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Christian Igel, Prof. Dr. habil. - Publications

Affiliations: 
Department of Computer Science University of Copenhagen, København, Denmark 
 Bielefeld University, Bielefeld, Nordrhein-Westfalen, Germany 
 Institute for Neuroinformatics Ruhr University Bochum, Bochum, Nordrhein-Westfalen, Germany 
 Technical University of Dortmund 
Area:
machine learning
Website:
https://christian-igel.github.io/
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46 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Krause O, Fischer A, Igel C. Algorithms for estimating the partition function of restricted Boltzmann machines Artificial Intelligence. 278: 103195. DOI: 10.1016/J.Artint.2019.103195  0.383
2019 Lorenzen SS, Igel C, Seldin Y. On PAC-Bayesian bounds for random forests Machine Learning. 108: 1503-1522. DOI: 10.1007/S10994-019-05803-4  0.36
2018 Shakibfar S, Krause O, Lund-Andersen C, Aranda A, Moll J, Andersen TO, Svendsen JH, Petersen HH, Igel C. Predicting electrical storms by remote monitoring of implantable cardioverter-defibrillator patients using machine learning. Europace : European Pacing, Arrhythmias, and Cardiac Electrophysiology : Journal of the Working Groups On Cardiac Pacing, Arrhythmias, and Cardiac Cellular Electrophysiology of the European Society of Cardiology. PMID 30508072 DOI: 10.1093/Europace/Euy257  0.301
2018 Krause O, Fischer A, Igel C. Population-Contrastive-Divergence: Does consistency help with RBM training? Pattern Recognition Letters. 102: 1-7. DOI: 10.1016/J.Patrec.2017.11.022  0.304
2017 Sørensen L, Igel C, Pai A, Balas I, Anker C, Lillholm M, Nielsen M. Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry. Neuroimage. Clinical. 13: 470-482. PMID 28119818 DOI: 10.1016/J.Nicl.2016.11.025  0.355
2017 Kremer J, Stensbo-Smidt K, Gieseke F, Pedersen KS, Igel C. Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy Ieee Intelligent Systems. 32: 16-22. DOI: 10.1109/Mis.2017.40  0.368
2017 Stensbo-Smidt K, Gieseke F, Igel C, Zirm A, Pedersen KS. Sacrificing information for the greater good: how to select photometric bands for optimal accuracy Monthly Notices of the Royal Astronomical Society. 464: 2577-2596. DOI: 10.1093/Mnras/Stw2476  0.417
2017 Schlipsing M, Salmen J, Tschentscher M, Igel C. Adaptive pattern recognition in real-time video-based soccer analysis Journal of Real-Time Image Processing. 13: 345-361. DOI: 10.1007/S11554-014-0406-1  0.428
2016 Kallenberg M, Petersen K, Nielsen M, Ng A, Diao P, Igel C, Vachon C, Holland K, Karssemeijer N, Lillholm M. Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring. Ieee Transactions On Medical Imaging. PMID 26915120 DOI: 10.1109/Tmi.2016.2532122  0.344
2016 Tuma M, Rorbech V, Prior M, Igel C. Integrated Optimization of Long-Range Underwater Signal Detection, Feature Extraction, and Classification for Nuclear Treaty Monitoring Ieee Transactions On Geoscience and Remote Sensing. 54: 3649-3659. DOI: 10.1109/Tgrs.2016.2522972  0.449
2015 Fischer A, Igel C. A bound for the convergence rate of parallel tempering for sampling restricted Boltzmann machines Theoretical Computer Science. 598: 102-117. DOI: 10.1016/J.Tcs.2015.05.019  0.343
2015 Kremer J, Gieseke F, Steenstrup Pedersen K, Igel C. Nearest neighbor density ratio estimation for large-scale applications in astronomy Astronomy and Computing. 12: 67-72. DOI: 10.1016/J.Ascom.2015.06.005  0.401
2014 Fischer A, Igel C. Training restricted Boltzmann machines Pattern Recognition. 47: 25-39. DOI: 10.1016/J.Patcog.2013.05.025  0.414
2014 Kremer J, Steenstrup Pedersen K, Igel C. Active learning with support vector machines Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 4: 313-326. DOI: 10.1002/Widm.1132  0.41
2013 Igel C. A Note on Generalization Loss When Evolving Adaptive Pattern Recognition Systems Ieee Transactions On Evolutionary Computation. 17: 345-352. DOI: 10.1109/Tevc.2012.2197214  0.421
2013 Bringmann K, Friedrich T, Igel C, Voß T. Speeding up many-objective optimization by Monte Carlo approximations Artificial Intelligence. 204: 22-29. DOI: 10.1016/J.Artint.2013.08.001  0.388
2013 Brügge K, Fischer A, Igel C. The flip-the-state transition operator for restricted Boltzmann machines Machine Learning. 93: 53-69. DOI: 10.1007/S10994-013-5390-3  0.369
2012 Stallkamp J, Schlipsing M, Salmen J, Igel C. 2012 Special Issue: Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition Neural Networks. 32: 323-332. PMID 22394690 DOI: 10.1016/J.Neunet.2012.02.016  0.406
2012 Chen C, Sørensen L, Lauze F, Igel C, Loog M, Feragen A, De Bruijne M, Nielsen M. Towards exaggerated emphysema stereotypes Progress in Biomedical Optics and Imaging - Proceedings of Spie. 8315. DOI: 10.1117/12.911398  0.375
2012 Prasoon A, Igel C, Loog M, Lauze F, Dam E, Nielsen M. Cascaded classifier for large-scale data applied to automatic segmentation of articular cartilage Proceedings of Spie. 8314: 1-9. DOI: 10.1117/12.910809  0.408
2012 Stallkamp J, Schlipsing M, Salmen J, Igel C. Introduction to the Special Issue on Machine Learning for Traffic Sign Recognition Ieee Transactions On Intelligent Transportation Systems. 13: 1481-1483. DOI: 10.1109/Tits.2012.2225192  0.374
2012 Kramer O, Igel C, Rudolph G. Evolutionary kernel machines Evolutionary Intelligence. 5: 151-152. DOI: 10.1007/S12065-012-0072-9  0.465
2011 Fischer A, Igel C. Bounding the bias of contrastive divergence learning Neural Computation. 23: 664-673. PMID 21162669 DOI: 10.1162/Neco_A_00085  0.355
2010 Glasmachers T, Igel C. Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters Ieee Transactions On Pattern Analysis and Machine Intelligence. 32: 1522-1528. PMID 20421674 DOI: 10.1109/Tpami.2010.95  0.733
2010 Roeschies B, Igel C. Structure Optimization of Reservoir Networks Logic Journal of the Igpl. 18: 635-669. DOI: 10.1093/Jigpal/Jzp043  0.38
2010 Salmen J, Schlipsing M, Igel C. Efficient update of the covariance matrix inverse in iterated linear discriminant analysis Pattern Recognition Letters. 31: 1903-1907. DOI: 10.1016/J.Patrec.2010.03.001  0.435
2009 Heidrich-Meisner V, Igel C. Neuroevolution strategies for episodic reinforcement learning Journal of Algorithms. 64: 152-168. DOI: 10.1016/J.Jalgor.2009.04.002  0.418
2009 Suttorp T, Hansen N, Igel C. Efficient covariance matrix update for variable metric evolution strategies Machine Learning. 75: 167-197. DOI: 10.1007/S10994-009-5102-1  0.431
2008 Glasmachers T, Igel C. Second-order smo improves svm online and active learning Neural Computation. 20: 374-382. PMID 18045012 DOI: 10.1162/Neco.2007.10-06-354  0.718
2008 Winter S, Brendel B, Pechlivanis I, Schmieder K, Igel C. Registration of CT and Intraoperative 3-D Ultrasound Images of the Spine Using Evolutionary and Gradient-Based Methods Ieee Transactions On Evolutionary Computation. 12: 284-296. DOI: 10.1109/Tevc.2007.907558  0.332
2007 Mersch B, Glasmachers T, Meinicke P, Igel C. Evolutionary optimization of sequence kernels for detection of bacterial gene starts. International Journal of Neural Systems. 17: 369-381. PMID 18098369 DOI: 10.1142/S0129065707001214  0.728
2007 Igel C, Glasmachers T, Mersch B, Pfeifer N, Meinicke P. 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: 216-226. PMID 17473315 DOI: 10.1109/Tcbb.2007.070208  0.733
2007 Igel C, Hansen N, Roth S. Covariance matrix adaptation for multi-objective optimization. Evolutionary Computation. 15: 1-28. PMID 17388777 DOI: 10.1162/Evco.2007.15.1.1  0.373
2005 Glasmachers T, Igel C. Gradient-Based Adaptation of General Gaussian Kernels Neural Computation. 17: 2099-2105. PMID 16105219 DOI: 10.1162/0899766054615635  0.728
2005 Friedrichs F, Igel C. Evolutionary tuning of multiple SVM parameters Neurocomputing. 64: 107-117. DOI: 10.1016/J.Neucom.2004.11.022  0.504
2004 Wiegand S, Igel C, Handmann U. Evolutionary Multi-Objective Optimisation Of Neural Networks For Face Detection International Journal of Computational Intelligence and Applications. 4: 237-253. DOI: 10.1142/S1469026804001288  0.343
2004 Igel C, Toussaint M. A No-Free-Lunch Theorem for Non-Uniform Distributions of Target Functions Journal of Mathematical Modelling and Algorithms. 3: 313-322. DOI: 10.1023/B:Jmma.0000049381.24625.F7  0.355
2004 Schneider S, Igel C, Klaes C, Dinse HR, Wiemer JC. Evolutionary Adaptation of Nonlinear Dynamical Systems in Computational Neuroscience Genetic Programming and Evolvable Machines. 5: 215-227. DOI: 10.1023/B:Genp.0000023689.70987.6A  0.356
2003 Bücher T, Curio C, Edelbrunner J, Igel C, Kastrup D, Leefken I, Lorenz G, Steinhage A, Von Seelen W. Image processing and behavior planning for intelligent vehicles Ieee Transactions On Industrial Electronics. 50: 62-75. DOI: 10.1109/Tie.2002.807650  0.304
2003 Igel C, Toussaint M. Neutrality and self-adaptation Natural Computing. 2: 117-132. DOI: 10.1023/A:1024906105255  0.335
2003 Igel C, Kreutz M. Operator adaptation in evolutionary computation and its application to structure optimization of neural networks Neurocomputing. 55: 347-361. DOI: 10.1016/S0925-2312(02)00628-8  0.383
2003 Igel C, Hüsken M. Empirical evaluation of the improved Rprop learning algorithms Neurocomputing. 50: 105-123. DOI: 10.1016/S0925-2312(01)00700-7  0.398
2003 Igel C, Toussaint M. On classes of functions for which No Free Lunch results hold Information Processing Letters. 86: 317-321. DOI: 10.1016/S0020-0190(03)00222-9  0.343
2002 Igel C, Stagge P. Effects of phenotypic redundancy in structure optimization Ieee Transactions On Evolutionary Computation. 6: 74-85. DOI: 10.1109/4235.985693  0.351
2002 Hüsken M, Igel C, Toussaint M. Task-dependent evolution of modularity in neural networks Connection Science. 14: 219-229. DOI: 10.1080/09540090208559328  0.353
2001 Igel C, Erlhagen W, Jancke D. Optimization of dynamic neural fields [1] Neurocomputing. 36: 225-233. DOI: 10.1016/S0925-2312(00)00328-3  0.361
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