Kerstin Bunte

Kerstin Bunte

Postdoctoral researcher

Office:

Room T-A326 in Computer Science Building,
Konemiehentie 2, Otaniemi campus area, Espoo

Postal Address:

Aalto University School of Science,
Department of Information and Computer Science,
P.O. Box 15400, FI-00076 Aalto, Finland

Consult my Google Scholar profile

Telephone:

+358 50 430 1880

Email:

firstname.lastname@aalto.fi

About Me

I am a postdoctoral researcher at Helsinki Institute for Information Technology HIIT, in the Statistical Machine Learning and Bioinformatics research group.
Current research in a nutshell (see publications for details)

Theory and application of machine learning
analysis, design and optimization of training algorithms
methods of feature selection, relevance learning, adaptive metrics
content based image retrieval
nonlinear dimension reduction
applications in, e.g. medical imaging and data analysis

Mini CV

since 01/2013	Postdoctoral fellow at the Aalto University
09/2011-12/2012	Postdoctoral fellow at the Bielefeld University
2011	PhD Thesis: Adaptive dissimilarity measures, dimension reduction and visualization
09/2009-03/2010	project at the University of Rochester United States National Center for Research Resources (NCRR), National Institutes of Health (NIH) and the NIH Roadmap for Medical Research, and the Center of Emerging and Innovative Sciences (CEIS), a NYSTAR-designated Center for Advanced Technology
2007-2011	PhD student at the University of Groningen
2006	Diplom in computer science (Bielefeld University Germany) Thesis: Interactive relevance-map based optimization of sonification (Interaktive relevanzkartenbasierte Optimierung der Sonifkation von Daten)
10/2001-09/2006	study of natural scientific computer science at the Bielefeld University in Germany

Further activities

07/2000-2007	Software engineer in the EDV-Organisation Päpenmöller gen. Peppmöller in the domain application server for individual business applications. Bielefeld, Germany.
01/1997-2007	Volunteerism in the German Life Saving Society (DLRG) in the domains training, education and organization

Selected Talks

Slides How to visualize a classifier?, presented at the Workshop New Challenges in Neural Computation in Graz, Austria, August 2012.
Poster Adaptive Matrices for Color Texture Classification, presented at 14th International Conference on Computer Analysis of Images and Patterns (CAIP), Seville, Spain, August 2011.
Slides Neighbor Embedding XOM for Dimension Reduction and Visualization, presented at the European Symposium on Artificial Neural Networks (ESANN) in Bruges, Belgium, April 2010.
Poster Nonlinear Dimension Reduction and Visualization of Labeled Data, presented at the 13th international Conference on Computer Analysis of Images and Patterns (CAIP) in Münster, Germany, 2009.

Publications [PDF]

2012

M. B. Huber, K. Bunte, M. B. Nagarajan, M. Biehl, L. A. Ray, and A. Wismüller, Texture feature ranking with relevance learning to classify interstitial lung disease patterns, Artificial Intelligence in Medicine, 2012, in press.
I. Giotis, K. Bunte, N. Petkov, and M. Biehl. Adaptive matrices and filters for color texture classification. Journal of Mathematical Imaging and Vision, accepted for publication 2012.
K. Bunte, S. Haase, M. Biehl, and T. Villmann, Stochastic neighbor embedding (SNE) for dimension reduction and visualization using arbitrary divergences, Neurocomputing, vol. 90, no. 1, pp. 23-45, 2012. More details
A. Schulz, A. Gisbrecht, K. Bunte, and B. Hammer, How to visualize a classifier? in New Challenges in Neural Computation (NC2), ser. Workshop of the GI-Fachgruppe Neuronale Netze and the German Neural Networks Society in connection to DAGM 2012, B. Hammer and T. Villmann, Eds. Graz, Austria: LNCS, August 2012.
G. Peters, K. Bunte, M. Strickert, M. Biehl, and T. Villmann, Visualization of processes in self-learning systems, in Proc. of the 3rd Workshop on Trustworthy Self-Organizing Systems (TSOS), ser. at the Tenth Annual Conference on Privacy, Security, and Trust, Paris, France, July 2012.
M. Biehl, K. Bunte, B. Hammer, F.-M. Schleif, P. Schneider, and T. Villmann, Large margin linear discriminative visualization by matrix relevance learning, in Proc. of the International Joint Conference on Neural Networks (IJCNN), D. E. Hussein Abbass and R. Sarker, Eds. Brisbane, Australia: IEEE, pp. 1873-1880, June 2012. More details
K. Bunte, M. Biehl, and B. Hammer, A general framework for dimensionality reducing data visualization using explicit mapping functions, Neural Computation, vol. 24, no. 3, pp. 771-804, 2012. More details
K. Bunte, F.-M. Schleif, and M. Biehl, Adaptive learning for complex-valued data, in Proc. of the 20th European Symposium on Artificial Neural Networks (ESANN), M. Verleysen, Ed., Bruges, Belgium, pp. 387-392, April 2012.
K. Bunte, P. Schneider, B. Hammer, F.-M. Schleif, T. Villmann, and M. Biehl, Limited rank matrix learning - discriminative dimension reduction and visualization, Neural Networks, vol. 26, no. 4, pp. 159-173, February 2012. More details

2011

Kerstin Bunte. Adaptive dissimilarity measures, dimension reduction and visualization. University of Groningen, Faculty of Mathematics and Natural Sciences, Groningen, The Netherlands, 2011. Doctoral dissertation. More details.
K. Bunte, M. Biehl, M. F. Jonkman, and N. Petkov, Learning effective color features for content based image retrieval in dermatology, Pattern Recognition, vol. 44, no. 9, pp. 1892-1902, September 2011. More details
K. Bunte, I. Giotis, N. Petkov, and M. Biehl, Adaptive matrices for color texture classification, in 14th International Conference on Computer Analysis of Images and Patterns (CAIP), ser. Lecture Notes in Computer Science, vol. 6855, Seville, Spain, pp. 489-497, August 2011. More details
B. Hammer, M. Biehl, K. Bunte, and B. Mokbel, A general framework for dimensionality reduction for large data sets, in Advances in Self-Organizing Maps, WSOM 2011, ser. Lecture Notes in Computer Science 6731, J. Laaksonen and T. Honkela, Eds. Springer, pp. 277-287, 2011. More details
K. Bunte, M. Biehl, and B. Hammer, Dimensionality reduction mappings, in IEEE Symposium Series in Computational Intelligence (SSCI) 2011: Computational Intelligence and Data Mining (CIDM), Paris, France, pp. 349-356, April 2011. More details
K. Bunte, F.-M. Schleif, S. Haase, and T. Villmann, 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), M. Verleysen, Ed., Bruges, Belgium, pp. 29-34, April 2011.
K. Bunte, M. Biehl, and B. Hammer, Supervised dimension reduction mappings, in Proc. of the 19th European Symposium on Artificial Neural Networks (ESANN), M. Verleysen, Ed., Bruges, Belgium, pp. 281-286, April 2011.
M. B. Huber, K. Bunte, M. B. Nagarajan, M. Biehl, L. A. Ray, and A. Wismüller, Texture feature selection with relevance learning to classify interstitial lung disease patterns, in SPIE Medical Imaging: Computer-Aided Diagnosis, R. M. S. M.D. and B. van Ginneken, Eds., vol. 7963:43, March 2011. More details
K. Bunte, B. Hammer, T. Villmann, M. Biehl, and A. Wismüller, Neighbor embedding XOM for dimension reduction and visualization, Neurocomputing, vol. 74, no. 9, pp. 1340-1350, 2011. More details
G. Papari, K. Bunte, and M. Biehl, Waypoint averaging and step size control in learning by gradient descent, Leipzig University, Tech. Rep. MLR-2011-06, 2011.

2010

B. Hammer, K. Bunte, and M. Biehl, Some steps towards a general principle for dimensionality reduction mappings, in Learning paradigms in dynamic environments, ser. Dagstuhl Seminar Proceedings, B. Hammer, P. Hitzler, W. Maas, and M. Toussaint, Eds., vol. 10302. Schloss Dagstuhl, Leibniz Zentrum für Informatik, p. 15, 2010.
P. Schneider, K. Bunte, B. Hammer, and M. Biehl, Regularization in matrix relevance learning, IEEE Transactions on Neural Networks, vol. 21, no. 5, pp. 831-840, May 2010. More details
K. Bunte, B. Hammer, T. Villmann, M. Biehl, and A. Wismüller, Exploratory observation machine (XOM) with kullback-leibler divergence for dimensionality reduction and visualization, in Proc. of the 18th European Symposium on Artificial Neural Networks (ESANN), M. Verleysen, Ed., Bruges, Belgium, pp. 87-92, April 2010.
PK. Bunte, B. Hammer, A. Wism ̈ller, and M. Biehl, Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data, Neurocomputing, vol. 73, no. 7-9, pp. 1074-1092, March 2010. More details
K. Bunte, S. Haase, M. Biehl, and T. Villmann, Mathematical Foundations of Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization, Leipzig University, Tech. Rep. MLR-03-2010, 2010.

2009

K. Bunte, B. Hammer, and M. Biehl, Nonlinear dimension reduction and visualization of labeled data, in 13th International Conference on Computer Analysis of Images and Patterns (CAIP), ser. Lecture Notes in Computer Science, X. Jiang and N. Petkov, Eds., vol. 5702. Münster, Germany: Springer, pp. 1162-1170, September 2009. More details
K. Bunte, M. Biehl, N. Petkov, and M. F. Jonkman, Adaptive metrics for content based image retrieval in dermatology, in Proc. of 17th European Symposium on Artificial Neural Networks (ESANN), M. Verleysen, Ed., Bruges, Belgium, pp. 129-134, April 2009.
K. Bunte, B. Hammer, P. Schneider, and M. Biehl, Nonlinear discriminative data visualization, in Proc. of 17th European Symposium on Artificial Neural Networks (ESANN), M. Verleysen, Ed., Bruges, Belgium, pp. 65-70, April 2009.

2008

K. Bunte, P. Schneider, B. Hammer, F.-M. Schleif, T. Villmann, and M. Biehl, Discriminative visualization by limited rank matrix learning, Leipzig University, Tech. Rep. MLR-03-2008, 2008.
P. Schneider, K. Bunte, B. Hammer, T. Villmann, and M. Biehl, Regularization in matrix relevance learning, Leipzig University, Tech. Rep. MLR-02-2008, 2008.

2007

T. Hermann, K. Bunte, and H. Ritter, Relevance-based interactive optimization of sonification, in Lecture Presentation at the 13th International Conference on Auditory Display (ICAD), Montréal, Canada, pp. 26-29, June 2007.