PUB - Publikationen an der Universität Bielefeld

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• [48]
  

  2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2671047

  Gisbrecht, A., Schulz, A., & Hammer, B., 2015. Parametric nonlinear dimensionality reduction using kernel t-SNE. Neurocomputing, 147, p 71-82.

  PUB | PDF | DOI | WoS
   
• [47]
  

  2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2909226

  Gisbrecht, A., & Hammer, B., 2015. Data visualization by nonlinear dimensionality reduction. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 5(2), p 51-73.

  PUB | DOI | WoS
   
• [46]
  

  2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2766822

  Schulz, A., Gisbrecht, A., & Hammer, B., 2015. Using Discriminative Dimensionality Reduction to Visualize Classifiers. Neural Processing Letters, 42(1), p 27-54.

  PUB | PDF | DOI | WoS
   
• [45]
  

  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. Similarity-Based Pattern Recognition. Similarity-Based Pattern Recognition : Third International Workshop, SIMBAD 2015, Proceedings. Lecture Notes in Computer Science. no.9370 Cham: Springer International Publishing, pp. 160-170.

  PUB | DOI
   
• [44]
  

  2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2772422

  Gisbrecht, A., & Schleif, F.-M., 2015. Metric and non-metric proximity transformations at linear costs. Neurocomputing, 167, p 643-657.

  PUB | DOI | WoS
   
• [43]
  

  2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2695196

  Hofmann, D., Gisbrecht, A., & Hammer, B., 2015. Efficient approximations of robust soft learning vector quantization for non-vectorial data. Neurocomputing, 147, p 96-106.

  PUB | DOI | WoS
   
• [42]
  

  2015 | Bielefelder E-Dissertation | PUB-ID: 2722974

  Gisbrecht, A., 2015. Advances in dissimilarity-based data visualisation, Bielefeld: Universitätsbibliothek Bielefeld.

  PUB | PDF
   
• [41]
  

  2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2673557

  Schulz, A., Gisbrecht, A., & Hammer, B., 2014. Relevance learning for dimensionality reduction. In M. Verleysen, ed. ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium: i6doc.com, pp. 165-170.

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• [40]
  

  2014 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2900324

  Gisbrecht, A., Schulz, A., & Hammer, B., 2014. Discriminative Dimensionality Reduction for the Visualization of Classifiers. In Pattern Recognition Applications and Methods. Advances in Intelligent Systems and Computing. no.318 Cham: Springer Science + Business Media, pp. 39-56.

  PUB | DOI
   
• [39]
  

  2013 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982102

  Hofmann, D., Gisbrecht, A., & Hammer, B., 2013. Efficient Approximations of Kernel Robust Soft LVQ. In P. A. Estévez, J. C. Príncipe, & P. Zegers, eds. Advances in Self-Organizing Maps. Advances in Intelligent Systems and Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 183-192.

  PUB | DOI
   
• [38]
  

  2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2623500

  Gisbrecht, A., et al., 2013. Nonlinear dimensionality reduction for cluster identification in metagenomic samples. In E. Banissi, ed. 17th International Conference on Information Visualisation IV 2013. Piscataway, NJ: IEEE, pp. 174-179.

  PUB | DOI
   
• [37]
  

  2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622454

  Hammer, B., Gisbrecht, A., & Schulz, A., 2013. Applications of discriminative dimensionality reduction. In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods. SCITEPRESS, pp. 33-41.

  PUB | DOI
   
• [36]
  

  2013 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2612736

  Mokbel, B., et al., 2013. Visualizing the quality of dimensionality reduction. Neurocomputing, 112, p 109-123.

  PUB | DOI | WoS
   
• [35]
  

  2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622456

  Schulz, A., Gisbrecht, A., & Hammer, B., 2013. Using Nonlinear Dimensionality Reduction to Visualize Classifiers. In I. Rojas, G. Joya, & J. Gabestany, eds. Advances in computational intelligence. Proceedings. Vol 1. Lecture Notes in Computer Science. no.7902 Springer, pp. 59-68.

  PUB | DOI | WoS
   
• [34]
  

  2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622467

  Schulz, A., Gisbrecht, A., & Hammer, B., 2013. Classifier inspection based on different discriminative dimensionality reductions. In Workshop NC^2 2013. TR Machine Learning Reports, pp. 77-86.

  PUB
   
• [33]
  

  2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625194

  Gisbrecht, A., et al., 2013. Visualizing Dependencies of Spectral Features using Mutual Information. In ESANN, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. pp. 573-578.

  PUB
   
• [32]
  

  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, pp. 59-74.

  PUB | DOI
   
• [31]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982108

  Gisbrecht, A., Mokbel, B., & Hammer, B., 2012. Linear basis-function t-SNE for fast nonlinear dimensionality reduction. In The 2012 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 1-8.

  PUB | DOI
   
• [30]
  

  2012 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982106

  Gisbrecht, A., Hofmann, D., & Hammer, B., 2012. Discriminative Dimensionality Reduction Mappings. In J. Hollmén, F. Klawonn, & A. Tucker, eds. Advances in Intelligent Data Analysis XI. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 126-138.

  PUB | DOI
   
• [29]
  

  2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2625232

  Gisbrecht, A., et al., 2012. Linear Time Relational Prototype Based Learning. International Journal of Neural Systems, 22(05): 1250021.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [28]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622449

  Schulz, A., et al., 2012. How to visualize a classifier? In Proceedings of the Workshop - New Challenges in Neural Computation 2012. Machine Learning Reports, pp. 73-83.

  PUB
   
• [27]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625260

  Gisbrecht, A., et al., 2012. Out-of-sample kernel extensions for nonparametric dimensionality reduction. In ESANN 2012. pp. 531-536.

  PUB
   
• [26]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625265

  Gisbrecht, A., et al., 2012. Relevance learning for time series inspection. In M. Verleysen, ed. ESANN 2012. pp. 489-494.

  PUB
   
• [25]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2671172

  Hofmann, D., Gisbrecht, A., & Hammer, B., 2012. Discriminative probabilistic prototype based models in kernel space. In Workshop NC^2 2012. TR Machine Learning Reports.

  PUB
   
• [24]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625238

  Hofmann, D., Gisbrecht, A., & Hammer, B., 2012. Efficient Approximations of Kernel Robust Soft LVQ. In WSOM.

  PUB
   
• [23]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625276

  Gisbrecht, A., Mokbel, B., & Hammer, B., 2012. Linear Basis-Function t-SNE for Fast Nonlinear Dimensionality Reduction. In IJCNN.

  PUB
   
• [22]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622453

  Hammer, B., Gisbrecht, A., & Schulz, A., 2012. How to Visualize Large Data Sets? Presented at the Workshop Advances in Self-Organizing Maps (WSOM), Santiago, Chile.

  PUB | DOI
   
• [21]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2625247

  Gisbrecht, A., Hofmann, D., & Hammer, B., 2012. Discriminative Dimensionality Reduction Mappings. In J. Hollmén, F. Klawonn, & A. Tucker, eds. Advances in Intelligent Data Analysis XI - 11th International Symposium, IDA 2012, Helsinki, Finland, October 25-27, 2012. Proceedings. Lecture Notes in Computer Science. no.7619 Springer, pp. 126-138.

  PUB
   
• [20]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2615750

  Schleif, F.-M., et al., 2012. Fast approximated relational and kernel clustering. In Proceedings of ICPR 2012. IEEE, pp. 1229-1232.

  PUB
   
• [19]
  

  2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2534877

  Schleif, F.-M., et al., 2012. Learning Relevant Time Points for Time-Series Data in the Life Sciences. In ICANN (2). Lecture Notes in Computer Science. no.7553 Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 531-539.

  PUB | DOI
   
• [18]
  

  2012 | Konferenzbeitrag | PUB-ID: 2909356

  Mokbel, B., et al., 2012. Visualizing the quality of dimensionality reduction. In M. Verleysen, ed. ESANN 2012. pp. 179--184.

  PUB
   
• [17]
  

  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 IEEE Computational Intelligence Society & Institute of Electrical and Electronics Engineers, eds. IJCNN. Piscataway, NJ: IEEE, pp. 1-8.

  PUB | DOI
   
• [16]
  

  2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2509852

  Zhu, X., et al., 2012. Approximation techniques for clustering dissimilarity data. Neurocomputing, 90, p 72-84.

  PUB | DOI | WoS
   
• [15]
  

  2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982113

  Hammer, B., et al., 2011. Topographic Mapping of Dissimilarity Data. In J. Laaksonen & T. Honkela, eds. Advances in Self-Organizing Maps. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 1-15.

  PUB | DOI
   
• [14]
  

  2011 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982110

  Schleif, F.-M., Gisbrecht, A., & Hammer, B., 2011. Accelerating Kernel Neural Gas. In T. Honkela, et al., eds. Artificial Neural Networks and Machine Learning – ICANN 2011. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 150-158.

  PUB | DOI
   
• [13]
  

  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
   
• [12]
  

  2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276480

  Gisbrecht, A., et al., 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. no.6936 Berlin, Heidelberg: Springer, pp. 25-33.

  PUB | DOI
   
• [11]
  

  2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276485

  Hammer, B., et al., 2011. Topographic Mapping of Dissimilarity Data. In WSOM'11.

  PUB
   
• [10]
  

  2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276492

  Schleif, F.-M., Gisbrecht, A., & Hammer, B., 2011. Accelerating Kernel Neural Gas. In S. Kaski, et al., eds. ICANN'2011.

  PUB
   
• [9]
  

  2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2276531

  Gisbrecht, A., Mokbel, B., & Hammer, B., 2011. Relational Generative Topographic Mapping. Neurocomputing, 74(9), p 1359-1371.

  PUB | DOI | WoS
   
• [8]
  

  2011 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276522

  Gisbrecht, A., et al., 2011. Accelerating dissimilarity clustering for biomedical data analysis. In IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. pp. pp.154-161.

  PUB
   
• [7]
  

  2011 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2276540

  Gisbrecht, A., & Hammer, B., 2011. Relevance learning in generative topographic mapping. Neurocomputing, 74(9), p 1351-1358.

  PUB | DOI | WoS
   
• [6]
  

  2010 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982117

  Gisbrecht, A., et al., 2010. Visualizing Dissimilarity Data Using Generative Topographic Mapping. In R. Dillmann, et al., eds. KI 2010: Advances in Artificial Intelligence. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 227-237.

  PUB | DOI
   
• [5]
  

  2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276543

  Gisbrecht, A., Mokbel, B., & Hammer, B., 2010. The Nystrom approximation for relational generative topographic mappings. In NIPS workshop on challenges of Data Visualization.

  PUB
   
• [4]
  

  2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2276547

  Mokbel, B., Gisbrecht, A., & Hammer, B., 2010. On the effect of clustering on quality assessment measures for dimensionality reduction. In NIPS workshop on Challenges of Data Visualization.

  PUB
   
• [3]
  

  2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993448

  Gisbrecht, A., & Hammer, B., 2010. Relevance learning in generative topographic maps. In M. Verleysen, ed. ESANN'10. Evere: D side, pp. 387-392.

  PUB
   
• [2]
  

  2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993452

  Gisbrecht, A., Mokbel, B., & Hammer, B., 2010. Relational Generative Topographic Map. In M. Verleysen, ed. ESANN'10. Evere: D side, pp. 277-282.

  PUB
   
• [1]
  

  2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1993457

  Gisbrecht, A., et al., 2010. Visualizing Dissimilarity Data using generative topographic mapping. In R. Dillmann, et al., eds. KI'2010. pp. 227-237.

  PUB