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ORCIDChristian Igel
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- affiliation: University of Copenhagen, Copenhagen, Denmark
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2020 – today
- 2024
[j67]Bjørn Leth Møller, Bobby Zhao Sheng Lo, Johan Burisch, Flemming Bendtsen, Ida Vind, Bulat Ibragimov, Christian Igel:
Building an AI Support Tool for Real-Time Ulcerative Colitis Diagnosis. Künstliche Intell. 38(3): 169-176 (2024)- [j66]Matthias Freiberger, Peter Kun, Christian Igel, Anders Sundnes Løvlie, Sebastian Risi:
Fooling Contrastive Language-Image Pre-Trained Models with CLIPMasterPrints. Trans. Mach. Learn. Res. 2024 (2024) - [c93]Nico Lang, Vésteinn Snæbjarnarson, Elijah Cole, Oisin Mac Aodha, Christian Igel, Serge J. Belongie:
From Coarse to Fine-Grained Open-Set Recognition. CVPR 2024: 17804-17814 - [c92]Vishal Nedungadi, Ankit Kariryaa
, Stefan Oehmcke, Serge J. Belongie, Christian Igel, Nico Lang:
MMEarth: Exploring Multi-modal Pretext Tasks for Geospatial Representation Learning. ECCV (64) 2024: 164-182 - [c91]Pedram Bakhtiarifard, Christian Igel, Raghavendra Selvan:
EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search. ICASSP 2024: 5660-5664 - [c90]Christian Igel:
Smooth Min-Max Monotonic Networks. ICML 2024 - [c89]Bjørn Leth Møller, Christian Igel, Kristoffer Knutsen Wickstrøm, Jon Sporring, Robert Jenssen, Bulat Ibragimov:
Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks. ICML 2024 - [i44]Raghavendra Selvan, Bob Pepin, Christian Igel, Gabrielle Samuel, Erik B. Dam:
Equity through Access: A Case for Small-scale Deep Learning. CoRR abs/2403.12562 (2024) - [i43]Vishal Nedungadi, Ankit Kariryaa, Stefan Oehmcke, Serge J. Belongie, Christian Igel, Nico Lang:
MMEarth: Exploring Multi-Modal Pretext Tasks For Geospatial Representation Learning. CoRR abs/2405.02771 (2024) - [i42]Dustin Wright, Christian Igel, Raghavendra Selvan:
BMRS: Bayesian Model Reduction for Structured Pruning. CoRR abs/2406.01345 (2024) - [i41]Venkanna Babu Guthula, Stefan Oehmcke, Remigio Chilaule, Hui Zhang, Nico Lang, Ankit Kariryaa, Johan Mottelson, Christian Igel:
Nacala-Roof-Material: Drone Imagery for Roof Detection, Classification, and Segmentation to Support Mosquito-borne Disease Risk Assessment. CoRR abs/2406.04949 (2024) - [i40]Nick Hauptvogel, Christian Igel:
Bayesian vs. PAC-Bayesian Deep Neural Network Ensembles. CoRR abs/2406.05469 (2024) - [i39]Bob Pepin, Christian Igel, Raghavendra Selvan:
When Can Memorization Improve Fairness? CoRR abs/2412.09254 (2024) - 2023
- [j65]Christian Igel, Stefan Oehmcke:
Remember to Correct the Bias When Using Deep Learning for Regression! Künstliche Intell. 37(1): 33-40 (2023) - [j64]Patrick Bilic, Patrick Ferdinand Christ, Hongwei Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland H. Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivanti, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Miriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Grün, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz K. Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John S. Lowengrub, Jun Ma, Klaus H. Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yue, Liping Zhang, Manuel Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern H. Menze:
The Liver Tumor Segmentation Benchmark (LiTS). Medical Image Anal. 84: 102680 (2023) - [c88]Rasmus Kær Jørgensen, Oliver Brandt, Mareike Hartmann, Xiang Dai, Christian Igel, Desmond Elliott:
MultiFin: A Dataset for Multilingual Financial NLP. EACL (Findings) 2023: 864-879 - [c87]Hui Zhang, Ankit Kariryaa, Venkanna Babu Guthula, Christian Igel, Stefan Oehmcke:
Predicting urban tree cover from incomplete point labels and limited background information. UrbanAI@SIGSPATIAL 2023: 52-60 - [i38]Lei Li, Tianfang Zhang, Stefan Oehmcke, Fabian Gieseke, Christian Igel:
BuildSeg: A General Framework for the Segmentation of Buildings. CoRR abs/2301.06190 (2023) - [i37]Christian Igel:
Smooth Monotonic Networks. CoRR abs/2306.01147 (2023) - [i36]Dustin Wright, Christian Igel, Gabrielle Samuel, Raghavendra Selvan:
Efficiency is Not Enough: A Critical Perspective of Environmentally Sustainable AI. CoRR abs/2309.02065 (2023) - [i35]Philip Enevoldsen, Christian Gundersen, Nico Lang, Serge J. Belongie, Christian Igel:
Familiarity-Based Open-Set Recognition Under Adversarial Attacks. CoRR abs/2311.05006 (2023) - [i34]Dimitri Gominski, Ankit Kariryaa, Martin Brandt, Christian Igel, Sizhuo Li, Maurice Mugabowindekwe, Rasmus Fensholt:
Benchmarking Individual Tree Mapping with Sub-meter Imagery. CoRR abs/2311.07981 (2023) - [i33]Hui Zhang, Ankit Kariryaa, Venkanna Babu Guthula, Christian Igel, Stefan Oehmcke:
Predicting urban tree cover from incomplete point labels and limited background information. CoRR abs/2311.11592 (2023) - 2022
- [j63]Abdelrahman Mohamed, Hung-yi Lee, Lasse Borgholt, Jakob D. Havtorn, Joakim Edin, Christian Igel, Katrin Kirchhoff, Shang-Wen Li, Karen Livescu, Lars Maaløe, Tara N. Sainath, Shinji Watanabe:
Self-Supervised Speech Representation Learning: A Review. IEEE J. Sel. Top. Signal Process. 16(6): 1179-1210 (2022) - [j62]Jaime C. Revenga, Katerina Trepekli, Stefan Oehmcke, Rasmus Jensen, Lei Li, Christian Igel, Fabian Gieseke, Thomas Friborg:
Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV-LiDAR and Machine Learning Methods. Remote. Sens. 14(16): 3912 (2022) - [c86]Rasmus Kær Jørgensen, Fiammetta Caccavale, Christian Igel, Anders Søgaard:
Are Multilingual Sentiment Models Equally Right for the Right Reasons? BlackboxNLP@EMNLP 2022: 131-141 - [c85]Stefan Oehmcke, Lei Li, Jaime C. Revenga, Thomas Nord-Larsen, Katerina Trepekli, Fabian Gieseke, Christian Igel:
Deep learning based 3D point cloud regression for estimating forest biomass. SIGSPATIAL/GIS 2022: 38:1-38:4 - [c84]Laura Cabello Piqueras, Constanza Fierro, Jonas F. Lotz, Phillip Rust, Joen Rommedahl, Jeppe Klok Due, Christian Igel, Desmond Elliott, Carsten B. Pedersen, Israfel Salazar, Anders Søgaard:
Date Recognition in Historical Parish Records. ICFHR 2022: 49-64 - [c83]Stephan Sloth Lorenzen, Christian Igel, Mads Nielsen:
Information Bottleneck: Exact Analysis of (Quantized) Neural Networks. ICLR 2022 - [c82]Pengfei Diao, Akshay Pai, Christian Igel, Christian Hedeager Krag:
Histogram-Based Unsupervised Domain Adaptation for Medical Image Classification. MICCAI (8) 2022: 755-764 - [i32]Lasse Borgholt, Jakob Drachmann Havtorn, Joakim Edin, Lars Maaløe, Christian Igel:
A Brief Overview of Unsupervised Neural Speech Representation Learning. CoRR abs/2203.01829 (2022) - [i31]Christian Igel, Stefan Oehmcke:
Remember to correct the bias when using deep learning for regression! CoRR abs/2203.16470 (2022) - [i30]Abdelrahman Mohamed, Hung-yi Lee, Lasse Borgholt, Jakob D. Havtorn, Joakim Edin, Christian Igel, Katrin Kirchhoff, Shang-Wen Li, Karen Livescu, Lars Maaløe, Tara N. Sainath, Shinji Watanabe:
Self-Supervised Speech Representation Learning: A Review. CoRR abs/2205.10643 (2022) - [i29]Pedram Bakhtiarifard, Christian Igel, Raghavendra Selvan:
Energy Consumption-Aware Tabular Benchmarks for Neural Architecture Search. CoRR abs/2210.06015 (2022) - [i28]Tianfang Zhang, Lei Li, Christian Igel, Stefan Oehmcke, Fabian Gieseke, Zhenming Peng:
LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing. CoRR abs/2212.09088 (2022) - 2021
- [j61]Rasmus Kær Jørgensen, Christian Igel:
Machine learning for financial transaction classification across companies using character-level word embeddings of text fields. Intell. Syst. Account. Finance Manag. 28(3): 159-172 (2021) - [j60]Christian Igel:
Data, Knowledge, and Computation. Künstliche Intell. 35(3): 247-249 (2021) - [j59]Mathias Perslev, Sune Darkner, Lykke Kempfner, Miki Nikolic, Poul Jørgen Jennum, Christian Igel:
U-Sleep: resilient high-frequency sleep staging. npj Digit. Medicine 4 (2021) - [c81]Kai Brügge, Asja Fischer, Christian Igel:
On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions. AISTATS 2021: 469-477 - [c80]Lasse Borgholt, Tycho M. S. Tax, Jakob D. Havtorn, Lars Maaløe, Christian Igel:
On Scaling Contrastive Representations for Low-Resource Speech Recognition. ICASSP 2021: 3885-3889 - [c79]Yi-Shan Wu, Andrés R. Masegosa, Stephan Sloth Lorenzen, Christian Igel, Yevgeny Seldin:
Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote. NeurIPS 2021: 12625-12636 - [i27]Svetlana Kutuzova, Oswin Krause, Douglas McCloskey, Mads Nielsen, Christian Igel:
Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts. CoRR abs/2101.07240 (2021) - [i26]Lasse Borgholt, Tycho Max Sylvester Tax, Jakob Drachmann Havtorn, Lars Maaløe, Christian Igel:
On Scaling Contrastive Representations for Low-Resource Speech Recognition. CoRR abs/2102.00850 (2021) - [i25]Lasse Borgholt, Jakob Drachmann Havtorn, Zeljko Agic, Anders Søgaard, Lars Maaløe, Christian Igel:
Do End-to-End Speech Recognition Models Care About Context? CoRR abs/2102.09928 (2021) - [i24]Stephan Sloth Lorenzen, Christian Igel, Mads Nielsen:
Information Bottleneck: Exact Analysis of (Quantized) Neural Networks. CoRR abs/2106.12912 (2021) - [i23]Yi-Shan Wu, Andrés R. Masegosa, Stephan Sloth Lorenzen, Christian Igel, Yevgeny Seldin:
Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote. CoRR abs/2106.13624 (2021) - [i22]Lasse Borgholt, Jakob Drachmann Havtorn, Mostafa Abdou, Joakim Edin, Lars Maaløe, Anders Søgaard, Christian Igel:
Do We Still Need Automatic Speech Recognition for Spoken Language Understanding? CoRR abs/2111.14842 (2021) - [i21]Stefan Oehmcke, Lei Li, Jaime C. Revenga, Thomas Nord-Larsen, Katerina Trepekli, Fabian Gieseke, Christian Igel:
Deep Learning Based 3D Point Cloud Regression for Estimating Forest Biomass. CoRR abs/2112.11335 (2021) - 2020
- [j58]Oswin Krause, Asja Fischer, Christian Igel:
Algorithms for estimating the partition function of restricted Boltzmann machines. Artif. Intell. 278 (2020) - [c78]Ürün Dogan, Aniket Anand Deshmukh, Marcin Machura, Christian Igel:
Label-Similarity Curriculum Learning. ECCV (29) 2020: 174-190 - [c77]Oswin Krause, Asja Fischer, Christian Igel:
Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract). IJCAI 2020: 5045-5049 - [c76]Lasse Borgholt, Jakob D. Havtorn, Zeljko Agic, Anders Søgaard, Lars Maaløe, Christian Igel:
Do End-to-End Speech Recognition Models Care About Context? INTERSPEECH 2020: 4352-4356 - [c75]Steffen Czolbe, Oswin Krause, Ingemar J. Cox, Christian Igel:
A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model. NeurIPS 2020 - [c74]Andrés R. Masegosa, Stephan Sloth Lorenzen, Christian Igel, Yevgeny Seldin:
Second Order PAC-Bayesian Bounds for the Weighted Majority Vote. NeurIPS 2020 - [i20]Arjun D. Desai, Francesco Calivá, Claudia Iriondo, Naji Khosravan, Aliasghar Mortazi, Sachin Jambawalikar, Drew A. Torigian, Jutta Ellermann, Mehmet Akçakaya, Ulas Bagci, Radhika Tibrewala, Io Flament, Matthew O'Brien, Sharmila Majumdar, Mathias Perslev, Akshay Pai, Christian Igel, Erik B. Dam, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Cem M. Deniz, Vladimir Juras, Ravinder Regatte, Garry Gold, Brian A. Hargreaves, Valentina Pedoia, Akshay S. Chaudhari:
The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset. CoRR abs/2004.14003 (2020) - [i19]Kai Brügge, Asja Fischer, Christian Igel:
On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions. CoRR abs/2006.14999 (2020) - [i18]Steffen Czolbe, Oswin Krause, Ingemar J. Cox, Christian Igel:
A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model. CoRR abs/2006.15057 (2020) - [i17]Andrés R. Masegosa, Stephan Sloth Lorenzen, Christian Igel, Yevgeny Seldin:
Second Order PAC-Bayesian Bounds for the Weighted Majority Vote. CoRR abs/2007.13532 (2020)
2010 – 2019
- 2019
- [j57]Stephan Sloth Lorenzen, Christian Igel, Yevgeny Seldin:
On PAC-Bayesian bounds for random forests. Mach. Learn. 108(8-9): 1503-1522 (2019) - [c73]Thorbjørn Louring Koch, Mathias Perslev, Christian Igel, Sami Sebastian Brandt:
Accurate Segmentation of Dental Panoramic Radiographs with U-NETS. ISBI 2019: 15-19 - [c72]Mathias Perslev, Erik Bjørnager Dam, Akshay Pai, Christian Igel:
One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation. MICCAI (2) 2019: 30-38 - [c71]Mauricio Orbes-Arteaga, M. Jorge Cardoso, Lauge Sørensen, Christian Igel, Sébastien Ourselin, Marc Modat, Mads Nielsen, Akshay Pai:
Knowledge Distillation for Semi-supervised Domain Adaptation. OR/MLCN@MICCAI 2019: 68-76 - [c70]Mauricio Orbes-Arteaga, Lauge Sørensen, Manuel Jorge Cardoso, Marc Modat, Sébastien Ourselin, Stefan Sommer, Mads Nielsen, Christian Igel, Akshay Pai:
PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation. Image Processing 2019: 109490S - [c69]Mathias Perslev, Michael Hejselbak Jensen, Sune Darkner, Poul Jørgen Jennum, Christian Igel:
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging. NeurIPS 2019: 4417-4428 - [i16]Mauricio Orbes-Arteaga, M. Jorge Cardoso, Lauge Sørensen, Christian Igel, Sébastien Ourselin, Marc Modat, Mads Nielsen, Akshay Pai:
Knowledge distillation for semi-supervised domain adaptation. CoRR abs/1908.07355 (2019) - [i15]Mathias Perslev, Michael Hejselbak Jensen, Sune Darkner, Poul Jørgen Jennum, Christian Igel:
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging. CoRR abs/1910.11162 (2019) - [i14]Mathias Perslev, Erik Bjørnager Dam, Akshay Pai, Christian Igel:
One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation. CoRR abs/1911.01764 (2019) - [i13]Ürün Dogan, Aniket Anand Deshmukh, Marcin Machura, Christian Igel:
Label-similarity Curriculum Learning. CoRR abs/1911.06902 (2019) - 2018
- [j56]Oswin Krause, Asja Fischer, Christian Igel:
Population-Contrastive-Divergence: Does consistency help with RBM training? Pattern Recognit. Lett. 102: 1-7 (2018) - [c68]Jan Kremer, Fei Sha, Christian Igel:
Robust Active Label Correction. AISTATS 2018: 308-316 - [c67]Ciprian Florescu, Christian Igel:
Resilient Backpropagation (Rprop) for Batch-learning in TensorFlow. ICLR (Workshop) 2018 - [c66]Fabian Gieseke, Christian Igel:
Training Big Random Forests with Little Resources. KDD 2018: 1445-1454 - [c65]Dídac Rodríguez Arbonès, Nataliia Y. Sergiienko, Boyin Ding, Oswin Krause, Christian Igel, Markus Wagner:
Sparse Incomplete LU-Decomposition for Wave Farm Designs Under Realistic Conditions. PPSN (1) 2018: 512-524 - [c64]Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes:
Bigger Buffer k-d Trees on Multi-Many-Core Systems. VECPAR 2018: 202-214 - [i12]Fabian Gieseke, Christian Igel:
Training Big Random Forests with Little Resources. CoRR abs/1802.06394 (2018) - [i11]Mauricio Orbes-Arteaga, Lauge Sørensen, Manuel Jorge Cardoso, Marc Modat, Sébastien Ourselin, Stefan Sommer, Mads Nielsen, Christian Igel, Akshay Pai:
PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation. CoRR abs/1810.01928 (2018) - [i10]Stephan Sloth Lorenzen, Christian Igel, Yevgeny Seldin:
On PAC-Bayesian Bounds for Random Forests. CoRR abs/1810.09746 (2018) - 2017
- [j55]Jan Kremer, Kristoffer Stensbo-Smidt, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel:
Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. IEEE Intell. Syst. 32(2): 16-22 (2017) - [j54]Marc Schlipsing, Jan Salmen, Marc Tschentscher, Christian Igel:
Adaptive pattern recognition in real-time video-based soccer analysis. J. Real Time Image Process. 13(2): 345-361 (2017) - [j53]Fabian Gieseke, Cosmin E. Oancea, Christian Igel:
bufferkdtree: A Python library for massive nearest neighbor queries on multi-many-core devices. Knowl. Based Syst. 120: 1-3 (2017) - [j52]Christian Igel:
Editorial - Project Reports. Künstliche Intell. 31(1): 1-4 (2017) - [c63]Niklas Thiemann, Christian Igel, Olivier Wintenberger, Yevgeny Seldin:
A Strongly Quasiconvex PAC-Bayesian Bound. ALT 2017: 466-492 - [c62]Oswin Krause, Tobias Glasmachers, Christian Igel:
Qualitative and Quantitative Assessment of Step Size Adaptation Rules. FOGA 2017: 139-148 - [c61]Fabian Gieseke, Kai Lars Polsterer, Ashish Mahabal, Christian Igel, Tom Heskes:
Massively-parallel best subset selection for ordinary least-squares regression. SSCI 2017: 1-8 - [p5]Akshay Pai, Yuan-Ching Teng, Joseph Blair, Michiel Kallenberg, Erik B. Dam, Stefan Sommer, Christian Igel, Mads Nielsen:
Characterization of Errors in Deep Learning-Based Brain MRI Segmentation. Deep Learning for Medical Image Analysis 2017: 223-242 - [e1]Christian Igel, Dirk Sudholt, Carsten Witt:
Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2017, Copenhagen, Denmark, January 12-15, 2017. ACM 2017, ISBN 978-1-4503-4651-1 [contents] - [r2]Christian Igel:
Evolutionary Kernel Learning. Encyclopedia of Machine Learning and Data Mining 2017: 465-469 - [i9]Jan Kremer, Kristoffer Stensbo-Smidt, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel:
Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. CoRR abs/1704.04650 (2017) - [i8]Carola Doerr, Christian Igel, Lothar Thiele, Xin Yao:
Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 17191). Dagstuhl Reports 7(5): 22-55 (2017) - 2016
- [j51]Ürün Dogan, Tobias Glasmachers, Christian Igel:
A Unified View on Multi-class Support Vector Classification. J. Mach. Learn. Res. 17: 45:1-45:32 (2016) - [j50]Lars Lau Rakêt, Britta Grimme, Gregor Schöner, Christian Igel, Bo Markussen:
Separating Timing, Movement Conditions and Individual Differences in the Analysis of Human Movement. PLoS Comput. Biol. 12(9) (2016) - [j49]Matthias Tuma, Valdemar Rorbech, Mark Prior, Christian Igel:
Integrated Optimization of Long-Range Underwater Signal Detection, Feature Extraction, and Classification for Nuclear Treaty Monitoring. IEEE Trans. Geosci. Remote. Sens. 54(6): 3649-3659 (2016) - [j48]Michiel Kallenberg, Kersten Petersen, Mads Nielsen, Andrew Y. Ng, Pengfei Diao, Christian Igel, Celine M. Vachon, Katharina Holland, Rikke Rass Winkel, Nico Karssemeijer, Martin Lillholm:
Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring. IEEE Trans. Medical Imaging 35(5): 1322-1331 (2016) - [c60]Kai Lars Polsterer, Fabian Gieseke, Christian Igel, Bernd Doser, Nikolaos Gianniotis:
Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs. ESANN 2016 - [c59]Oswin Krause, Tobias Glasmachers, Nikolaus Hansen, Christian Igel:
Unbounded Population MO-CMA-ES for the Bi-Objective BBOB Test Suite. GECCO (Companion) 2016: 1177-1184 - [c58]Michiel Kallenberg, Mads Nielsen, Katharina Holland, Nico Karssemeijer, Christian Igel, Martin Lillholm:
Learning Density Independent Texture Features. Digital Mammography / IWDM 2016: 299-306 - [c57]Oswin Krause, Dídac Rodríguez Arbonès, Christian Igel:
CMA-ES with Optimal Covariance Update and Storage Complexity. NIPS 2016: 370-378 - [i7]Niklas Thiemann, Christian Igel, Yevgeny Seldin:
PAC-Bayesian Aggregation without Cross-Validation. CoRR abs/1608.05610 (2016) - 2015
- [j47]Jan Kremer, Fabian Gieseke, Kim Steenstrup Pedersen, Christian Igel:
Nearest neighbor density ratio estimation for large-scale applications in astronomy. Astron. Comput. 12: 67-72 (2015) - [j46]Asja Fischer, Christian Igel:
A bound for the convergence rate of parallel tempering for sampling restricted Boltzmann machines. Theor. Comput. Sci. 598: 102-117 (2015) - [c56]Søren Frejstrup Maibing, Christian Igel:
Computational Complexity of Linear Large Margin Classification With Ramp Loss. AISTATS 2015 - [c55]Nicolae-Bogdan Sara, Rasmus Halland, Christian Igel, Stephen Alstrup:
High-School Dropout Prediction Using Machine Learning: A Danish Large-scale Study. ESANN 2015 - [c54]Oswin Krause, Christian Igel:
A More Efficient Rank-one Covariance Matrix Update for Evolution Strategies. FOGA 2015: 129-136 - [i6]Oswin Krause, Asja Fischer, Christian Igel:
Population-Contrastive-Divergence: Does Consistency help with RBM training? CoRR abs/1510.01624 (2015) - [i5]Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes:
Bigger Buffer k-d Trees on Multi-Many-Core Systems. CoRR abs/1512.02831 (2015) - [i4]Benjamin Doerr, Nikolaus Hansen, Christian Igel, Lothar Thiele:
Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211). Dagstuhl Reports 5(5): 57-91 (2015) - 2014
- [j45]Asja Fischer, Christian Igel:
Training restricted Boltzmann machines: An introduction. Pattern Recognit. 47(1): 25-39 (2014) - [j44]Jan Kremer, Kim Steenstrup Pedersen, Christian Igel:
Active learning with support vector machines. WIREs Data Mining Knowl. Discov. 4(4): 313-326 (2014) - [c53]Fabian Gieseke, Kai Lars Polsterer, Cosmin Eugen Oancea, Christian Igel:
Speedy greedy feature selection: Better redshift estimation via massive parallelism. ESANN 2014 - [c52]Fabian Gieseke, Justin Heinermann, Cosmin E. Oancea, Christian Igel:
Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs. ICML 2014: 172-180 - [c51]Dídac R. Arbonès, Henrik G. Jensen, Annika Loft, Per Munck af Rosenschöld, Anders E. Hansen, Christian Igel, Sune Darkner:
Automatic FDG-PET-based tumor and metastatic lymph node segmentation in cervical cancer. Image Processing 2014: 903441 - [p4]Christian Igel:
No Free Lunch Theorems: Limitations and Perspectives of Metaheuristics. Theory and Principled Methods for the Design of Metaheuristics 2014: 1-23 - 2013
- [j43]Karl Bringmann, Tobias Friedrich, Christian Igel, Thomas Voß:
Speeding up many-objective optimization by Monte Carlo approximations. Artif. Intell. 204: 22-29 (2013) - [j42]Marc Schlipsing, Jan Salmen, Christian Igel:
Echtzeit-Videoanalyse im Fußball - Ein Live-System zum Spieler-Tracking. Künstliche Intell. 27(3): 235-240 (2013) - [j41]Kai Brügge, Asja Fischer, Christian Igel:
The flip-the-state transition operator for restricted Boltzmann machines. Mach. Learn. 93(1): 53-69 (2013) - [j40]Joselene Marques, Christian Igel, Martin Lillholm, Erik B. Dam:
Linear feature selection in texture analysis - A PLS based method. Mach. Vis. Appl. 24(7): 1435-1444 (2013) - [j39]Christian Igel:
A Note on Generalization Loss When Evolving Adaptive Pattern Recognition Systems. IEEE Trans. Evol. Comput. 17(3): 345-352 (2013) - [c50]Fabian Gieseke, Tapio Pahikkala, Christian Igel:
Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification. ACML 2013: 62-71 - [c49]Søren Dahlgaard, Christian Igel, Mikkel Thorup:
Nearest neighbor classification using bottom-k sketches. IEEE BigData 2013: 28-34 - [c48]Kristoffer Stensbo-Smidt, Christian Igel, Andrew Zirm, Kim Steenstrup Pedersen:
Nearest neighbour regression outperforms model-based prediction of specific star formation rate. IEEE BigData 2013: 141-144 - [c47]Adhish Prasoon, Christian Igel, Marco Loog, François Lauze, Erik B. Dam, Mads Nielsen:
Femoral cartilage segmentation in Knee MRI scans using two stage voxel classification. EMBC 2013: 5469-5472 - [c46]Kim Steenstrup Pedersen, Kristoffer Stensbo-Smidt, Andrew Zirm, Christian Igel:
Shape Index Descriptors Applied to Texture-Based Galaxy Analysis. ICCV 2013: 2440-2447 - [c45]Oswin Krause, Asja Fischer, Tobias Glasmachers, Christian Igel:
Approximation properties of DBNs with binary hidden units and real-valued visible units. ICML (1) 2013: 419-426 - [c44]Sebastian Houben, Johannes Stallkamp, Jan Salmen, Marc Schlipsing, Christian Igel:
Detection of traffic signs in real-world images: The German traffic sign detection benchmark. IJCNN 2013: 1-8 - [c43]Adhish Prasoon, Kersten Petersen, Christian Igel, François Lauze, Erik Dam, Mads Nielsen:
Deep Feature Learning for Knee Cartilage Segmentation Using a Triplanar Convolutional Neural Network. MICCAI (2) 2013: 246-253 - 2012
- [j38]Oliver Kramer, Christian Igel, Günter Rudolph:
Evolutionary kernel machines. Evol. Intell. 5(3): 151-152 (2012) - [j37]Christian Igel:
Learning ∈ Artificial Intelligence ∩ Cognitive Technologies ∩ Neural Computation ∩ ... Künstliche Intell. 26(3): 209-212 (2012) - [j36]Johannes Stallkamp, Marc Schlipsing, Jan Salmen, Christian Igel:
Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition. Neural Networks 32: 323-332 (2012) - [j35]Johannes Stallkamp, Marc Schlipsing, Jan Salmen, Christian Igel:
Introduction to the Special Issue on Machine Learning for Traffic Sign Recognition. IEEE Trans. Intell. Transp. Syst. 13(4): 1481-1483 (2012) - [c42]Asja Fischer, Christian Igel:
An Introduction to Restricted Boltzmann Machines. CIARP 2012: 14-36 - [c41]C. Chen, Lauge Sørensen, François Lauze, Christian Igel, Marco Loog, Aasa Feragen, Marleen de Bruijne, Mads Nielsen:
Towards exaggerated emphysema stereotypes. Computer-Aided Diagnosis 2012: 83150Q - [c40]Adhish Prasoon, Christian Igel, Marco Loog, François Lauze, Erik Dam, Mads Nielsen:
Cascaded classifier for large-scale data applied to automatic segmentation of articular cartilage. Image Processing 2012: 83144V - [c39]Ürün Dogan, Tobias Glasmachers, Christian Igel:
A Note on Extending Generalization Bounds for Binary Large-Margin Classifiers to Multiple Classes. ECML/PKDD (1) 2012: 122-129 - 2011
- [j34]Asja Fischer, Christian Igel:
Bounding the Bias of Contrastive Divergence Learning. Neural Comput. 23(3): 664-673 (2011) - [j33]Holger Blume, Bernd Bischl, Martin Botteck, Christian Igel, Rainer Martin, Günther Rötter, Günter Rudolph, Wolfgang M. Theimer, Igor Vatolkin, Claus Weihs:
Huge Music Archives on Mobile Devices. IEEE Signal Process. Mag. 28(4): 24-39 (2011) - [c38]Chen Chen, François Lauze, Christian Igel, Aasa Feragen, Marco Loog, Mads Nielsen:
Towards exaggerated image stereotypes. ACPR 2011: 422-426 - [c37]Matthias Tuma, Christian Igel:
Improved Working Set Selection for LaRank. CAIP (1) 2011: 327-334 - [c36]Jan Salmen, Lukas Caup, Christian Igel:
Real-Time Estimation of Optical Flow Based on Optimized Haar Wavelet Features. EMO 2011: 448-461 - [c35]Asja Fischer, Christian Igel:
Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives. ESANN 2011 - [c34]Verena Heidrich-Meisner, Christian Igel:
Non-linearly increasing resampling in racing algorithms. ESANN 2011 - [c33]Tobias Friedrich, Karl Bringmann, Thomas Voß, Christian Igel:
The logarithmic hypervolume indicator. FOGA 2011: 81-92 - [c32]Johannes Stallkamp, Marc Schlipsing, Jan Salmen, Christian Igel:
The German Traffic Sign Recognition Benchmark: A multi-class classification competition. IJCNN 2011: 1453-1460 - 2010
- [j32]Benjamin Roeschies, Christian Igel:
Structure optimization of reservoir networks. Log. J. IGPL 18(5): 635-669 (2010) - [j31]Tobias Glasmachers, Christian Igel:
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters. IEEE Trans. Pattern Anal. Mach. Intell. 32(8): 1522-1528 (2010) - [j30]Valentin Markounikau, Christian Igel, Amiram Grinvald, Dirk Jancke:
A Dynamic Neural Field Model of Mesoscopic Cortical Activity Captured with Voltage-Sensitive Dye Imaging. PLoS Comput. Biol. 6(9) (2010) - [j29]Jan Salmen, Marc Schlipsing, Christian Igel:
Efficient update of the covariance matrix inverse in iterated linear discriminant analysis. Pattern Recognit. Lett. 31(13): 1903-1907 (2010) - [j28]Rolf P. Würtz, Kirstie L. Bellman, Hartmut Schmeck, Christian Igel:
Editorial: Special issue on organic computing. ACM Trans. Auton. Adapt. Syst. 5(3): 9:1-9:3 (2010) - [c31]Thomas Voß, Nikolaus Hansen, Christian Igel:
Improved step size adaptation for the MO-CMA-ES. GECCO 2010: 487-494 - [c30]Thomas Voß, Tobias Friedrich, Karl Bringmann, Christian Igel:
Scaling up indicator-based MOEAs by approximating the least hypervolume contributor: a preliminary study. GECCO (Companion) 2010: 1975-1978 - [c29]Asja Fischer, Christian Igel:
Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines. ICANN (3) 2010: 208-217 - [c28]Matthias Tuma, Christian Igel, Mark Prior:
Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets. ICPR 2010: 1011-1014 - [c27]Thomas Voß, Heike Trautmann, Christian Igel:
New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization. PPSN (2) 2010: 260-269 - [r1]Christian Igel:
Evolutionary Kernel Learning. Encyclopedia of Machine Learning 2010: 369-373
2000 – 2009
- 2009
- [j27]Verena Heidrich-Meisner, Christian Igel:
Neuroevolution strategies for episodic reinforcement learning. J. Algorithms 64(4): 152-168 (2009) - [j26]Christian Igel:
Gasteditorial Reinforcement Learning. Künstliche Intell. 23(3): 4 (2009) - [j25]Tom Schaul, Daan Wierstra, Faustino J. Gomez, Jürgen Schmidhuber, Christian Igel, Julian Togelius:
Ontogenetic and Phylogenetic Reinforcement Learning. Künstliche Intell. 23(3): 30-33 (2009) - [j24]Thorsten Suttorp, Nikolaus Hansen, Christian Igel:
Efficient covariance matrix update for variable metric evolution strategies. Mach. Learn. 75(2): 167-197 (2009) - [c26]Thomas Voß, Nikolaus Hansen, Christian Igel:
Recombination for Learning Strategy Parameters in the MO-CMA-ES. EMO 2009: 155-168 - [c25]Verena Heidrich-Meisner, Christian Igel:
Uncertainty handling CMA-ES for reinforcement learning. GECCO 2009: 1211-1218 - [c24]Verena Heidrich-Meisner, Christian Igel:
Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search. ICML 2009: 401-408 - 2008
- [j23]Christian Igel, Verena Heidrich-Meisner, Tobias Glasmachers:
Shark. J. Mach. Learn. Res. 9: 993-996 (2008) - [j22]Tobias Glasmachers, Christian Igel:
Second-Order SMO Improves SVM Online and Active Learning. Neural Comput. 20(2): 374-382 (2008) - [j21]Susanne Winter, Bernhard Brendel, Ioannis Pechlivanis, Kirsten Schmieder, Christian Igel:
Registration of CT and Intraoperative 3-D Ultrasound Images of the Spine Using Evolutionary and Gradient-Based Methods. IEEE Trans. Evol. Comput. 12(3): 284-296 (2008) - [c23]Thomas Voß, Nicola Beume, Günter Rudolph, Christian Igel:
Scalarization versus indicator-based selection in multi-objective CMA evolution strategies. IEEE Congress on Evolutionary Computation 2008: 3036-3043 - [c22]Verena Heidrich-Meisner, Christian Igel:
Similarities and differences between policy gradient methods and evolution strategies. ESANN 2008: 149-154 - [c21]Thorsten Suttorp, Christian Igel:
Approximation of Gaussian process regression models after training. ESANN 2008: 427-432 - [c20]Verena Heidrich-Meisner, Christian Igel:
Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem. EWRL 2008: 136-150 - [c19]Tobias Glasmachers, Christian Igel:
Uncertainty Handling in Model Selection for Support Vector Machines. PPSN 2008: 185-194 - [c18]Verena Heidrich-Meisner, Christian Igel:
Evolution Strategies for Direct Policy Search. PPSN 2008: 428-437 - [p3]Christian Igel, Bernhard Sendhoff:
Genesis of Organic Computing Systems: Coupling Evolution and Learning. Organic Computing 2008: 141-166 - 2007
- [j20]Christian Igel, Nikolaus Hansen, Stefan Roth:
Covariance Matrix Adaptation for Multi-objective Optimization. Evol. Comput. 15(1): 1-28 (2007) - [j19]Jens Niehaus, Christian Igel, Wolfgang Banzhaf:
Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database. Evol. Comput. 15(2): 199-221 (2007) - [j18]Britta Mersch, Tobias Glasmachers, Peter Meinicke, Christian Igel:
Evolutionary Optimization of Sequence Kernels for Detection of bacterial gene Starts. Int. J. Neural Syst. 17(5): 369-381 (2007) - [j17]Christian Igel, Tobias Glasmachers, Britta Mersch, Nico Pfeifer, Peter Meinicke:
Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection. IEEE ACM Trans. Comput. Biol. Bioinform. 4(2): 216-226 (2007) - [c17]Christian Igel, Thorsten Suttorp, Nikolaus Hansen:
Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES. EMO 2007: 171-185 - [c16]Verena Heidrich-Meisner, Martin Lauer, Christian Igel, Martin A. Riedmiller:
Reinforcement learning in a nutshell. ESANN 2007: 277-288 - [c15]Jan Salmen, Thorsten Suttorp, Johann Edelbrunner, Christian Igel:
Evolutionary Optimization ofWavelet Feature Sets for Real-Time Pedestrian Classification. HIS 2007: 222-227 - [c14]Thorsten Suttorp, Christian Igel:
Resilient Approximation of Kernel Classifiers. ICANN (1) 2007: 139-148 - 2006
- [j16]Tobias Glasmachers, Christian Igel:
Maximum-Gain Working Set Selection for SVMs. J. Mach. Learn. Res. 7: 1437-1466 (2006) - [c13]Christian Igel, Thorsten Suttorp, Nikolaus Hansen:
A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies. GECCO 2006: 453-460 - [c12]Britta Mersch, Tobias Glasmachers, Peter Meinicke, Christian Igel:
Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. ICANN (2) 2006: 827-836 - [p2]Thorsten Suttorp, Christian Igel:
Multi-Objective Optimization of Support Vector Machines. Multi-Objective Machine Learning 2006: 199-220 - [p1]Stefan Roth, Alexander Rainer Tassilo Gepperth, Christian Igel:
Multi-Objective Neural Network Optimization for Visual Object Detection. Multi-Objective Machine Learning 2006: 629-655 - 2005
- [j15]Antonio Pellecchia, Christian Igel, Johann Edelbrunner, Gregor Schöner:
Making Driver Modeling Attractive. IEEE Intell. Syst. 20(2): 8-12 (2005) - [j14]Frauke Friedrichs, Christian Igel:
Evolutionary tuning of multiple SVM parameters. Neurocomputing 64: 107-117 (2005) - [j13]Tobias Glasmachers, Christian Igel:
Gradient-Based Adaptation of General Gaussian Kernels. Neural Comput. 17(10): 2099-2105 (2005) - [c11]Susanne Winter, Bernhard Brendel, Christian Igel:
Registrierung von Knochen in 3D-Ultraschall- und CT-Daten: Vergleich verschiedener Optimierungsverfahren. Bildverarbeitung für die Medizin 2005: 345-349 - [c10]Christian Igel:
Multi-objective Model Selection for Support Vector Machines. EMO 2005: 534-546 - [c9]Christian Igel, Bernhard Sendhoff:
Synergies between Evolutionary and Neural Computation. ESANN 2005: 241-252 - 2004
- [j12]Stefan Schneider, Christian Igel, Christian Klaes, Hubert R. Dinse, Jan C. Wiemer:
Evolutionary Adaptation of Nonlinear Dynamical Systems in Computational Neuroscience. Genet. Program. Evolvable Mach. 5(2): 215-227 (2004) - [j11]Stefan Wiegand, Christian Igel, Uwe Handmann:
Evolutionary Multi-Objective Optimisation Of Neural Networks For Face Detection. Int. J. Comput. Intell. Appl. 4(3): 237-254 (2004) - [j10]Christian Igel, Marc Toussaint:
A No-Free-Lunch theorem for non-uniform distributions of target functions. J. Math. Model. Algorithms 3(4): 313-322 (2004) - [j9]Christian Igel, Karl-Heinz Temme:
The chaining syllogism in fuzzy logic. IEEE Trans. Fuzzy Syst. 12(6): 849-853 (2004) - [c8]Stefan Wiegand, Christian Igel, Uwe Handmann:
Evolutionary Optimization of Neural Networks for Face Detection. ESANN 2004: 139-144 - [c7]Frauke Friedrichs, Christian Igel:
Evolutionary tuning of multiple SVM parameters. ESANN 2004: 519-524 - [c6]Christian Igel, Jutta Gebert, Thomas Wiebringhaus:
Protein fold class prediction using neural networks with tailored early-stopping. IJCNN 2004: 1693-1697 - 2003
- [b1]Christian Igel:
Beiträge zum Entwurf neuronaler Systeme. Bielefeld University, Germany, Shaker 2003, ISBN 978-3-8322-1103-5, pp. 1-230 - [j8]Christian Igel, Michael Hüsken:
Empirical evaluation of the improved Rprop learning algorithms. Neurocomputing 50: 105-123 (2003) - [j7]Christian Igel, Martin Kreutz:
Operator adaptation in evolutionary computation and its application to structure optimization of neural networks. Neurocomputing 55(1-2): 347-361 (2003) - [j6]Christian Igel, Marc Toussaint:
On classes of functions for which No Free Lunch results hold. Inf. Process. Lett. 86(6): 317-321 (2003) - [j5]Christian Igel, Marc Toussaint:
Neutrality and self-adaptation. Nat. Comput. 2(2): 117-132 (2003) - [j4]Thomas Bücher, Cristóbal Curio, Johann Edelbrunner, Christian Igel, David Kastrup, Iris Leefken, Gesa Lorenz, Axel Steinhage, Werner von Seelen:
Image processing and behavior planning for intelligent vehicles. IEEE Trans. Ind. Electron. 50(1): 62-75 (2003) - [c5]Christian Igel:
Neuroevolution for reinforcement learning using evolution strategies. IEEE Congress on Evolutionary Computation 2003: 2588-2595 - [i3]Christian Igel, Marc Toussaint:
Recent Results on No-Free-Lunch Theorems for Optimization. CoRR cs.NE/0303032 (2003) - 2002
- [j3]Christian Igel, Werner von Seelen, Wolfram Erlhagen, Dirk Jancke:
Evolving field models for inhibition effects in early vision. Neurocomputing 44-46: 467-472 (2002) - [j2]Christian Igel, Peter Stagge:
Effects of phenotypic redundancy in structure optimization. IEEE Trans. Evol. Comput. 6(1): 74-85 (2002) - [c4]Marc Toussaint, Christian Igel:
Neutrality: a necessity for self-adaptation. IEEE Congress on Evolutionary Computation 2002: 1354-1359 - [c3]Michael Hüsken, Christian Igel:
Balancing Learning And Evolution. GECCO 2002: 391-398 - [i2]Marc Toussaint, Christian Igel:
Neutrality: A Necessity for Self-Adaptation. CoRR nlin.AO/0204038 (2002) - 2001
- [j1]Christian Igel, Wolfram Erlhagen, Dirk Jancke:
Optimization of dynamic neural fields. Neurocomputing 36(1-4): 225-233 (2001) - [i1]Christian Igel, Marc Toussaint:
On Classes of Functions for which No Free Lunch Results Hold. CoRR cs.NE/0108011 (2001)
1990 – 1999
- 1999
- [c2]Christian Igel, Martin Kreutz:
Using fitness distributions to improve the evolution of learning structures. CEC 1999: 1902-1909 - 1997
- [c1]Christian Igel, Karl-Heinz Temme:
Chaining Syllogism Applied to Fuzzy IF-THEN Rules and Rule Bases. Fuzzy Days 1997: 179-188
Coauthor Index
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