K. (Kerstin) Bunte, PhD

Rosalind Franklin Fellow

Research

Research units:

Postal address:
Nijenborgh
9
Gebouw 5161, ruimte 0590
Groningen
Netherlands
Phone: +31 50 363 3966
  1. 2019
  2. Bakker, J., & Bunte, K. (2019). Efficient learning of email similarities for customer support. In M. Verleysen (Ed.), 27th European Symposium on Artificial Neural Networks, ESANN 2019 (pp. 119-124). d-side publishing.
  3. 2018
  4. Bunte, K., Smith, D. J., Chappell, M. J., Hassan-Smith, Z. K., Tomlinson, J. W., Arlt, W., & Tino, P. (2018). Learning pharmacokinetic models for in vivo glucocorticoid activation. Journal of Theoretical Biology, 455, 222-231. https://doi.org/10.1016/j.jtbi.2018.07.025
  5. Mohammadi, M., Peletier, R., Schleif, F-M., Petkov, N., & Bunte, K. (2018). Globular cluster detection in the Gaia survey. In 26th European Symposium on Artificial Neural Networks, ESANN 2018 d-side publishing.
  6. Biehl, M., Bunte, K., Longo, G., & Tino, P. (2018). Machine Learning and Data Analysis in Astroinformatics. In M. Verleysen (Ed.), ESANN, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (Vol. 26, pp. 307-314). Ciaco - i6doc.com.
  7. Mohammadi, M., Petkov, N., Peletier, R., Bibiloni Serrano, P., & Bunte, K. (2018). Detection of Globular Clusters in the Halo of Milky Way. In N. Petkov, N. Strisciuglio, & C. M. Travieso-González (Eds.), Frontiers in Artificial Intelligence and Applications (FAIA) ( Frontiers in Artificial Intelligence and Applications; Vol. 310). IOS Press. https://doi.org/10.3233/978-1-61499-419-0-27
  8. 2017
  9. Ghosh, S., Baranowski, E. S., van Veen, R., de Vries, G-J., Biehl, M., Arlt, W., ... Bunte, K. (2017). Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders. In M. Verleysen (Ed.), 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2017 (pp. 199-205). Ciaco - i6doc.com.
  10. 2016
  11. Bunte, K., Baranowski, E. S., Arlt, W., & Tino, P. (2016). Relevance Learning Vector Quantization in Variable Dimensional Spaces. In Workshop of the GI-Fachgruppe Neuronale Netze and the German Neural Networks Society in connection to GCPR 2016 (pp. 20-23). Hannover, Germany: LNCS.
  12. Bunte, K., Kaden, M., & Schleif, F-M. (2016). Low-Rank Kernel Space Representations in Prototype Learning. In E. Merenyi, M. J. Mendenhall, & P. O'Driscoll (Eds.), Advances in Self-Organizing Maps and Learning Vector Quantization: Proceedings of the 11th International Workshop WSOM (Vol. 428, pp. 341-353). ( Advances in Intelligent Systems and Computing ; Vol. 428). Houston, Texas, USA. https://doi.org/10.1007/978-3-319-28518-4_30
  13. Sieberts, S., Zhu, F., Garcia-Garcia, J., Stahl, E., Pratap, A., Pandey, G., ... Mangravite, L. (2016). Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis. Nature Communications, 7, [12460 (2016)]. https://doi.org/10.1038/ncomms12460
  14. 2014
  15. Bunte, K., Jaervisalo, M., Berg, J., Myllymaeki, P., Peltonen, J., & Kaski, S. (2014). Optimal neighborhood preserving visualization by maximum satisfiability. In C. E. Brodley, & P. Stone (Eds.), Proc. of the 28th Conference on Artificial Intelligence (AAAI) (pp. 1694-1700). Quebec, Canada: AAAI Press.
  16. 2013
  17. Strickert, M., & Bunte, K. (2013). Soft Rank Neighbor Embeddings. In Proc. of the 21th European Symposium on Artificial Neural Networks (ESANN) (pp. 77-82)
  18. 2012
  19. Bunte, K., Schleif, F-M., & Biehl, M. (2012). Adaptive learning for complex valued data. In M. Verleysen (Ed.), 20th European Symposium on Artificial Neural Networks, ESANN 2012 (pp. 387-392). d-side publishing.
  20. Schulz, A., Gisbrecht, A., Bunte, K., & Hammer, B. (2012). How to visualize a classifier? In Workshop of the GI-Fachgruppe Neuronale Netze and the German Neural Networks Society in connection to DAGM 2012 (pp. 73-83). Graz, Austria.
  21. Biehl, M., Bunte, K., Schleif, F-M., Schneider, P., & Villmann, T. (2012). Large Margin Linear Discriminative Visualization by Matrix Relevance Learning. In 2012 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) (IEEE International Joint Conference on Neural Networks (IJCNN)). NEW YORK: IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/IJCNN.2012.6252627
  22. Peters, G., Bunte, K., Strickert, M., Biehl, M., & Villmann, T. (2012). Visualization of Processes in Self-Learning Systems. In Privacy, Security and Trust (PST), 2012 Tenth Annual International Conference on (pp. 244-249). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/PST.2012.6297953
  23. 2011
  24. Hammer, B., Biehl, M., Bunte, K., & Mokbel, B. (2011). A general framework for dimensionality reduction for large data sets. In J. Laaksonen, & T. Honkela (Eds.), Advances in Self-Organizing Maps, Proc. 8th Intl. Workshop on Selforganizing Maps (WSOM 2011): WSOM 2011 (pp. 277-287). (Lecture Notes in Computer Science; Vol. 6731). Springer. https://doi.org/10.1007/978-3-642-21566-7_28
  25. Bunte, K., Giotis, I., Petkov, N., & Biehl, M. (2011). Adaptive Matrices for Color Texture Classification. In P. Real, D. DiazPernil, H. MolinaAbril, A. Berciano, & W. Kropatsch (Eds.), COMPUTER ANALYSIS OF IMAGES AND PATTERNS: 14TH INTERNATIONAL CONFERENCE, CAIP 2011, PT 2 (pp. 489-497). (Lecture Notes in Computer Science; Vol. 6855). BERLIN: Springer. https://doi.org/10.1007/978-3-642-23678-5_58
  26. Bunte, K., Biehl, M., & Hammer, B. (2011). Dimensionality Reduction Mappings. In Proc. IEEE Symp. on Computational Intelligence and Data Mining SSCI 2011 CDIM (pp. 349-356). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/CIDM.2011.5949443
  27. Bunte, K., Schleif, F. -M., Haase, S., & Villmann, T. (2011). Mathematical Foundations of the Self Organized Neighbor Embedding ({SONE}) for Dimension Reduction and Visualization. In Proc. of the 19th European Symposium on Artificial Neural Networks (ESANN) (pp. 29-34). Bruges, Belgium.
  28. Bunte, K., Biehl, M., & Hammer, B. (2011). Supervised dimension reduction mappings. In M. Verleysen (Ed.), 19th European Symposium on Artificial Neural Networks (ESANN 2011) (pp. 281-286). d-side publishing.
  29. Huber, M. B., Bunte, K., Nagajaran, M. B., Biehl, M., Ray, L. A., & [No Value], W. (2011). Texture feature selection with relevance learning to classify Interstitial lung disease patterns. In Medical Imaging 2011: Computer Aided Diagnostics (Vol. 7963 (43)). (SPIE Conference Proceedings). https://doi.org/10.1117/12.877894
  30. Papari, G., Bunte, K., & Biehl, M. (2011). Waypoint averaging and step size control in learning by gradient descent (technical report). In F-M. Schleif, & T. Villmann (Eds.), MIWOCI 2011, Mittweida Workshop on Computational Intelligence (Vol. MLR-2011-06, pp. 16-26). (Machine Learning Reports). Univ. of Bielefeld.
  31. 2010
  32. Bunte, K., Hammer, B., Villmann, T., Biehl, M., & Wismüller, A. (2010). Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization. In M. Verleysen (Ed.), 18th European Symposium on Artificial Neural Networks (ESANN 2010) (pp. 87-92). d-side publishing.
  33. Hammer, B., Bunte, K., & Biehl, M. (2010). Some steps towards a general principle for dimensionality reduction mappings. In B. Hammer, P. Hitzler, W. Maas, & M. Toussaint (Eds.), Learning paradigms in dynamic environments (Vol. 10302). (Dagstuhl Seminar Proceedings). Dagstuhl Research Online Publication Server.
  34. 2009
  35. Bunte, K., Biehl, M., Petkov, N., & Jonkman, M. F. (2009). Adaptive Metrics for Content Based Image Retrieval in Dermatology. In M. Verleysen (Ed.), 17th European Symposium on Artificial Neural Networks (ESANN 2009) (pp. 129-134). d-side publishing.
  36. Bunte, K., Hammer, B., & Biehl, M. (2009). Nonlinear Dimension Reduction and Visualization of Labeled Data. In Jiang, & N. Petkov (Eds.), COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS (pp. 1162-1170). (Lecture Notes in Computer Science; Vol. 5702). BERLIN: Springer. https://doi.org/10.1007/978-3-642-03767-2_141
  37. Bunte, K., Hammer, B., Schneider, P., & Biehl, M. (2009). Nonlinear Discriminative Data Visualization. In M. Verleysen (Ed.), 17th European Symposium on Artificial Neural Networks (ESANN 2009) (pp. 65-70). d-side publishing.
  38. 2008
  39. Bunte, K., Schneider, P., Hammer, B., Schleif, F. M., Villmann, T., & Biehl, M. (2008). Discriminative visualization by limited rank matrix learning.
  40. Schneider, P., Bunte, K., Stiekema, H., Hammer, B., Villmann, T., & Biehl, M. (2008). Regularization in Matrix Relevance Learning. University of Leipzig.
  41. 2007
  42. Hermann, T., Bunte, K., & Ritter, H. (2007). Relevance-based Interactive Optimization of Sonification. (13 ed.) Montreal, Canada: International Conference on Auditory Display (ICAD).

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