 19, 610-622 (2006)
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Neural Networks
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Distance metric learning for large margin nearest neighbor classification
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