The Image Group – University of Copenhagen

The Image Group
Christian's Publications

Publications by Christian Igel

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Contributions to journals, books, and conferences

Coming soon

Jan Kremer, Kim Steenstrup Pedersen, and Christian Igel. Active Learning with Support Vector Machines. WIREs Data Mining and Knowledge Discovery, in press

2014

Asja Fischer and Christian Igel. Training Restricted Boltzmann Machines: An Introduction. Training Restricted Boltzmann Machines: An Introduction. Pattern Recognition 47, pp. 25-39, 2014
Fabian Gieseke, Justin Heinermann, Cosmin Oancea, and Christian Igel. Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs. JMLR W&CP 32 (ICML), pp. 172-180, 2014
Marc Schlipsing, Jan Salmen, Marc Philipp Tschentscher, and Christian Igel. Adaptive Pattern Recognition in Real-time Video-based Soccer Analysis. Journal of Real-Time Image Processing, 2014
Christian Igel. No Free Lunch Theorems: Limitations and Perspectives of Metaheuristics. In Y. Borenstein and A. Moraglio, eds.: Theory and Principled Methods for the Design of Metaheuristics, pp. 1-23, Springer-Verlag, 2014
Dídac R. Arbonès, Henrik G. Jensen, Annika Loft, Per Munck af Rosenschöld, Anders Elias Hansen, Christian Igel, and Sune Darkner. Automatic FDG-PET-based tumor and metastatic lymph node segmentation in cervical cancer. In: Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 903441, 2014
Fabian Gieseke, Kai Lars Polsterer, Cosmin E. Oancea, and Christian Igel. Speedy Greedy Feature Selection: Better Redshift Estimation via Massive Parallism. In M. Verleysen, ed.: 22th European Symposium on Artificial Neural Networks (ESANN 2014), pp. 87-92, Belgium: i6doc.com, 2014
Kai Lars Polsterer, Fabian Gieseke, Christian Igel, and Tomotsugu Goto. Improving the Performance of Photometric Regression Models via Massive Parallel Feature Selection. In N. Manset and P. Forshay, eds.: 23rd Annual Astronomical Data Analysis Software and Systems Conference (ADASS XXIII), ASP Conference Series 485, 2014

2013

Karl Bringmann, Tobias Friedrich, Christian Igel, and Thomas Voß. Speeding Up Many-Objective Optimization by Monte Carlo Approximations. Artificial Intelligence 204, pp. 22-29, 2013
Kai Brügge, Asja Fischer, and Christian Igel. The flip-the-state transition operator for restricted Boltzmann machines. Machine Learning 13, pp. 53-69, 2013
Fabian Gieseke, Christian Igel, and Tapio Pahikkala. Polynomial runtime bounds for fixed-rank unsupervised least-squares classification. JMLR W&CP 29 (ACML), pp. 62-71, 2013
Christian Igel. A Note on Generalization Loss When Evolving Adaptive Pattern Recognition Systems. IEEE Transactions on Evolutionary Computation 17(3), pp. 345-352, 2013
Oswin Krause, Asja Fischer, Tobias Glasmachers, and Christian Igel. Approximation properties of DBNs with binary hidden units and real-valued visible units. JMLR W&CP 28 (ICML), pp. 419–426, 2013
Joselene Marques, Christian Igel, Martin Lillholm, and Erik B. Dam. Linear feature selection in texture analysis. Machine Vision and Applications 24, pp. 1435-1444, 2013
Marc Schlipsing, Jan Salmen, and Christian Igel. Echtzeit-Videoanalyse im Fußball - Entwurf eines Live-Systems zum Spieler-Tracking. Künstliche Intelligenz 27(3), pp 235-240, 2013
Søren Dahlgaard, Christian Igel, and Mikkel Thorup. Nearest Neighbor Classification Using Bottom-k Sketches. IEEE International Conference on Big Data 2013, pp. 28-34, IEEE Press, 2013
Sebastian Houben, Johannes Stallkamp, Jan Salmen, Marc Schlipsing, and Christian Igel. Detection of Traffic Signs in Real-World Images: The German Traffic Sign Detection Benchmark. International Joint Conference on Neural Networks (IJCNN 2013), pp. 715-722, IEEE Press
Kim Steenstrup Pedersen, Kristoffer Stensbo-Smidt, Andrew Zirm, and Christian Igel. Shape Index Descriptors Applied to Texture-Based Galaxy Analysis. International Conference on Computer Vision (ICCV), pp 2440-2447, IEEE Press, 2013
Kristoffer Stensbo-Smidt, Christian Igel, Andrew Zirm, and Kim Steenstrup Pedersen. Nearest Neighbour Regression Outperforms Model-based Prediction of Specific Star Formation Rate. IEEE International Conference on Big Data 2013, pp. 141-144, IEEE Press, 2013
Adhish Prasoon, Kersten Petersen, Christian Igel, Francois Lauze, Erik Dam, and Mads Nielsen. Deep Feature Learning for Knee Cartilage Segmentation Using a Triplanar Convolutional Neural Network. In: Medical Image Computing and Computer Assisted Intervention (MICCAI 2013), LNCS 8150, pp 246-253, Springer-Verlag, 2013
Adhish Prasoon, Christian Igel, Marco Loog, Francois Lauze, Erik Dam, and Mads Nielsen. Femoral Cartilage Segmentation in Knee MRI Scans Using Two Stage Voxel Classification. In: 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 5469-5472, IEEE Press, 2012 note

2012

Johannes Stallkamp, Marc Schlipsing, Jan Salmen, and Christian Igel. Man vs. Computer: Benchmarking Machine Learning Algorithms for Traffic Sign Recognition. Neural Networks 32, pp. 323-332, 2012
Christian Igel. Learning ∈ Artificial Intelligence ∩ Cognitive Technologies ∩ Neural Computation ∩ ... Künstliche Intelligenz 26(3), pp. 209-212, 2012 (editorial)
Oliver Kramer, Christian Igel, and Günter Rudolph. Evolutionary Kernel Machines. Evolutionary Intelligence 5(3), pp. 151-152, 2012 (guest editorial)
Johannes Stallkamp, Marc Schlipsing, Jan Salmen, and Christian Igel. Introduction to the Special Issue on Machine Learning for Traffic Sign Recognition. IEEE Transactions on Transportation Systems 13(4), pp. 1481-1481, 2012 (guest editorial)
Matthias Tuma, Christian Igel, and Mark Prior. Hydroacoustic Signal Classification Using Support Vector Machines. In C. H. Chen, ed.: Signal and Image Processing for Remote Sensing, 2nd edition, pp. 37-56, CRC Press, 2012
Chen Chen, Lauge Sørensen, Francois Lauze, Christian Igel, Marco Loog, Aasa Feragen, Marleen de Bruijne, and Mads Nielsen. Towards exaggerated emphysema stereotypes. In: SPIE Medical Imaging 2012: Image Processing. Proceedings of SPIE 8315, 83150Q, 2012
Ürün Dogan, Tobias Glasmachers, and Christian Igel. A Note on Extending Generalization Bounds for Binary Large-margin Classifiers to Multiple Classes. In P. A. Flach, T. De Bie, and N. Cristianini, eds.: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2012), LNCS 7523, pp.122-129, Springer-Verlag, 2012
Asja Fischer and Christian Igel. An Introduction to Restricted Boltzmann Machines. In L. Alvarez, M. Mejail, L. Gomez, and J. Jacobo, eds.: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (CIARP 2012), LNCS 7441, pp. 14-36, Springer-Verlag, 2012
Adhish Prasoon, Christian Igel, Marco Loog, Francois Lauze, Erik Dam, and Mads Nielsen. Cascaded classifier for large-scale data applied to automatic segmentation of articular cartilage. In: SPIE Medical Imaging 2012: Image Processing. Proceedings of SPIE 8314, 83144V, 2012
Ürün Dogan, Tobias Glasmachers, and Christian Igel. Turning Binary Large-margin Bounds into Multi-class Bounds. In A. Gretton, Z. Harchaoui, and B. Sriperumbudur, organizers: ICML 2012 Workshop on RKHS and kernel-based methods, 2012

2011

Holger Blume, Bernd Bischl, Martin Botteck, Christian Igel, Rainer Martin, Günther Rötter, Günter Rudolph, Wolfgang Theimer, Igor Vatolkin, and Claus Weihs. Huge Music Archives on Mobile Devices. IEEE Signal Processing Magazine, 28(4), pp. 24-39, 2011
Asja Fischer and Christian Igel. Bounding the Bias of Contrastive Divergence Learning. Neural Computation 23, pp. 664-673, 2011
Chen Chen, Francois Lauze, Christian Igel, Aasa Feragen, Marco Loog, and Mads Nielsen. Towards exaggerated image stereotypes. In: Asian Conference on Pattern Recognition (ACPR 2011), pp. 422-426, IEEE Press, 2011
Asja Fischer and Christian Igel. Training RBMs Based on the Signs of the CD Approximation of the Log-likelihood Derivatives. In M. Verleysen, ed.: 19th European Symposium on Artificial Neural Networks (ESANN 2011), pp. 495-500, Belgium: d-side publications, 2011
Tobias Friedrich, Karl Bringmann, Thomas Voß, and Christian Igel. The Logarithmic Hypervolume Indicator. In H.G. Beyer and W. B. Langdon, eds.: Foundations of Genetic Algorithms (FOGA 2011), pp. 81-92, ACM Press, 2011
Verena Heidrich-Meisner and Christian Igel. Non-linearly Increasing Resampling in Racing Algorithms. In M. Verleysen, ed.: 19th European Symposium on Artificial Neural Networks (ESANN 2011), pp. 465-470, Belgium: d-side publications, 2011
Jan Salmen, Lukas Caup, and Christian Igel. Real-time Estimation of Optical Flow Based on Optimized Haar Wavelet Features. In R. H. C. Takahashi, K. Deb, E. F. Wanner and S. Greco, eds.: Sixth International Conference on Evolutionary Multi-Criterion Optimization (EMO 2011), LNCS 6576, pp. 448-461, Springer-Verlag, 2011
Johannes Stallkamp, Marc Schlipsing, Jan Salmen, and Christian Igel. The German Traffic Sign Recognition Benchmark: A Multi-class Classification Competition. International Joint Conference on Neural Networks (IJCNN 2011), pp. 1453-1460, IEEE Press
Matthias Tuma and Christian Igel. Improved Working Set Selection for LaRank. In A. Berciano et al., eds.: 14th International Conference on Computer Analysis of Images and Patterns (CAIP 2011), LNCS 6854, pp. 327-334, Springer-Verlag, 2011

2010

Tobias Glasmachers and Christian Igel. Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(8), pp. 1522-1528, 2010 source code
Jan Salmen, Marc Schlipsing, and Christian Igel. Efficient Update of the Covariance Matrix Inverse in Iterated Linear Discriminant Analysis. Pattern Recognition Letters 31(1), pp. 1903-1907, 2010
Valentin Markounikau, Christian Igel, Amiram Grinvald, and Dirk Jancke. Dynamic Neural Field Model of Mesoscopic Cortical Activity Captured with Voltage-sensitive Dye Imaging. PLoS Computational Biology 6(9), 2010
Benjamin Roeschies and Christian Igel. Structure Optimization of Reservoir Networks. Logic Journal of the IGPL 18(5), pp. 635-669, 2010
Rolf P. Würtz, Kirstie L. Bellman, Hartmut Schmeck, and Christian Igel. Special Issue on Organic Computing. ACM Transactions Autonomous and Adaptive Systems, (3), pp. 1-3, 2010 (guest editorial)
Christian Igel. Evolutionary Kernel Learning. In C. Sammut and G. I. Webb, eds.: Encyclopedia of Machine Learning, Springer-Verlag, 2010
Asja Fischer and Christian Igel. Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines. In K. Diamantaras, W. Duch, and L. S. Iliadis, eds.: International Conference on Artificial Neural Networks (ICANN 2010), LNCS 6354, pp. 208-217, Springer-Verlag, 2010
Asja Fischer and Christian Igel. Challenges in Training Restricted Boltzmann Machines. In B. Hammer and T. Villmann, eds.: New Challenges in Neural Computation (NC2), Machine Learning Reports 04/2010, pp. 11–24, 2010
Verena Heidrich-Meisner and Christian Igel. Direct policy search: Intrinsic versus extrinsic perturbations. In B. Hammer and T. Villmann, eds.: New Challenges in Neural Computation (NC2), Machine Learning Reports 04/2010, pp. 33–39, 2010
Matthias Tuma, Christian Igel, and Mark Prior. Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets. In: International Conference on Pattern Recognition (ICPR 2010), 2010
Thomas Voß, Heike Trautmann, and Christian Igel. New Uncertainty Handling Strategies in Multi-Objective Evolutionary Optimization. Parallel Problem Solving from Nature (PPSN XI), LNCS, Springer-Verlag, 2010
Thomas Voß, Tobias Friedrich, Karl Bringmann, and Christian Igel. Scaling Up Indicator-based MOEAs by Approximating the Least Hypervolume Contributor: A Preliminary Study. In N. Beume and D. Brockhoff, eds.: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010): Workshop on Theoretical Aspects of Evolutionary Multiobjective Optimization, pp. 1975-1978, ACM Press, 2010
Thomas Voß, Nikolaus Hansen, and Christian Igel. Improved Step Size Adaptation for the MO-CMA-ES. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010), pp. 487-494, ACM Press, 2010

2009

Verena Heidrich-Meisner and Christian Igel. Neuroevolution Strategies for Episodic Reinforcement Learning. Journal of Algorithms 64(4), pp. 152-168, 2009
Christian Igel. Service: Reinforcement Learning. Künstliche Intelligenz 09(3), p. 44, 2009
Christian Igel. Reinforcement Learning. Künstliche Intelligenz 09(3), p. 4, 2009 (guest editorial)
Julian Togelius, Tom Schaul, Daan Wierstra, Christian Igel, Faustino Gomez, and Jürgen Schmidhuber. Ontogenetic and Phylogenetic Reinforcement Learning. Künstliche Intelligenz 09(3), pp. 30-33, 2009
Susanne Winter, Ioannis Pechlivanis, Claudia Dekomien, Bernhard Brendel, Christian Igel, and Kirsten Schmieder. Toward Registration of 3D Ultrasound and CT Images of the Spine in Clinical Praxis: Design and Evaluation of a Data Acquisition Protocol. Ultrasound in Medicine and Biology 35(11), pp. 1773-1782, 2009, doi:10.1016/j.ultrasmedbio.2009.06.1089
Asja Fischer and Christian Igel. Contrastive Divergence Learning May Diverge When Training Restricted Boltzmann Machines. Frontiers in Computational Neuroscience. Conference Abstract: Bernstein Conference on Computational Neuroscience (BCCN 2009), 2009, doi:10.3389/conf.neuro.10.2009.14.121
Verena Heidrich-Meisner and Christian Igel. Hoeffding and Bernstein Races for Selecting Policies in Evolutionary Direct Policy Search. In L. Bottou and M. Littman, eds.: Proceedings of the International Conference on Machine Learning (ICML 2009), pp. 401-408, 2009
Verena Heidrich-Meisner and Christian Igel. Uncertainty Handling CMA-ES for Reinforcement Learning. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2009), pp. 1211-1218, ACM Press, 2009
Verena Heidrich-Meisner and Christian Igel. Variable-metric Evolution Strategies for Direct Policy Search. In: Multidisciplinary Symposium on Reinforcement Learning (MSRL 2009), 2009
Christian Igel and Tobias Glasmachers. Second-order SMO for SVM Online and Active Learning. In: 23rd European Conference on Operational Research (EURO 2009), 2009
Valentin Markounikau, Christian Igel, and Dirk Jancke. A Mesoscopic Model of VSD Dynamics Observed in Visual Cortex Induced by Flashed and Moving Stimuli. Frontiers in Computational Neuroscience. Conference Abstract: Bernstein Conference on Computational Neuroscience (BCCN 2009), 2009, doi: 10.3389/conf.neuro.10.2009.14.064
Matthias Tuma and Christian Igel. Kernel-based Machine Learning Techniques for Hydroacoustic Signal Classification. International Scientific Studies Conference (ISS 2009), 2009
Thomas Voß, Nikolaus Hansen, and Christian Igel. Recombination for Learning Strategy Parameters in the MO-CMA-ES. In M. Ehrgott, C. Fonseca, X. Gandibleux, J.-K. Hao, and M. Sevaux, eds.: Fifth International Conference on Evolutionary Multi-Criterion Optimization (EMO 2009), LNCS 5467, pp. 155-168, Springer-Verlag, 2009

2008

Tobias Glasmachers and Christian Igel. Second Order SMO Improves SVM Online and Active Learning. Neural Computation 20(2), pp. 374-382, 2008 source code
Christian Igel, Verena Heidrich-Meisner, and Tobias Glasmachers. Shark. Journal of Machine Learning Research 9, pp. 993-996, 2008 source code
Susanne Winter, Bernhard Brendel, Ioannis Pechlivanis, Kirsten Schmieder, and Christian Igel. Registration of CT and Intraoperative 3D Ultrasound Images of the Spine Using Evolutionary and Gradient-based Methods. IEEE Transactions on Evolutionary Computation, 12(3), pp. 284–296, 2008
Christian Igel and Bernhard Sendhoff. Genesis of Organic Computing Systems: Coupling Evolution and Learning. In R. Würtz, ed.: Organic Computing, Chapter 7, pp. 141-166, Springer-Verlag, 2008
Tobias Glasmachers and Christian Igel. Uncertainty Handling in Model Selection for Support Vector Machines. In G. Rudolph, ed.: Parallel Problem Solving from Nature (PPSN X), LNCS 5199, pp. 185-194, Springer-Verlag, 2008
Verena Heidrich-Meisner and Christian Igel. Learning Behavioral Policies using Extrinsic Perturbations on the Level of Synapses. Frontiers in Computational Neuroscience. Conference Abstract: Bernstein Symposium 2008, 2008, doi:10.3389/conf.neuro.10.2008.01.060
Verena Heidrich-Meisner and Christian Igel. Evolution Strategies for Direct Policy Search. In G. Rudolph, ed.: Parallel Problem Solving from Nature (PPSN X), LNCS 5199, pp. 428-437, Springer-Verlag, 2008
Verena Heidrich-Meisner and Christian Igel. Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem. In Girgin et al., eds.: European Workshop on Reinforcement Learning (EWRL 2008), LNAI 5323, pp. 136-150, Springer-Verlag, 2008
Verena Heidrich-Meisner and Christian Igel. Similarities and differences between policy gradient methods and evolution strategies. In M. Verleysen, ed.: 16th European Symposium on Artificial Neural Networks (ESANN 2008), pp. 149-154, Belgium: d-side publications, 2008
Verena Heidrich-Meisner and Christian Igel. Uncertainty Handling in Evolutionary Direct Policy Search. In Y. Engel, M. Ghavamzadeh, P. Poupart, and S. Mannor, eds.: NIPS-08 Workshop on Model Uncertainty and Risk in Reinforcement Learning, 2008
Thorsten Suttorp and Christian Igel. Approximation of Gaussian Process Regression Models after Training. In M. Verleysen, ed.: 16th European Symposium on Artificial Neural Networks (ESANN 2008), pp. 427-432, Belgium: d-side publications, 2008 source code
Thomas Voß, Nicola Beume, Günter Rudolph, Christian Igel. Scalarization versus Indicator-based Selection in Multi-objective CMA Evolution Strategies. Congress on Evolutionary Computation 2008 (CEC 2008), pp. 3041-3048, IEEE Press, 2008

2007

Christian Igel, Nikolaus Hansen, and Stefan Roth. Covariance Matrix Adaptation for Multi-objective Optimization. Evolutionary Computation 15(1), pp. 1-28, 2007 source code
Christian Igel, Tobias Glasmachers, Britta Mersch, Nico Pfeifer, and Peter Meinicke. Gradient-based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection. IEEE/ACM Transactions on Computational Biology and Bioinformatics 4(2), pp. 216-226, 2007 source code & supplementary material
Britta Mersch, Tobias Glasmachers, Peter Meinicke, and Christian Igel. Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. International Journal of Neural Systems 17(5), selected paper of ICANN 2006, pp. 369-381, 2007 source code & supplementary material
Jens Niehaus, Christian Igel, and Wolfgang Banzhaf. Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database. Evolutionary Computation, 15(2), pp. 199-221, 2007
Verena Heidrich-Meisner, Martin Lauer, Christian Igel, and Martin Riedmiller. Reinforcement Learning in a Nutshell. In M. Verleysen, ed.: 15th European Symposium on Artificial Neural Networks (ESANN 2007), Belgium: d-side publications, pp. 277-288, 2007
Christian Igel, Thorsten Suttorp, and Nikolaus Hansen. Steady-state Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES. In S. Obayashi et al., eds.: Proceedings of the Fourth International Conference on Evolutionary Multi-Criterion Optimization (EMO 2007), LNCS 4403, pp. 171-185, Springer-Verlag, 2007 source code
Thorsten Suttorp and Christian Igel. Resilient Approximation of Kernel Classifiers. In J. Marques de Sá et al., eds.: International Conference on Artificial Neural Networks (ICANN 2007), LNCS 4668, pp. 139-148, Springer-Verlag, 2007 source code
Karin Liebenrodt, Martin H. J. Busch, Serban Mateiescu, Christian Igel, Susanne Winter, and Dietrich H. W. Grönemeyer. Protonenresonanzspektroskopie des Gehirns mit kurzer Echozeit: Unterstützung der Gewebeklassifizierung durch künstliche neuronale Netzwerke, Biomedizinische Technik (BMT), 52 (suppl.), 2007
Jan Salmen, Thorsten Suttorp, Johann Edelbrunner, and Christian Igel. Evolutionary Optimization of Wavelet Feature Sets for Real-Time Pedestrian Classification. In A. König, M. Köppen, A. Abraham, C. Igel, and N. Kasabov, eds.: International Conference on Hybrid Intelligent Systems (HIS 2007), pp. 222-227, IEEE Computer Society, 2007

2006

Tobias Glasmachers and Christian Igel. Maximum-Gain Working Set Selection for SVMs. Journal of Machine Learning Research 7, pp. 1437-1466, 2006 source code and supplementary information
Thorsten Suttorp and Christian Igel. Multi-objective optimization of support vector machines. In Y. Jin, ed.: Multi-objective Machine Learning, pp. 199-220, Studies in Computational Intelligence, Springer-Verlag, 2006
Stefan Roth, Alexander Gepperth, and Christian Igel. Multi-objective neural network optimization for visual object detection. In Y. Jin, ed.: Multi-objective Machine Learning, pp. 629-655, Studies in Computational Intelligence, Springer-Verlag, 2006
Christian Igel, Thorsten Suttorp, and Nikolaus Hansen. A Computational Efficient Covariance Matrix Update and a (1+1)-CMA for Evolution Strategies. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2006), pp. 453-460, ACM Press, 2006 source code
Britta Mersch, Tobias Glasmachers, Peter Meinicke, and Christian Igel. Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. In S. Kollias et al., eds.: International Conference on Artificial Neural Networks (ICANN 2006), LNCS 4132, pp. 827-836, Springer-Verlag, 2006 source code & supplementary material

2005

Tobias Glasmachers and Christian Igel. Gradient-based Adaptation of General Gaussian Kernels. Neural Computation 17(10), pp. 2099-2105, 2005
Antonio Pellecchia, Christian Igel, Johann Edelbrunner, and Gregor Schöner. Making Driver Modeling Attractive. IEEE Intelligent Systems 20(2), pp. 8-12, 2005
Frauke Friedrichs and Christian Igel. Evolutionary Tuning of Multiple SVM Parameters. Neurocomputing 64(C), pp. 107-117, 2005
Christian Igel, Marc Toussaint, and Wan Weishui. Rprop Using the Natural Gradient. In M. G. de Bruin, D. H. Mache, and J. Szabados, eds.: Trends and Applications in Constructive Approximation. International Series of Numerical Mathematics, vol. 151, pp. 259-272, Birkhäuser Verlag, 2005
Christian Igel, Frauke Friedrichs, and Stefan Wiegand. Evolutionary Optimization of Neural Systems: The Use of Strategy Adaptation. In M. G. de Bruin, D. H. Mache, and J. Szabados, eds.: Trends and Applications in Constructive Approximation. International Series of Numerical Mathematics, vol. 151, pp. 103-123, Birkhäuser Verlag, 2005
Susanne Winter, Bernhard Brendel, and Christian Igel. Registration of bone structures in 3D ultrasound and CT data: Comparison of different optimization strategies. In H. U. Lemke, K. Inamura, K. Doi, M. W. Vannier, and A. G. Farman, eds.: Computer Assisted Radiology and Surgery (CARS 2005), International Congress Series 1281, pp. 242-247, Elsevier, 2005
Christian Igel and Bernhard Sendhoff. Synergies between Evolutionary and Neural Computation. In M. Verleysen, ed.: 13th European Symposium on Artificial Neural Networks (ESANN 2005), pp. 241-252, Belgium: d-side publications, 2005
Christian Igel. Multiobjective Model Selection for Support Vector Machines. In C. A. Coello Coello, E. Zitzler, and A. Hernandez Aguirre, eds.: Proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization (EMO 2005), LNCS 3410, pp. 534-546, Springer-Verlag, 2005
Susanne Winter, Bernhard Brendel, and Christian Igel. Registrierung von Knochen in 3D-Ultraschall- und CT-Daten: Vergleich verschiedener Optimierungsverfahren. In Bildverarbeitung für die Medizin (BVM), pp. 345-149, Springer-Verlag, 2005

2004

Christian Igel and Karl-Heinz Temme. The Chaining Syllogism in Fuzzy Logic. IEEE Transactions on Fuzzy Systems 12(6), pp. 849-853, 2004 (extended version)
Stefan Wiegand, Christian Igel, and Uwe Handmann. Evolutionary Multi-Objective Optimization of Neural Networks for Face Detection. International Journal of Computational Intelligence and Applications, Special Issue on Neurocomputing and Hybrid Methods for Evolving Intelligence 4(3), pp. 237-253, 2004
Christian Igel and Marc Toussaint. A No-Free-Lunch Theorem for Non-Uniform Distributions of Target Functions. Journal of Mathematical Modelling and Algorithms 3(4), pp. 313-322, 2004
Stefan Schneider, Christian Igel, Christian Klaes, Hubert R. Dinse, and Jan C. Wiemer. Evolutionary adaptation of nonlinear dynamical systems in computational neuroscience. Genetic Programming and Evolvable Machines 5(2), Special Issue on Biological Applications of Genetic and Evolutionary Computation, pp. 215-227, 2004
Thomas Wiebringhaus, Christian Igel, and Jutta Gebert. Protein Fold Class Prediction Using Neural Networks with Tailored Early-Stopping. International Joint Conference on Neural Networks (IJCNN 2004), pp. 1693-1697, IEEE Press, 2004 note
Frauke Friedrichs and Christian Igel. Evolutionary Tuning of Multiple SVM Parameters. In M. Verleysen, ed.: 12th European Symposium on Artificial Neural Networks (ESANN 2004), pp. 519-524, Belgium: d-side publications, 2004 note
Stefan Wiegand, Christian Igel, and Uwe Handmann. Evolutionary Optimization of Neural Networks for Face Detection. In M. Verleysen, ed.: 12th European Symposium on Artificial Neural Networks (ESANN 2004), pp. 139-144 Belgium: d-side publications, 2004

2003

Christian Igel and Martin Kreutz. Operator Adaptation in Evolutionary Computation and its Application to Structure Optimization of Neural Networks. Neurocomputing 55(1-2), pp. 347-361, 2003 (uncorrected proof)
Torsten Mayr, Christian Igel, Gregor Liebsch, Ingo Klimant, and Otto S. Wolfbeis. Cross-Reactive Metal Ion Sensor Array in a Microtiterplate Format. Analytical Chemistry 75(17), pp. 4389-4396, 2003
Christian Igel and Marc Toussaint. Neutrality and Self-Adaptation. Natural Computing 2(2), pp. 117-132, 2003
Christian Igel and Marc Toussaint. On Classes of Functions for which No Free Lunch Results Hold. Information Processing Letters 86(6), pp. 317-321, 2003
Thomas Bücher, Cristobal Curio, Johann Edelbrunner, Christian Igel, David Kastrup, Iris Leefken, Gesa Lorenz, Axel Steinhage, and Werner von Seelen. Image Processing and Behaviour Planning for Intelligent Vehicles. IEEE Transactions on Industrial Electronics 50(1), pp. 62-75, 2003
Christian Igel and Michael Hüsken. Empirical Evaluation of the Improved Rprop Learning Algorithm. Neurocomputing 50(C), pp. 105-123, 2003 source code
Christian Igel. Neuroevolution for Reinforcement Learning Using Evolution Strategies. In R. Sarker, R. Reynolds, H. Abbass, K. C. Tan, B. McKay, D. Essam, and T. Gedeon, eds.: Congress on Evolutionary Computation 2003 (CEC 2003), Volume 4, pp. 2588-2595, IEEE Press, 2003
Thomas Wiebringhaus, Ulrich Faigle, Dietmar Schomburg, Jutta Gebert, Christian Igel, and Gerhard-Wilhelm Weber. Protein Fold Class Prediction Using Neural Networks Reconsidered. Currents in Computational Molecular Biology, The Seventh Annual International Conference on Research in Computational Molecular Biology (RECOMB 2003), pp. 225-226, 2003

2002

Michael Hüsken, Christian Igel, and Marc Toussaint. Task-Dependent Evolution of Modularity in Neural Networks. Connection Science 14(3), pp. 219-229, 2002
Christian Igel and Peter Stagge. Effects of Phenotypic Redundancy in Structure Optimization. IEEE Transactions on Evolutionary Computation 6(1), pp. 74-85, 2002
Christian Igel, Werner von Seelen, Wolfram Erlhagen, and Dirk Jancke. Evolving Field Models for Inhibition Effects in Early Vision. Neurocomputing 44-46(C), pp. 467-472, 2002
Hubert R. Dinse, Michael Hüsken, Christian Igel, Christian Klaes, Marc Nunkesser, Stefan Schneider, and Jan Wiemer. Derandomized Evolution Strategies in Computational Neuroscience. In A. Barry, ed.: 2002 Genetic and Evolutionary Computation Conference Workshop Program (GECCO 2002): Biological Applications of Genetic and Evolutionary Computation (BioGEC 2002), pp. 35-37, 2002
Michael Hüsken and Christian Igel. Balancing Learning and Evolution. In W. B. Langdon, E. Cantu-Paz, K. Mathias, R. Roy, D. Davis, R. Poli, K. Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M. A. Potter, A. C. Schultz, J. F. Miller, E. Burke, and N. Jonoska, eds.: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2002), pp. 391-398, 2002, Morgan Kaufmann
Christian Igel and Peter Stagge. Graph Isomorphisms Affect Structure Optimization of Neural Networks. International Joint Conference on Neural Networks 2002 (IJCNN 2002), pp. 142-147, IEEE Press
Marc Toussaint and Christian Igel. Neutrality: A Necessity for Self-Adaptation. Congress on Evolutionary Computation 2002 (CEC 2002), pp. 1354-1359, IEEE Press

2001

Christian Igel, Wolfram Erlhagen, and Dirk Jancke. Optimization of Dynamic Neural Fields. Neurocomputing 36(1-4), pp. 225-233, 2001
Thomas Bergener, Carsten Bruckhoff and Christian Igel. Parameter Optimization for Visual Obstacle Detection Using a Derandomized Evolution Strategy. In J. Blanc-Talon and D. Popescu, eds.: Imaging and Vision Systems: Theory, Assessment and Application. Advances in Computation: Theory and Practice 9, Chapter 13, pp. 265-279, NOVA Science Books, 2001
Christian Igel and Martin Kreutz. Operator Adaptation in Structure Optimization of Neural Networks. In L. Spector, E. Goodman, A. Wu, W.B. Langdon, H.-M. Voigt, M. Gen, S. Sen, M. Dorigo, S. Pezeshk, M. Garzon, and E. Burke, eds.: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '01), p. 1094, Morgan Kaufmann Publishers, 2001
Johann Edelbrunner, Uwe Handmann, Christian Igel, Iris Leefken and Werner von Seelen. Application and Optimization of Neural Field Dynamics for Driver Assistance. In The IEEE 4th International Conference on Intelligent Transportation Systems (ITSC '01), pp. 309-314, IEEE Press, 2001
Peter Stagge and Christian Igel. Structure Optimization and Isomorphisms. In L. Kallel, B. Naudts and A. Rogers, eds.: Theoretical Aspects of Evolutionary Computing, Natural Computing series, pp. 409-422, Springer-Verlag, 2001

2000

Peter Stagge and Christian Igel. Neural Network Structures and Isomorphisms: Random Walk Characteristics of the Search Space. In X. Yao and D. B. Fogel, eds.: 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (ECNN), pp. 82-90, IEEE press, 2000
Christian Igel and Michael Hüsken. Improving the Rprop Learning Algorithm. In H. Bothe and R. Rojas, eds.: Second International Symposium on Neural Computation (NC 2000), pp. 115-121, ICSC Academic Press, 2000 source code

1999

Thomas Bergener, Carsten Bruckhoff and Christian Igel. Evolutionary Parameter Optimization for Visual Obstacle Detection. In J. Blanc-Talon and D. Popescu, eds.: Advanced Concepts for Intelligent Vision Systems (ACIVS'99), pp. 104-109, The International Institute for Advanced Studies in Systems Research and Cybernetics, 1999
Christian Igel and Kumar Chellapilla. Fitness Distributions: Tools for Designing Efficient Evolutionary Computations. In L. Spector, W. B. Langdon, U.-M. O'Reilly, and P. J. Angeline, eds.: Advances in Genetic Programming 3, Chapter 9, pp. 191-216, MIT Press, 1999
Christian Igel and Kumar Chellapilla. Investigating the Influence of Depth and Degree of Genotypic Change on Fitness in Genetic Programming. In W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela and R. E. Smith, eds.: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '99), Volume 2, pp. 1061-1068, Morgan Kaufmann Publishers, 1999 note
Christian Igel and Martin Kreutz. Using Fitness Distributions to Improve the Evolution of Learning Structures. Congress on Evolutionary Computation (CEC 99), Volume 3, pp. 1902-1909, IEEE Press, 1999

1998

Christian Igel. Causality of Hierarchical Variable Length Representations. Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC'98), pp. 324-329, IEEE Press, 1998

1997

Christian Igel and Karl-Heinz Temme. Chaining Syllogism Applied to Fuzzy If-Then Rules and Rule Bases. In B. Reusch, ed.: Computational Intelligence - Theory and Applications, LNCS 1226, pp. 179-188, Springer-Verlag, 1997

Edited Conference Proceedings

Christian Blum et al.: Proceedings of the Ffteenth International Conference on Genetic and Evolutionary Computation (GECCO 2013), ACM Press, 2013 (ESEP track chair)
Terence Soule, Anne Auger, Christian Blum, Jürgen Branke, Nicolas Bredeche, Will Neil Browne, John Andrew Clark, Kalyanmoy Deb, Alan Dorin, Rene Doursat, Aniko Ekart, Tobias Friedrich, Steven Gustafson, Gregory S. Hornby, Christian Igel, Tim Kovacs, Dario Landa-Silva, Fernando G. Lobo, Gisele Lobo Pappa, Jose A. Lozano, Silja Meyer-Nieberg, Alison Motsinger, Frank Neumann, Gabriela Ochoa, Gustavo Olague, Yew-Soon Ong, Martin Pelikan, David Pelta, Clara Pizzuti, Mike Preuss, Jonathan Rowe, Stephen Leslie Smith, Christine Solnon, Giovanni Squillero, Daniel Tauritz, Man Leung Wong, Shin Yoo, and Tina Yu, eds.: Proceedings of the Fourteenth International Conference on Genetic and Evolutionary Computation (GECCO 2012), ACM Press, 2012 (ESEP track chair)
Andreas König, Mario Köppen, Ajith Abraham, Christian Igel, and Nikola Kasabov, eds.: International Conference on Hybrid Intelligent Systems (HIS 2007), IEEE Computer Society, 2007

Theses

Christian Igel. Optimization of Support Vector Machines, Habiltation thesis, Faculty of Electrical Engineering and Information Technology, Ruhr-Universität Bochum, 2010
Christian Igel. Beiträge zum Entwurf neuronaler Systeme, Doctoral thesis, University of Bielefeld, Faculty of Technology, Shaker-Verlag, Aachen, Germany, ISBN: 3-8322-1103-9
Christian Igel. Untersuchungen zur Kettenregel für Fuzzy-Regeln und Regelbasen mit implikationsbasierter Semantik, Diploma thesis, University of Dortmund, Department of Computer Science, 1997

Abstracts and not peer-reviewed contributions to conferences

Matthias Tuma and Christian Igel. Kernel-based machine learning techniques for infrasound signal classification. European Geosciences Union General Assembly 2014, accepted
Matthias Tuma and Christian Igel. Investigation of Kernel-Based Machine Learning Techniques for Infrasound Signal Classification. CTBTO Science and Technology (SNT 2013), T3-P67 , 2013
Matthias Tuma, Christian Igel, and Mark Prior. Joint Optimization of a Signal Processing Chain for Hydroacoustic Signal Classification. CTBTO Science and Technology (SNT 2013), T3-P69, 2013
Lauge Sørensen, Akshay Pai, Sune Darkner, Gennan Chen, Joonmi Oh, Joyce Suhy, Christian Igel, and Mads Nielsen. Hippocampal Texture Predicts One-Year Hippocampal Atrophy in Mild Cognitively Impaired Subjects. European Congress on Radiology, 2013
Lauge Sørensen, Akshay Pai and Christian Igel and Mads Nielsen. Hippocampal Texture Predicts Conversion from MCI to AD. Alzheimer's Association International Conference, Alzheimer's and Dementia 9(4), suppl., P581, 2013
Lauge Sørensen, Akshay Pai and Christian Igel and Mads Nielsen. Hippocampal Texture Predicts Conversion from MCI to AD. Alzheimer's Imaging Consortium, Alzheimer's and Dementia 9(4), suppl., P52 2013
Lauge Sørensen, Akshay Pai, Sune Darkner, Joyce Suhy, Joommi Oh, Gennan Chen, Christian Igel, Mads Nielsen. Hippocampal Texture Provides Volume Independent Information for Alzheimer’s Disease Diagnosis. Alzheimer's & Dementia: The Journal of the Alzheimer’s Association 8(4) supplement, P162–P163, 2012
Lauge Sørensen, Akshay Pai, Sune Darkner, Joyce Suhy, Joommi Oh, Gennan Chen, Christian Igel, Mads Nielsen. Hippocampal Texture Provides Volume Independent Information for Alzheimer’s Diagnosis. Alzheimer's & Dementia: The Journal of the Alzheimer’s Association 8(4), supplement, P15, IC-P-013, 2012
Asja Fischer and Christian Igel. Bounding the Bias of Contrastive Divergence Used for Maximum Likelihood Learning in Restricted Boltzmann Machines. In: Second Joint Statistical Meeting Deutsche Arbeitsgemeinschaft Statistik `Statistics under one umbrella' (DAGStat 2010), p. 98, 2010
Matthias Tuma and Christian Igel. Automatic Classification of Hydroacoustic Signals to Support Verification of the Comprehensive Nuclear-Test-Ban Treaty. In: Second Joint Statistical Meeting Deutsche Arbeitsgemeinschaft Statistik `Statistics under one umbrella' (DAGStat 2010), p. 361, 2010
Valentin Markounikau, Christian Igel, and Dirk Jancke. Neural Field Models of Early Cortical Processing of Real and Apparent Motion. In: Computational Vision and Neuroscience Symposium, p. 36. Max Planck Institute for Biological Cybernetics, Tübingen, 2008
Christian Igel. Efficient Covariance Matrix Update for Evolution Strategies. In D. V. Arnold, A. Auger, J. E. Rowe, and C. Witt, eds.: Theory of Evolutionary Algorithms, Dagstuhl Seminar Proceedings 08051, Abstract Collection. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, 2008
Jennifer Meyer, Dirk Jancke, and Christian Igel. Modelling cortical activity underlying apparent and real motion perception. In K.-A. Hossmann, ed.: Symposium `Neuro-Visionen 4, Perspektiven in Nordrhein-Westfalen', pp. 257-258. Verlag Ferdinand Schöningh, 2007
Christian Igel. Computational Efficient Covariance Matrix Update and the Multi-objective Variable Metric Evolution Strategy. In D. V. Arnold, T. Jansen, J. E. Rowe, and M. D. Vose, eds.: Theory of Evolutionary Algorithms, Dagstuhl Seminar Proceedings 06061, Abstract Collection. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, 2006
Christian Igel. The Bias-Invariance Dilemma. In K. Bellman, P. Hofmann, C. Müller-Schloer, H. Schmeck, and R.Würtz, eds.: Organic Computing - Controlled Emergence, Dagstuhl Seminar Proceedings 06031, Abstract Collection. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, 2006
Jennifer Meyer, Christian Igel, and Dirk Jancke. Modelling dynamic activity patterns in early visual cortex based on voltage sensitive dye experiments. In K.-A. Hossmann, ed.: Symposium `Neuro-Visionen 3, Perspektiven in Nordrhein-Westfalen', pp. 193-195. Verlag Ferdinand Schöningh, 2006
Christian Igel: Recent Results on No-Free-Lunch for Optimization. In H.-G. Beyer, T. Jansen, C. Reeves, and M. D. Vose, eds.: Theory of Evolutionary Algorithms, Dagstuhl Seminar Proceedings 04081, Abstract Collection. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, 2004.
Christian Igel and Werner von Seelen. Design of a Field Model for Early Vision: A Case Study of Evolutionary Algorithms in Neuroscience. In N. Elsner and G. W. Kreutzberg, eds.: Göttingen Neurobiology Report 2001, Volume 2, p. 1034, Georg Thieme Verlag, 2001
Michael Hüsken, Christian Igel, and Marc Toussaint. Task-Dependent Evolution of Modularity in Neural Networks - A Quantitative Case Study. In Erik D. Goodman, ed.: Late Breaking Papers at the 2001 Genetic and Evolutionary Computation Conference, pp. 187-193, 2001
Jens Busse, Hans-Jürgen Röhm, Sascha Wenzel, Gerd Emmrich, and Christian Igel. Zur Auslegung von thermisch und stofflich gekoppelten Destillationskolonnen mit evulutionären Algorithmen, GVC / DECHEMA Fachausschuss Prozess- und Anlagentechnik, 2001

Technical reports

Ürün Dogan, Tobias Glasmachers, and Christian Igel. Fast Training of Multi-class Support Vector Machines. Technical Report no. 03/2011, Department of Computer Science, Faculty of Science, University of Copenhagen, 2011
Christian Igel, Nikolaus Hansen, and Stefan Roth. The Multi-objective Variable Metric Evolution Strategy, Part I. Technical Report, IRINI-2001-04, Institut für Neuroinformatik, 2005
Tobias Glasmachers and Christian Igel. Maximum-Gain Working Set Selection for Support Vector Machines. Technical Report, IRINI-2005-03, Institut für Neuroinformatik, 2005 source code and supplementary information
Jens Niehaus, Christian Igel, and Wolfgang Banzhaf. Graph Genetic Programming and Neutrality. Technical Report, IRINI-2005-02, Institut für Neuroinformatik, 2005
Britta Mersch, Nico Pfeifer, Tobias Glasmachers, Peter Meinicke, and Christian Igel. Gradient-based Optimization of Kernel-Target Alignment for Sequence Kernels Technical Report, IRINI-2005-01, Institut für Neuroinformatik, 2005
Christian Igel and Martin Kreutz. Operator Adaptation in Evolutionary Computation and its Application to Structure Optimization of Neural Networks. Technical Report, IRINI-2001-03, Institut für Neuroinformatik, 2001