Christian Igel

According to our database1, Christian Igel authored at least 136 papers between 1997 and 2018.

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Bibliography

2018
Population-Contrastive-Divergence: Does consistency help with RBM training?
Pattern Recognition Letters, 2018

On PAC-Bayesian Bounds for Random Forests.
CoRR, 2018

PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation.
CoRR, 2018

Training Big Random Forests with Little Resources.
CoRR, 2018

Sparse Incomplete LU-Decomposition for Wave Farm Designs Under Realistic Conditions.
Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

Training Big Random Forests with Little Resources.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Robust Active Label Correction.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Evolutionary Kernel Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Editorial - Project Reports.
KI, 2017

bufferkdtree: A Python library for massive nearest neighbor queries on multi-many-core devices.
Knowl.-Based Syst., 2017

Adaptive pattern recognition in real-time video-based soccer analysis.
J. Real-Time Image Processing, 2017

Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy.
IEEE Intelligent Systems, 2017

Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 17191).
Dagstuhl Reports, 2017

Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy.
CoRR, 2017

Massively-parallel best subset selection for ordinary least-squares regression.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Qualitative and Quantitative Assessment of Step Size Adaptation Rules.
Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2017

A Strongly Quasiconvex PAC-Bayesian Bound.
Proceedings of the International Conference on Algorithmic Learning Theory, 2017

Characterization of Errors in Deep Learning-Based Brain MRI Segmentation.
Proceedings of the Deep Learning for Medical Image Analysis, 1st Edition, 2017

2016
Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring.
IEEE Trans. Med. Imaging, 2016

Integrated Optimization of Long-Range Underwater Signal Detection, Feature Extraction, and Classification for Nuclear Treaty Monitoring.
IEEE Trans. Geoscience and Remote Sensing, 2016

Separating Timing, Movement Conditions and Individual Differences in the Analysis of Human Movement.
PLoS Computational Biology, 2016

A Unified View on Multi-class Support Vector Classification.
Journal of Machine Learning Research, 2016

PAC-Bayesian Aggregation without Cross-Validation.
CoRR, 2016

CMA-ES with Optimal Covariance Update and Storage Complexity.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning Density Independent Texture Features.
Proceedings of the Breast Imaging, 2016

Unbounded Population MO-CMA-ES for the Bi-Objective BBOB Test Suite.
Proceedings of the Genetic and Evolutionary Computation Conference, 2016

Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
A bound for the convergence rate of parallel tempering for sampling restricted Boltzmann machines.
Theor. Comput. Sci., 2015

Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211).
Dagstuhl Reports, 2015

Population-Contrastive-Divergence: Does Consistency help with RBM training?
CoRR, 2015

Bigger Buffer k-d Trees on Multi-Many-Core Systems.
CoRR, 2015

A More Efficient Rank-one Covariance Matrix Update for Evolution Strategies.
Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIII, Aberystwyth, United Kingdom, January 17, 2015

High-School Dropout Prediction Using Machine Learning: A Danish Large-scale Study.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Computational Complexity of Linear Large Margin Classification With Ramp Loss.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
No Free Lunch Theorems: Limitations and Perspectives of Metaheuristics.
Proceedings of the Theory and Principled Methods for the Design of Metaheuristics, 2014

Active learning with support vector machines.
Wiley Interdiscip. Rev. Data Min. Knowl. Discov., 2014

Training restricted Boltzmann machines: An introduction.
Pattern Recognition, 2014

Automatic FDG-PET-based tumor and metastatic lymph node segmentation in cervical cancer.
Proceedings of the Medical Imaging 2014: Image Processing, 2014

Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs.
Proceedings of the 31th International Conference on Machine Learning, 2014

Speedy greedy feature selection: Better redshift estimation via massive parallelism.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013
A Note on Generalization Loss When Evolving Adaptive Pattern Recognition Systems.
IEEE Trans. Evolutionary Computation, 2013

Linear feature selection in texture analysis - A PLS based method.
Mach. Vis. Appl., 2013

The flip-the-state transition operator for restricted Boltzmann machines.
Machine Learning, 2013

Echtzeit-Videoanalyse im Fußball - Ein Live-System zum Spieler-Tracking.
KI, 2013

Speeding up many-objective optimization by Monte Carlo approximations.
Artif. Intell., 2013

Deep Feature Learning for Knee Cartilage Segmentation Using a Triplanar Convolutional Neural Network.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

Detection of traffic signs in real-world images: The German traffic sign detection benchmark.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Approximation properties of DBNs with binary hidden units and real-valued visible units.
Proceedings of the 30th International Conference on Machine Learning, 2013

Shape Index Descriptors Applied to Texture-Based Galaxy Analysis.
Proceedings of the IEEE International Conference on Computer Vision, 2013

Femoral cartilage segmentation in Knee MRI scans using two stage voxel classification.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

Nearest neighbour regression outperforms model-based prediction of specific star formation rate.
Proceedings of the 2013 IEEE International Conference on Big Data, 2013

Nearest neighbor classification using bottom-k sketches.
Proceedings of the 2013 IEEE International Conference on Big Data, 2013

Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification.
Proceedings of the Asian Conference on Machine Learning, 2013

2012
Introduction to the Special Issue on Machine Learning for Traffic Sign Recognition.
IEEE Trans. Intelligent Transportation Systems, 2012

Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition.
Neural Networks, 2012

Learning ∈ Artificial Intelligence ∩ Cognitive Technologies ∩ Neural Computation ∩ ...
KI, 2012

Evolutionary kernel machines.
Evolutionary Intelligence, 2012

A Note on Extending Generalization Bounds for Binary Large-Margin Classifiers to Multiple Classes.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Cascaded classifier for large-scale data applied to automatic segmentation of articular cartilage.
Proceedings of the Medical Imaging 2012: Image Processing, 2012

Towards exaggerated emphysema stereotypes.
Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, 2012

An Introduction to Restricted Boltzmann Machines.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2012

2011
Huge Music Archives on Mobile Devices.
IEEE Signal Process. Mag., 2011

Bounding the Bias of Contrastive Divergence Learning.
Neural Computation, 2011

The German Traffic Sign Recognition Benchmark: A multi-class classification competition.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

The logarithmic hypervolume indicator.
Proceedings of the Foundations of Genetic Algorithms, 11th International Workshop, 2011

Non-linearly increasing resampling in racing algorithms.
Proceedings of the ESANN 2011, 2011

Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives.
Proceedings of the ESANN 2011, 2011

Real-Time Estimation of Optical Flow Based on Optimized Haar Wavelet Features.
Proceedings of the Evolutionary Multi-Criterion Optimization, 2011

Improved Working Set Selection for LaRank.
Proceedings of the Computer Analysis of Images and Patterns, 2011

Towards exaggerated image stereotypes.
Proceedings of the First Asian Conference on Pattern Recognition, 2011

2010
Evolutionary Kernel Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Editorial: Special issue on organic computing.
TAAS, 2010

Efficient update of the covariance matrix inverse in iterated linear discriminant analysis.
Pattern Recognition Letters, 2010

A Dynamic Neural Field Model of Mesoscopic Cortical Activity Captured with Voltage-Sensitive Dye Imaging.
PLoS Computational Biology, 2010

Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters.
IEEE Trans. Pattern Anal. Mach. Intell., 2010

Structure optimization of reservoir networks.
Logic Journal of the IGPL, 2010

New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization.
Proceedings of the Parallel Problem Solving from Nature, 2010

Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines.
Proceedings of the Artificial Neural Networks - ICANN 2010, 2010

Improved step size adaptation for the MO-CMA-ES.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Scaling up indicator-based MOEAs by approximating the least hypervolume contributor: a preliminary study.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

2009
Efficient covariance matrix update for variable metric evolution strategies.
Machine Learning, 2009

Ontogenetic and Phylogenetic Reinforcement Learning.
KI, 2009

Gasteditorial Reinforcement Learning.
KI, 2009

Neuroevolution strategies for episodic reinforcement learning.
J. Algorithms, 2009

Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Uncertainty handling CMA-ES for reinforcement learning.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

Recombination for Learning Strategy Parameters in the MO-CMA-ES.
Proceedings of the Evolutionary Multi-Criterion Optimization, 5th International Conference, 2009

2008
Registration of CT and Intraoperative 3-D Ultrasound Images of the Spine Using Evolutionary and Gradient-Based Methods.
IEEE Trans. Evolutionary Computation, 2008

Second-Order SMO Improves SVM Online and Active Learning.
Neural Computation, 2008

Shark.
Journal of Machine Learning Research, 2008

Evolution Strategies for Direct Policy Search.
Proceedings of the Parallel Problem Solving from Nature, 2008

Uncertainty Handling in Model Selection for Support Vector Machines.
Proceedings of the Parallel Problem Solving from Nature, 2008

Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem.
Proceedings of the Recent Advances in Reinforcement Learning, 8th European Workshop, 2008

Approximation of Gaussian process regression models after training.
Proceedings of the ESANN 2008, 2008

Similarities and differences between policy gradient methods and evolution strategies.
Proceedings of the ESANN 2008, 2008

Scalarization versus indicator-based selection in multi-objective CMA evolution strategies.
Proceedings of the IEEE Congress on Evolutionary Computation, 2008

2007
Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection.
IEEE/ACM Trans. Comput. Biology Bioinform., 2007

Evolutionary Optimization of Sequence Kernels for Detection of bacterial gene Starts.
Int. J. Neural Syst., 2007

Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database.
Evolutionary Computation, 2007

Covariance Matrix Adaptation for Multi-objective Optimization.
Evolutionary Computation, 2007

Resilient Approximation of Kernel Classifiers.
Proceedings of the Artificial Neural Networks, 2007

Evolutionary Optimization ofWavelet Feature Sets for Real-Time Pedestrian Classification.
Proceedings of the 7th International Conference on Hybrid Intelligent Systems (HIS 2007), 2007

Reinforcement learning in a nutshell.
Proceedings of the ESANN 2007, 2007

2006
Multi-Objective Optimization of Support Vector Machines.
Proceedings of the Multi-Objective Machine Learning, 2006

Multi-Objective Neural Network Optimization for Visual Object Detection.
Proceedings of the Multi-Objective Machine Learning, 2006

Maximum-Gain Working Set Selection for SVMs.
Journal of Machine Learning Research, 2006

Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts.
Proceedings of the Artificial Neural Networks, 2006

A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies.
Proceedings of the Genetic and Evolutionary Computation Conference, 2006

Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES.
Proceedings of the Evolutionary Multi-Criterion Optimization, 4th International Conference, 2006

2005
Gradient-Based Adaptation of General Gaussian Kernels.
Neural Computation, 2005

Evolutionary tuning of multiple SVM parameters.
Neurocomputing, 2005

Making Driver Modeling Attractive.
IEEE Intelligent Systems, 2005

Synergies between Evolutionary and Neural Computation.
Proceedings of the ESANN 2005, 2005

Multi-objective Model Selection for Support Vector Machines.
Proceedings of the Evolutionary Multi-Criterion Optimization, 2005

Registrierung von Knochen in 3D-Ultraschall- und CT-Daten: Vergleich verschiedener Optimierungsverfahren.
Proceedings of the Bildverarbeitung für die Medizin 2005, Algorithmen - Systeme, 2005

2004
The chaining syllogism in fuzzy logic.
IEEE Trans. Fuzzy Systems, 2004

A No-Free-Lunch theorem for non-uniform distributions of target functions.
J. Math. Model. Algorithms, 2004

Evolutionary Multi-Objective Optimisation Of Neural Networks For Face Detection.
International Journal of Computational Intelligence and Applications, 2004

Evolutionary Adaptation of Nonlinear Dynamical Systems in Computational Neuroscience.
Genetic Programming and Evolvable Machines, 2004

Evolutionary Optimization of Neural Networks for Face Detection.
Proceedings of the ESANN 2004, 2004

Evolutionary tuning of multiple SVM parameters.
Proceedings of the ESANN 2004, 2004

2003
Beiträge zum Entwurf neuronaler Systeme.
PhD thesis, 2003

Image processing and behavior planning for intelligent vehicles.
IEEE Trans. Industrial Electronics, 2003

Neutrality and self-adaptation.
Natural Computing, 2003

On classes of functions for which No Free Lunch results hold.
Inf. Process. Lett., 2003

Operator adaptation in evolutionary computation and its application to structure optimization of neural networks.
Neurocomputing, 2003

Empirical evaluation of the improved Rprop learning algorithms.
Neurocomputing, 2003

Recent Results on No-Free-Lunch Theorems for Optimization
CoRR, 2003

2002
Effects of phenotypic redundancy in structure optimization.
IEEE Trans. Evolutionary Computation, 2002

Evolving field models for inhibition effects in early vision.
Neurocomputing, 2002

Neutrality: A Necessity for Self-Adaptation
CoRR, 2002

Balancing Learning And Evolution.
Proceedings of the GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, 2002

2001
Optimization of dynamic neural fields.
Neurocomputing, 2001

On Classes of Functions for which No Free Lunch Results Hold
CoRR, 2001

1997
Chaining Syllogism Applied to Fuzzy IF-THEN Rules and Rule Bases.
Proceedings of the Computational Intelligence, 1997


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