Contact

Dr. Stefan Harmeling

Adresse: Spemannstr. 38
72076 Tübingen
Raum Nummer: 207
Fax: 07071 601 552

 

Bild von Harmeling, Stefan, Dr.

Stefan Harmeling

Position: Group Leader  Abteilung: 

News:





Primary research interest:

 

Machine learning

Current research focus:

Machine learning applied to computational imaging



Besides recent publications on computational imaging, please find below selected publications on

supervised learning, unsupervised learning, and reinforcement learning.




 

 

 

 

 

 

 

 

Research on computational imaging

Hirsch, M., S. Harmeling, S. Sra and B. Schölkopf: Online Multi-frame Blind Deconvolution with Super-resolution and Saturation Correction. Astronomy and Astrophysics xx, xx (accepted) (10 2010)
Abstract
Harmeling, S., M. Hirsch and B. Schölkopf: Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake. Proceedings of the Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010) (accepted) (12 2010)
Link
Harmeling, S., S. Sra, M. Hirsch and B. Schölkopf: Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction via Incremental EM. Proceedings of the 17th International Conference on Image Processing (ICIP 2010) (accepted) (09 2010)
Link
Hirsch, M., S. Sra, B. Schölkopf and S. Harmeling: Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution. Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), 607-614 (06 2010)
Abstract PDF Link DOI
Harmeling, S., M. Hirsch, S. Sra and B. Schölkopf: Online blind deconvolution for Astronomy. Proceedings of the First IEEE International Conference Computational Photography (ICCP 2009), 1-7 (04 2009)
Abstract PDF Link

code (mbd-0.0.tar)



 

 

 

 

 

 

 


 

 

Research on supervised learning

Bridle, S., S. T. Balan, M. Bethge, M. Gentile, S. Harmeling, C. Heymans, M. Hirsch, R. Hosseini, M. Jarvis, D. Kirk, T. Kitching, K. Kuijken, A. Lewis, S. Paulin-Henriksson, B. Schölkopf, M. Velander, L. Voigt, D. Witherick, A. Amara, G. Bernstein, F. Courbin, M. Gill and A. He: Results of the GREAT08 Challenge: An image analysis competition for cosmological lensing. Monthly Notices of the Royal Astronomical Society 405(3), 2044-2061 (07 2010)
Abstract Link DOI
Baehrens, D., T. Schroeter, S. Harmeling, M. Kawanabe, K. Hansen and K.-R. Müller: How to Explain Individual Classification Decisions. Journal of Machine Learning Research 11, 1803-1831 (06 2010)
Abstract PDF Link
Harmeling, S.: Inferring textual entailment with a probabilistically sound calculus. Natural Language Engineering 15(4), 459-477 (10 2009)
Abstract PDF Link DOI
Lampert, C. H., H. Nickisch and S. Harmeling: Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 951-958, IEEE Service Center, Piscataway, NJ, USA (06 2009)
Abstract PDF Link DOI



 

 

 

 

 

 

 

 

Research on unsupervised learning

Harmeling, S. and C. K. Williams: Greedy Learning of Binary Latent Trees. IEEE Transactions on Pattern Analysis and Machine Intelligence Epub ahead (in press) (09 2010)
Abstract Link DOI

code (ltt-1.4.tar)
Harmeling, S.: Exploring model selection techniques for nonlinear dimensionality reduction. Technical report No.(EDI-INF-RR-0960) (03 2007)
Abstract PDF Link

code (nldim-0.1.tar) (generates different types of swiss rolls, fishbowls, and much more)
Harmeling, S., G. Dornhege, D. Tax, F. Meinecke and K.-R. Müller: From outliers to prototypes: Ordering data. Neurocomputing 69(13-15), 1608-1618 (08 2006)

Abstract PDF Link DOI
Meinecke, F., S. Harmeling and K.-R. Müller: Inlier-based ICA with an application to superimposed images. International Journal of Imaging Systems and Technology 15(1), 48-55 (07 2005)
Abstract Link DOI

Meinecke, F., S. Harmeling and K.-R. Müller: Robust ICA for Super-Gaussian Sources. Independent Component Analysis and Blind Signal Separation: Fifth International Conference (ICA 2004), 217-224. (Eds.) Puntonet, C. G., A. Prieto, Springer, Berlin, Germany (10 2004)
Abstract DOI

code (ibica-0.1.tar)
Harmeling, S., F. Meinecke and K.-R. Müller: Injecting noise for analysing the stability of ICA components. Signal Processing 84(2), 255-266 (02 2004)
Abstract Link DOI

Harmeling, S., F. Meinecke and K.-R. Müller: Analysing ICA component by injection noise. Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), 149-154. (Eds.) Amari, S.-I., A. Cichocki, S. Makino, N. Murata (04 2003)
Abstract PDF Link

code (relica-0.1.tar)
Harmeling, S., A. Ziehe, M. Kawanabe and K.-R. Müller: Kernel-based nonlinear blind source separation. Neural Computation 15(5), 1089-1124 (05 2003)
Abstract PDF Link DOI

Harmeling, S., A. Ziehe, M. Kawanabe and K.-R. Müller: Kernel feature spaces and nonlinear blind source separation. Advances in Neural Information Processing Systems 14: Proceedings of the NIPS 2001 Conference, 761-768. (Eds.) Dietterich, T. G., S. Becker, Z. Ghahramani, MIT Press, Cambridge, MA, USA (09 2002)
Abstract PDF Link

Harmeling, S., A. Ziehe, M. Kawanabe, B. Blankertz and K.-R. Müller: Nonlinear blind source separation using kernel feature spaces. Proceedings of the Third International Workshop on Independent Component Analysis and Blind Signal Separation (ICA 2001), 102-107. (Eds.) Lee, T.-W., T.P. Jung, S. Makeig, T. J. Sejnowski (12 2001)
Abstract PDF

code (ktdsep-0.1.tar)



 

 

 

 

 

 

 

 

Research on reinforcement learning

Toussaint, M., A. Storkey and S. Harmeling: Expectation-Maximization methods for solving (PO)MDPs and optimal control problems. Inference and Learning in Dynamic Models, xx, Cambridge University Press, UK (in press) (2010)
PDF

Toussaint, M., S. Harmeling and A. Storkey: Probabilistic inference for solving (PO)MDPs. Technical report No.(934) (12 2006)
PDF



 

 

 

 

 

 

 

 

Miscellaneous code

Schölkopf/Smola/Müller's kernel principal component analysis (KPCA)
Matlab-Implemenation, for more information see Bernhard Schölkopf, Alexander Smola, Klaus-Robert Müller, Nonlinear component analysis as a kernel eigenvalue problem, Neural Computation 10, 5, 1299-1319, 1996.
code (kpca-0.1.tar)

Parra/Spence's blind source separation algorithm
Matlab-Implemenation
code (convbss-0.1.tar)

Genetic Algorithms applied to 3-SAT problems
C Programming Language
code (gasat-1.1.tar)

Edit (login required)

Präferenzen: 
Referenzen pro Seite: Jahr: Medium:

  
Zeige Zusammenfassung

Artikel (13):

Schütt HH, Harmeling S, Macke JH und Wichmann FA (Mai-2016) Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data Vision Research 122 105–123.
Kitching T, Amara A, Gill M, Harmeling S, Heymans C, Massey R, Rowe B, Schrabback T, Voigt L, Balan S, Bernstein G, Bethge M, Bridle S, Courbin F, Gentile M, Heavens A, Hirsch M, Hosseini R, Kiessling A, Kirk D, Kuijken K, Mandelbaum R, Moghaddam B, Nurbaeva G, Paulin-Henriksson S, Rassat A, Rhodes J, Schölkopf B, Shawe-Taylor J, Shmakova M, Taylor A, Velander M, van Waerbeke L, Witherick D und Wittman D (September-2011) Gravitational Lensing Accuracy Testing 2010 (GREAT10) Challenge Handbook Annals of Applied Statistics 5(3) 2231-2263.
pdf
Hirsch M, Harmeling S, Sra S und Schölkopf B (Juli-2011) Online Multi-frame Blind Deconvolution with Super-resolution and Saturation Correction Astronomy & Astrophysics 531(A9) 11 pages.
Harmeling S und Williams CK (Juni-2011) Greedy Learning of Binary Latent Trees IEEE Transactions on Pattern Analysis and Machine Intelligence 33(6) 1087-1097.
pdf
Bridle S, Balan ST, Bethge M, Gentile M, Harmeling S, Heymans C, Hirsch M, Hosseini R, Jarvis M, Kirk D, Kitching T, Kuijken K, Lewis A, Paulin-Henriksson S, Schölkopf B, Velander M, Voigt L, Witherick D, Amara A, Bernstein G, Courbin F, Gill M, Heavens A, Mandelbaum R, Massey R, Moghaddam B, Rassat A, Refregier A, Rhodes J, Schrabback T, Shawe-Taylor J, Shmakova M, van Waerbeke L und Wittman D (Juli-2010) Results of the GREAT08 Challenge: An image analysis competition for cosmological lensing Monthly Notices of the Royal Astronomical Society 405(3) 2044-2061.
Baehrens D, Schroeter T, Harmeling S, Kawanabe M, Hansen K und Müller K-R (Juni-2010) How to Explain Individual Classification Decisions Journal of Machine Learning Research 11 1803-1831.
pdf
Harmeling S (Oktober-2009) Inferring textual entailment with a probabilistically sound calculus Natural Language Engineering 15(4) 459-477.
pdf
Harmeling S, Dornhege G, Tax D, Meinecke F und Müller K-R (August-2006) From outliers to prototypes: Ordering data Neurocomputing 69(13-15) 1608-1618.
pdf
Meinecke F, Harmeling S und Müller K-R (Juli-2005) Inlier-based ICA with an application to superimposed images International Journal of Imaging Systems and Technology 15(1) 48-55.
Oja E, Harmeling S und Almeida L (Februar-2004) Independent component analysis and beyond Signal Processing 84(2) 215-216.
Harmeling S, Meinecke F und Müller K-R (Februar-2004) Injecting noise for analysing the stability of ICA components Signal Processing 84(2) 255-266.
Ziehe A, Kawanabe M, Harmeling S und Müller K-R (November-2003) Blind separation of post-nonlinear mixtures using linearizing transformations and temporal decorrelation Journal of Machine Learning Research 4(7-8) 1319-1338.
pdf
Harmeling S, Ziehe A, Kawanabe M und Müller K-R (Mai-2003) Kernel-based nonlinear blind source separation Neural Computation 15(5) 1089-1124.
pdf

Beiträge zu Tagungsbänden (21):

Köhler R, Hirsch M, Mohler B, Schölkopf B und Harmeling S (Oktober-2012) Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database In: Computer Vision – ECCV 2012, , 12th European Conference on Computer Vision, Springer, Berlin, Germany, 27-40, Series: Lecture Notes in Computer Science ; 7578.
Zscheischler J, Mahecha MD und Harmeling S (Juni-2012) Climate classifications: the value of unsupervised clustering, International Conference on Computational Science (ICCS 2012), Elsevier, Amsterdam, Netherlands, Procedia Computer Science, 9, 897–906.
Burger HC, Schuler CJ und Harmeling S (Juni-2012) Image denoising: Can plain Neural Networks compete with BM3D?, 25th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2012), IEEE, Piscataway, NJ, USA, 2392-2399.
Hirsch M, Schuler CJ, Harmeling S und Schölkopf B (November-2011) Fast removal of non-uniform camera shake, 13th IEEE International Conference on Computer Vision (ICCV 2011), IEEE, Piscataway, NJ, USA, 463-470.
Schuler CJ, Hirsch M, Harmeling S und Schölkopf B (November-2011) Non-stationary correction of optical aberrations, 13th IEEE International Conference on Computer Vision (ICCV 2011), IEEE, Piscataway, NJ, USA, 659-666.
Loktyushin A und Harmeling S (September-2011) Automatic foreground-background refocusing, 18th IEEE International Conference on Image Processing (ICIP 2011), IEEE, Piscataway, NJ, USA, 3445-3448.
Burger HC und Harmeling S (September-2011) Improving Denoising Algorithms via a Multi-scale Meta-procedure In: Pattern Recognition, , 33rd DAGM Symposium, Springer, Berlin, Germany, 206-215, Series: Lecture Notes in Computer Science ; 6835.
Harmeling S, Hirsch M und Schölkopf B (Juni-2011) Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake In: Advances in Neural Information Processing Systems 23, , Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010), Curran, Red Hook, NY, USA, 829-837.
pdf
Burger HC, Schölkopf B und Harmeling S (April-2011) Removing noise from astronomical images using a pixel-specific noise model, IEEE International Conference on Computational Photography (ICCP 2011), IEEE, Piscataway, NJ, USA, 1-8.
Harmeling S, Sra S, Hirsch M und Schölkopf B (September-2010) Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction via Incremental EM, 17th International Conference on Image Processing (ICIP 2010), IEEE, Piscataway, NJ, USA, 3313-3316.
pdf
Hirsch M, Sra S, Schölkopf B und Harmeling S (Juni-2010) Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution, Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), IEEE, Piscataway, NJ, USA, 607-614.
pdf
Lampert CH, Nickisch H und Harmeling S (Juni-2009) Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), IEEE Service Center, Piscataway, NJ, USA, 951-958.
pdf
Harmeling S, Hirsch M, Sra S und Schölkopf B (April-2009) Online blind deconvolution for astronomical imaging, First IEEE International Conference Computational Photography (ICCP 2009), IEEE, Piscataway, NJ, USA, 1-7.
pdf
Harmeling S (Juni-2007) An Extensible Probabilistic Transformation-based Approach to the Third Recognizing Textual Entailment Challenge, RTE '07 ACL-PASCAL Workshop on Textual Entailment and Paraphrasing (TextEntail 2007), Association for Computational Linguistics, Stroudsburg, PA, USA, 137-142.
Meinecke F, Harmeling S und Müller K-R (Oktober-2004) Robust ICA for Super-Gaussian Sources In: Independent Component Analysis and Blind Signal Separation, , Fifth International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2004), Springer, Berlin, Germany, 217-224, Series: Lecture Notes in Computer Science ; 3195.
Honkela A, Harmeling S, Lundqvist L und Valpola H (Oktober-2004) Using kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method In: Independent Component Analysis and Blind Signal Separation, , Fifth International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2004), Springer, Berlin, Germany, 790-797, Series: Lecture Notes in Computer Science ; 3195.
Harmeling S, Meinecke F und Müller K-R (April-2003) Analysing ICA component by injection noise, 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), Tokyo, Japan, 149-154.
pdf
Ziehe A, Kawanabe M, Harmeling S und Müller K-R (April-2003) Blind separation of post-nonlinear mixtures using gaussianizing transformations and temporal decorrelation, 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), Tokyo, Japan, 269-274.
pdf
Harmeling S, Ziehe A, Kawanabe M und Müller K-R (September-2002) Kernel feature spaces and nonlinear blind source separation In: Advances in Neural Information Processing Systems 14, , Fifteenth Annual Neural Information Processing Systems Conference (NIPS 2001), MIT Press, Cambridge, MA, USA, 761-768.
pdf
Harmeling S, Ziehe A, Kawanabe M, Blankertz B und Müller K-R (Dezember-2001) Nonlinear blind source separation using kernel feature spaces, Third International Workshop on Independent Component Analysis and Blind Signal Separation (ICA 2001), 102-107.
pdf
Ziehe A, Kawanabe M, Harmeling S und Müller K-R (Dezember-2001) Separation of post-nonlinear mixtures using ACE and temporal decorrelation, Third International Workshop on Independent Component Analysis and Blind Signal Separation (ICA 2001), 433-438.
pdf

Beiträge zu Büchern (1):

Harmeling S: Solving Satisfiability Problems with Genetic Algorithms, 206-213. In: Genetic Algorithms and Genetic Programming at Stanford 2000, (Ed) J. R. Koza, Stanford Bookstore, Stanford, CA, USA, (Juni-2000).
pdf

Technische Berichte (9):

Schuler CJ, Hirsch M, Harmeling S und Schölkopf B: Non-stationary Correction of Optical Aberrations, 1, Max Planck Institute for Intelligent Systems, Tübingen, Germany, (Mai-2011).
pdf
Harmeling S, Sra S, Hirsch M und Schölkopf B: An Incremental GEM Framework for Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction, 187, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (November-2009).
pdf
Hirsch M, Sra S, Schölkopf B und Harmeling S: Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution, 188, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (November-2009).
pdf
Harmeling S und Toussaint M: Bayesian Estimators for Robins-Ritov’s Problem, EDI-INF-RR-1189, School of Informatics, University of Edinburgh, (Oktober-2007).
pdf
Harmeling S: Exploring model selection techniques for nonlinear dimensionality reduction, EDI-INF-RR-0960, School of Informatics, University of Edinburgh, (März-2007).
pdf
Toussaint M, Harmeling S und Storkey A: Probabilistic inference for solving (PO)MDPs, 934, School of Informatics, University of Edinburgh, (Dezember-2006).
pdf
Jutten C, Karhunen J, Almeida L und Harmeling S: Technical report on Separation methods for nonlinear mixtures, D29, EU-Project BLISS, (Oktober-2003).
pdf
Harmeling S, Bünau P, Ziehe A und Pham D-T: Technical report on implementation of linear methods and validation on acoustic sources, EU-Project BLISS, (September-2003).
pdf
Harmeling S, Ziehe A, Kawanabe M und Müller K-R: Kernel-based nonlinear blind source separation, EU-Project BLISS, (Januar-2002).
default

Poster (3):

Schütt H, Harmeling S, Macke J und Wichmann F (September-2015): Psignifit 4: Pain-free Bayesian Inference for Psychometric Functions, 15th Annual Meeting of the Vision Sciences Society (VSS 2015), St. Pete Beach, FL, USA, Journal of Vision, 15(12) 474.
Schütt H, Harmeling S, Macke J und Wichmann F (August-2014): Pain-free bayesian inference for psychometric functions, 37th European Conference on Visual Perception (ECVP 2014), Beograd, Serbia, Perception, 43(ECVP Abstract Supplement) 162.
Schütt H, Harmeling S, Macke J und Wichmann F (August-2014): Pain-free Bayesian inference for psychometric functions, 2014 European Mathematical Psychology Group Meeting (EMPG), Tübingen, Germany.

Abschlussarbeiten (2):

Harmeling S: Independent component analysis and beyond, Universität Potsdam, Potsdam, (Oktober-2004). PhD thesis
pdf
Harmeling S: Eine beweistheoretische Anwendung der, Westfälische Wilhelms-Universität Münster, Münster, (Mai-1998). Diplom thesis
pdf

Vorträge (1):

Harmeling S (Dezember-11-2010) Invited Lecture: Efficient space-variant blind deconvolution, NIPS 2010 Workshop on Numerical Mathematics Challenges in Machine Learning (NUMML 2010), Whistler, BC, Canada.

Export als:
BibTeX, XML, pubman, Edoc, RTF
Last updated: Montag, 22.05.2017