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ORCIDBarbara Hammer
Person information
- affiliation: Bielefeld University, Faculty of Technology
- affiliation: Clausthal University of Technology, Computer Science Institute
- affiliation: University of Osnabrück, Institute of Computer Science
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Books and Theses
- 1999
[b2]Barbara Hammer:
Learning with recurrent neural networks. University of Osnabrück, Germany, 1999, pp. 1-124- 1996
- [b1]Volker Sperschneider, Barbara Hammer:
Theoretische Informatik - eine problemorientierte Einführung. Springer-Lehrbuch, Springer 1996, ISBN 978-3-540-60860-8, pp. I-VIII, 1-193
Journal Articles
- 2023
- [j123]Jonathan Jakob, André Artelt, Martina Hasenjäger, Barbara Hammer
:
Interpretable SAM-kNN Regressor for Incremental Learning on High-Dimensional Data Streams. Appl. Artif. Intell. 37(1) (2023) - [j122]Dominik Stallmann, Barbara Hammer:
Unsupervised Cyclic Siamese Networks Automating Cell Imagery Analysis. Algorithms 16(4): 205 (2023) - [j121]Aleksei Liuliakov, Luca Hermes, Barbara Hammer:
AutoML technologies for the identification of sparse classification and outlier detection models. Appl. Soft Comput. 133: 109942 (2023) - [j120]Ulrike Kuhl, André Artelt, Barbara Hammer:
Let's go to the Alien Zoo: Introducing an experimental framework to study usability of counterfactual explanations for machine learning. Frontiers Comput. Sci. 5 (2023) - [j119]Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer:
Model-based explanations of concept drift. Neurocomputing 555: 126640 (2023) - [j118]André Artelt, Roel Visser, Barbara Hammer:
"I do not know! but why?" - Local model-agnostic example-based explanations of reject. Neurocomputing 558: 126722 (2023) - [j117]Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer:
Incremental permutation feature importance (iPFI): towards online explanations on data streams. Mach. Learn. 112(12): 4863-4903 (2023) - [j116]Philip Kenneweg, Dominik Stallmann, Barbara Hammer:
Novel transfer learning schemes based on Siamese networks and synthetic data. Neural Comput. Appl. 35(11): 8423-8436 (2023) - [j115]André Artelt, Fabian Hinder, Valerie Vaquet, Robert Feldhans, Barbara Hammer:
Contrasting Explanations for Understanding and Regularizing Model Adaptations. Neural Process. Lett. 55(5): 5273-5297 (2023) - [j114]Johannes Kummert, Alexander Schulz, Barbara Hammer:
Metric Learning with Self-Adjusting Memory for Explaining Feature Drift. SN Comput. Sci. 4(4): 376 (2023) - 2022
- [j113]André Artelt, Barbara Hammer:
Efficient computation of counterfactual explanations and counterfactual metrics of prototype-based classifiers. Neurocomputing 470: 304-317 (2022) - [j112]Jan Philip Göpfert, Heiko Wersing, Barbara Hammer:
Interpretable Locally Adaptive Nearest Neighbors. Neurocomputing 470: 344-351 (2022) - [j111]Benjamin Paaßen, Alexander Schulz, Barbara Hammer:
Reservoir stack machines. Neurocomputing 470: 352-364 (2022) - [j110]Valerie Vaquet, Patrick Menz, Udo Seiffert, Barbara Hammer:
Investigating intensity and transversal drift in hyperspectral imaging data. Neurocomputing 505: 68-79 (2022) - [j109]Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier:
Agnostic Explanation of Model Change based on Feature Importance. Künstliche Intell. 36(3): 211-224 (2022) - [j108]Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl:
Supervised learning in the presence of concept drift: a modelling framework. Neural Comput. Appl. 34(1): 101-118 (2022) - [j107]Jan Philip Göpfert, Ulrike Kuhl, Lukas Hindemith, Heiko Wersing, Barbara Hammer:
Intuitiveness in Active Teaching. IEEE Trans. Hum. Mach. Syst. 52(3): 458-467 (2022) - [j106]Benjamin Paaßen, Alexander Schulz, Terrence C. Stewart, Barbara Hammer:
Reservoir Memory Machines as Neural Computers. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2575-2585 (2022) - 2021
- [j105]Florian Buckermann, Nils Klement, Oliver Beyer, Andreas Hütten, Barbara Hammer:
Automating the optical identification of abrasive wear on electrical contact pins. Autom. 69(10): 903-914 (2021) - [j104]Dominik Stallmann, Jan Philip Göpfert, Julian Schmitz, Alexander Grünberger, Barbara Hammer:
Towards an automatic analysis of CHO-K1 suspension growth in microfluidic single-cell cultivation. Bioinform. 37(20): 3632-3639 (2021) - [j103]Malte Schilling, Andrew Melnik, Frank W. Ohl, Helge J. Ritter, Barbara Hammer:
Decentralized control and local information for robust and adaptive decentralized Deep Reinforcement Learning. Neural Networks 144: 699-725 (2021) - [j102]Johannes Kummert, Alexander Schulz, Tim Redick, Nassim Ayoub, Ali Modabber, Dirk Abel, Barbara Hammer:
Efficient Reject Options for Particle Filter Object Tracking in Medical Applications. Sensors 21(6): 2114 (2021) - [j101]Katharina J. Rohlfing, Philipp Cimiano, Ingrid Scharlau, Tobias Matzner, Heike M. Buhl, Hendrik Buschmeier, Elena Esposito, Angela Grimminger, Barbara Hammer, Reinhold Häb-Umbach, Ilona Horwath, Eyke Hüllermeier, Friederike Kern, Stefan Kopp, Kirsten Thommes, Axel-Cyrille Ngonga Ngomo, Carsten Schulte, Henning Wachsmuth, Petra Wagner, Britta Wrede:
Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems. IEEE Trans. Cogn. Dev. Syst. 13(3): 717-728 (2021) - 2020
- [j100]Babak Hosseini, Romain Montagné, Barbara Hammer:
Deep-Aligned Convolutional Neural Network for Skeleton-Based Action Recognition and Segmentation. Data Sci. Eng. 5(2): 126-139 (2020) - [j99]Lukas Pfannschmidt, Jonathan Jakob, Fabian Hinder, Michael Biehl, Peter Tiño, Barbara Hammer:
Feature relevance determination for ordinal regression in the context of feature redundancies and privileged information. Neurocomputing 416: 266-279 (2020) - [j98]Lazaros S. Iliadis, Vera Kurková, Barbara Hammer:
Brain-inspired computing and machine learning. Neural Comput. Appl. 32(11): 6641-6643 (2020) - [j97]Johannes Brinkrolf, Barbara Hammer:
Time integration and reject options for probabilistic output of pairwise LVQ. Neural Comput. Appl. 32(24): 18009-18022 (2020) - 2019
- [j96]Johannes Brinkrolf, Christina Göpfert, Barbara Hammer:
Differential privacy for learning vector quantization. Neurocomputing 342: 125-136 (2019) - 2018
- [j95]Johannes Brinkrolf, Barbara Hammer:
Interpretable machine learning with reject option. Autom. 66(4): 283-290 (2018) - [j94]Markus Lux, Ryan Remy Brinkman, Cédric Chauve, Adam Laing, Anna Lorenc, Lucie Abeler-Dörner, Barbara Hammer:
flowLearn: fast and precise identification and quality checking of cell populations in flow cytometry. Bioinform. 34(13): 2245-2253 (2018) - [j93]Felix Hülsmann, Jan Philip Göpfert, Barbara Hammer, Stefan Kopp, Mario Botsch:
Classification of motor errors to provide real-time feedback for sports coaching in virtual reality - A case study in squats and Tai Chi pushes. Comput. Graph. 76: 47-59 (2018) - [j92]Nelishia Pillay, Rong Qu, Dipti Srinivasan, Barbara Hammer, Kenneth Sörensen:
Automated Design of Machine Learning and Search Algorithms [Guest Editorial]. IEEE Comput. Intell. Mag. 13(2): 16-17 (2018) - [j91]Michiel Straat, Fthi Abadi, Christina Göpfert, Barbara Hammer, Michael Biehl:
Statistical Mechanics of On-Line Learning Under Concept Drift. Entropy 20(10): 775 (2018) - [j90]Viktor Losing, Barbara Hammer, Heiko Wersing:
Incremental on-line learning: A review and comparison of state of the art algorithms. Neurocomputing 275: 1261-1274 (2018) - [j89]Christina Göpfert, Lukas Pfannschmidt, Jan Philip Göpfert, Barbara Hammer:
Interpretation of linear classifiers by means of feature relevance bounds. Neurocomputing 298: 69-79 (2018) - [j88]Benjamin Paaßen, Alexander Schulz, Janne Hahne, Barbara Hammer:
Expectation maximization transfer learning and its application for bionic hand prostheses. Neurocomputing 298: 122-133 (2018) - [j87]Viktor Losing, Barbara Hammer, Heiko Wersing:
Tackling heterogeneous concept drift with the Self-Adjusting Memory (SAM). Knowl. Inf. Syst. 54(1): 171-201 (2018) - [j86]Benjamin Paaßen, Christina Göpfert, Barbara Hammer:
Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces. Neural Process. Lett. 48(2): 669-689 (2018) - 2017
- [j85]Alexander Schulz, Johannes Brinkrolf, Barbara Hammer:
Efficient kernelisation of discriminative dimensionality reduction. Neurocomputing 268: 34-41 (2017) - [j84]Haibo He, Robert Haas, Jun Fu, Barbara Hammer, Daniel W. C. Ho, Fakhri Karray, Dhireesha Kudithipudi, José Antonio Lozano, Teresa Bernarda Ludermir, Jacek Mandziuk, Stefano Melacci, Antonio Paiva, Hong Qiao, Alain Rakotomamonjy, Shiliang Sun, Johan A. K. Suykens, Meng Wang:
Editorial: A Successful Year and Looking Forward to 2017 and Beyond. IEEE Trans. Neural Networks Learn. Syst. 28(1): 2-7 (2017) - 2016
- [j83]Markus Lux, Jan Krüger, Christian Rinke, Irena Maus, Andreas Schlüter, Tanja Woyke, Alexander Sczyrba, Barbara Hammer:
acdc - Automated Contamination Detection and Confidence estimation for single-cell genome data. BMC Bioinform. 17: 543:1-543:11 (2016) - [j82]Benjamin Paaßen, Bassam Mokbel, Barbara Hammer:
Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. Neurocomputing 192: 3-13 (2016) - [j81]Lydia Fischer, Barbara Hammer, Heiko Wersing:
Optimal local rejection for classifiers. Neurocomputing 214: 445-457 (2016) - [j80]Frank-Michael Schleif, Barbara Hammer, Javier Gonzalez Monroy, Javier González Jiménez, José-Luis Blanco-Claraco, Michael Biehl, Nicolai Petkov:
Odor recognition in robotics applications by discriminative time-series modeling. Pattern Anal. Appl. 19(1): 207-220 (2016) - 2015
- [j79]Frank-Michael Schleif, Xibin Zhu, Barbara Hammer:
Sparse conformal prediction for dissimilarity data. Ann. Math. Artif. Intell. 74(1-2): 95-116 (2015) - [j78]Andrej Gisbrecht, Alexander Schulz, Barbara Hammer:
Parametric nonlinear dimensionality reduction using kernel t-SNE. Neurocomputing 147: 71-82 (2015) - [j77]Daniela Hofmann, Andrej Gisbrecht, Barbara Hammer:
Efficient approximations of robust soft learning vector quantization for non-vectorial data. Neurocomputing 147: 96-106 (2015) - [j76]David Nebel, Barbara Hammer, Kathleen Frohberg, Thomas Villmann:
Median variants of learning vector quantization for learning of dissimilarity data. Neurocomputing 169: 295-305 (2015) - [j75]Bassam Mokbel, Benjamin Paaßen, Frank-Michael Schleif, Barbara Hammer:
Metric learning for sequences in relational LVQ. Neurocomputing 169: 306-322 (2015) - [j74]Lydia Fischer, Barbara Hammer, Heiko Wersing:
Efficient rejection strategies for prototype-based classification. Neurocomputing 169: 334-342 (2015) - [j73]Barbara Hammer, Marc Toussaint:
Special Issue on Autonomous Learning. Künstliche Intell. 29(4): 323-327 (2015) - [j72]Oliver Walter, Reinhold Haeb-Umbach, Bassam Mokbel, Benjamin Paaßen, Barbara Hammer:
Autonomous Learning of Representations. Künstliche Intell. 29(4): 339-351 (2015) - [j71]Sebastian Gross, Bassam Mokbel, Barbara Hammer, Niels Pinkwart:
Learning Feedback in Intelligent Tutoring Systems - Report of the FIT Project, Conducted from December 2011 to March 2015. Künstliche Intell. 29(4): 413-418 (2015) - [j70]Alexander Schulz, Andrej Gisbrecht, Barbara Hammer:
Using Discriminative Dimensionality Reduction to Visualize Classifiers. Neural Process. Lett. 42(1): 27-54 (2015) - [j69]Andrej Gisbrecht, Barbara Hammer:
Data visualization by nonlinear dimensionality reduction. WIREs Data Mining Knowl. Discov. 5(2): 51-73 (2015) - 2014
- [j68]Yaochu Jin, Barbara Hammer:
Computational Intelligence in Big Data [Guest Editorial]. IEEE Comput. Intell. Mag. 9(3): 12-13 (2014) - [j67]Sebastian Gross, Bassam Mokbel, Benjamin Paaßen, Barbara Hammer, Niels Pinkwart:
Example-based feedback provision using structured solution spaces. Int. J. Learn. Technol. 9(3): 248-280 (2014) - [j66]Barbara Hammer, Thomas Villmann:
Special issue on new challenges in neural computation 2012. Neurocomputing 131: 1 (2014) - [j65]Barbara Hammer, Daniela Hofmann, Frank-Michael Schleif, Xibin Zhu:
Learning vector quantization for (dis-)similarities. Neurocomputing 131: 43-51 (2014) - [j64]Daniela Hofmann, Frank-Michael Schleif, Benjamin Paaßen, Barbara Hammer:
Learning interpretable kernelized prototype-based models. Neurocomputing 141: 84-96 (2014) - [j63]Xibin Zhu, Frank-Michael Schleif, Barbara Hammer:
Adaptive conformal semi-supervised vector quantization for dissimilarity data. Pattern Recognit. Lett. 49: 138-145 (2014) - 2013
- [j62]Barbara Hammer, Daniel A. Keim, Neil D. Lawrence, Guy Lebanon:
Preface: Intelligent interactive data visualization. Data Min. Knowl. Discov. 27(1): 1-3 (2013) - [j61]Bassam Mokbel, Wouter Lueks, Andrej Gisbrecht, Barbara Hammer:
Visualizing the quality of dimensionality reduction. Neurocomputing 112: 109-123 (2013) - 2012
- [j60]Andrej Gisbrecht, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu, Barbara Hammer:
Linear Time Relational Prototype Based Learning. Int. J. Neural Syst. 22(5) (2012) - [j59]Xibin Zhu, Andrej Gisbrecht, Frank-Michael Schleif, Barbara Hammer:
Approximation techniques for clustering dissimilarity data. Neurocomputing 90: 72-84 (2012) - [j58]Marika Kästner, Barbara Hammer, Michael Biehl, Thomas Villmann:
Functional relevance learning in generalized learning vector quantization. Neurocomputing 90: 85-95 (2012) - [j57]Barbara Hammer:
Special Issue on Neural Learning Paradigms. Künstliche Intell. 26(4): 329-332 (2012) - [j56]Barbara Hammer:
Challenges in Neural Computation. Künstliche Intell. 26(4): 333-340 (2012) - [j55]Kerstin Bunte, Michael Biehl, Barbara Hammer:
A General Framework for Dimensionality-Reducing Data Visualization Mapping. Neural Comput. 24(3): 771-804 (2012) - [j54]Kerstin Bunte, Petra Schneider, Barbara Hammer, Frank-Michael Schleif, Thomas Villmann, Michael Biehl:
Limited Rank Matrix Learning, discriminative dimension reduction and visualization. Neural Networks 26: 159-173 (2012) - 2011
- [j53]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer, Petra Schneider:
Efficient Kernelized Prototype Based Classification. Int. J. Neural Syst. 21(6): 443-457 (2011) - [j52]Banchar Arnonkijpanich, Alexander Hasenfuss, Barbara Hammer:
Local matrix adaptation in topographic neural maps. Neurocomputing 74(4): 522-539 (2011) - [j51]Kerstin Bunte, Barbara Hammer, Thomas Villmann, Michael Biehl, Axel Wismüller:
Neighbor embedding XOM for dimension reduction and visualization. Neurocomputing 74(9): 1340-1350 (2011) - [j50]Andrej Gisbrecht, Barbara Hammer:
Relevance learning in generative topographic mapping. Neurocomputing 74(9): 1351-1358 (2011) - [j49]Andrej Gisbrecht, Bassam Mokbel, Barbara Hammer:
Relational generative topographic mapping. Neurocomputing 74(9): 1359-1371 (2011) - 2010
- [j48]Marco Gori, Barbara Hammer, Pascal Hitzler, Guenther Palm:
Perspectives and challenges for recurrent neural network training. Log. J. IGPL 18(5): 617-619 (2010) - [j47]Kerstin Bunte, Barbara Hammer, Axel Wismüller, Michael Biehl:
Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data. Neurocomputing 73(7-9): 1074-1092 (2010) - [j46]Tina Geweniger, Dietlind Zühlke, Barbara Hammer, Thomas Villmann:
Median fuzzy c-means for clustering dissimilarity data. Neurocomputing 73(7-9): 1109-1116 (2010) - [j45]Petra Schneider, Michael Biehl, Barbara Hammer:
Hyperparameter learning in probabilistic prototype-based models. Neurocomputing 73(7-9): 1117-1124 (2010) - [j44]Stephan Simmuteit, Frank-Michael Schleif, Thomas Villmann, Barbara Hammer:
Evolving trees for the retrieval of mass spectrometry-based bacteria fingerprints. Knowl. Inf. Syst. 25(2): 327-343 (2010) - [j43]Barbara Hammer, Alexander Hasenfuss:
Topographic Mapping of Large Dissimilarity Data Sets. Neural Comput. 22(9): 2229-2284 (2010) - [j42]Aree Witoelar, Anarta Ghosh, J. J. G. de Vries, Barbara Hammer, Michael Biehl:
Window-Based Example Selection in Learning Vector Quantization. Neural Comput. 22(11): 2924-2961 (2010) - [j41]Banchar Arnonkijpanich, Alexander Hasenfuss, Barbara Hammer:
Local matrix learning in clustering and applications for manifold visualization. Neural Networks 23(4): 476-486 (2010) - [j40]Petra Schneider, Kerstin Bunte, Han Stiekema, Barbara Hammer, Thomas Villmann, Michael Biehl:
Regularization in matrix relevance learning. IEEE Trans. Neural Networks 21(5): 831-840 (2010) - 2009
- [j39]Frank-Michael Schleif, Thomas Villmann, Markus Kostrzewa, Barbara Hammer, Alexander Gammerman:
Cancer informatics by prototype networks in mass spectrometry. Artif. Intell. Medicine 45(2-3): 215-228 (2009) - [j38]Nikolai Alex, Alexander Hasenfuss, Barbara Hammer:
Patch clustering for massive data sets. Neurocomputing 72(7-9): 1455-1469 (2009) - [j37]Petra Schneider, Michael Biehl, Barbara Hammer:
Distance Learning in Discriminative Vector Quantization. Neural Comput. 21(10): 2942-2969 (2009) - [j36]Petra Schneider, Michael Biehl, Barbara Hammer:
Adaptive Relevance Matrices in Learning Vector Quantization. Neural Comput. 21(12): 3532-3561 (2009) - 2008
- [j35]Thomas Villmann, Frank-Michael Schleif, Markus Kostrzewa, Axel Walch, Barbara Hammer:
Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods. Briefings Bioinform. 9(2): 129-143 (2008) - [j34]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer:
Prototype based fuzzy classification in clinical proteomics. Int. J. Approx. Reason. 47(1): 4-16 (2008) - [j33]Aree Witoelar, Michael Biehl, Anarta Ghosh, Barbara Hammer:
Learning dynamics and robustness of vector quantization and neural gas. Neurocomputing 71(7-9): 1210-1219 (2008) - [j32]Thomas Villmann, Barbara Hammer, Frank-Michael Schleif, Wieland Hermann, Marie Cottrell:
Fuzzy classification using information theoretic learning vector quantization. Neurocomputing 71(16-18): 3070-3076 (2008) - 2007
- [j31]Frank-Michael Schleif, Barbara Hammer, Thomas Villmann:
Margin-based active learning for LVQ networks. Neurocomputing 70(7-9): 1215-1224 (2007) - [j30]Barbara Hammer, Alexander Hasenfuss, Thomas Villmann:
Magnification control for batch neural gas. Neurocomputing 70(7-9): 1225-1234 (2007) - [j29]Michael Biehl, Anarta Ghosh, Barbara Hammer:
Dynamics and Generalization Ability of LVQ Algorithms. J. Mach. Learn. Res. 8: 323-360 (2007) - 2006
- [j28]Marc Strickert, Udo Seiffert, Nese Sreenivasulu, Winfriede Weschke, Thomas Villmann, Barbara Hammer:
Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis. Neurocomputing 69(7-9): 651-659 (2006) - [j27]Michael Biehl, Anarta Ghosh, Barbara Hammer:
Learning vector quantization: The dynamics of winner-takes-all algorithms. Neurocomputing 69(7-9): 660-670 (2006) - [j26]Thomas Villmann, Frank-Michael Schleif, Barbara Hammer:
Prototype-based fuzzy classification with local relevance for proteomics. Neurocomputing 69(16-18): 2425-2428 (2006) - [j25]Barbara Hammer, Thomas Villmann:
Effizient Klassifizieren und Clustern: Lernparadigmen von Vektorquantisierern. Künstliche Intell. 20(3): 5-11 (2006) - [j24]Thomas Villmann, Frank-Michael Schleif, Barbara Hammer:
Comparison of relevance learning vector quantization with other metric adaptive classification methods. Neural Networks 19(5): 610-622 (2006) - [j23]Marie Cottrell, Barbara Hammer, Alexander Hasenfuss, Thomas Villmann:
Batch and median neural gas. Neural Networks 19(6-7): 762-771 (2006) - [j22]Thomas Villmann, Barbara Hammer, Frank-Michael Schleif, Tina Geweniger, Wieland Hermann:
Fuzzy classification by fuzzy labeled neural gas. Neural Networks 19(6-7): 772-779 (2006) - [j21]Anarta Ghosh, Michael Biehl, Barbara Hammer:
Performance analysis of LVQ algorithms: A statistical physics approach. Neural Networks 19(6-7): 817-829 (2006) - 2005
- [j20]Marie Cottrell, Barbara Hammer, Thomas Villmann:
New Aspects in Neurocomputing. Neurocomputing 63: 1-3 (2005) - [j19]Marc Strickert, Barbara Hammer, Sebastian Blohm:
Unsupervised recursive sequence processing. Neurocomputing 63: 69-97 (2005) - [j18]Kai Gersmann, Barbara Hammer:
Improving iterative repair strategies for scheduling with the SVM. Neurocomputing 63: 271-292 (2005) - [j17]Marc Strickert, Barbara Hammer:
Merge SOM for temporal data. Neurocomputing 64: 39-71 (2005) - [j16]Barbara Hammer, Alessio Micheli, Alessandro Sperduti:
Universal Approximation Capability of Cascade Correlation for Structures. Neural Comput. 17(5): 1109-1159 (2005) - [j15]Barbara Hammer, Craig Saunders, Alessandro Sperduti:
Special issue on neural networks and kernel methods for structured domains. Neural Networks 18(8): 1015-1018 (2005) - [j14]Barbara Hammer, Marc Strickert, Thomas Villmann:
Supervised Neural Gas with General Similarity Measure. Neural Process. Lett. 21(1): 21-44 (2005) - [j13]Barbara Hammer, Marc Strickert, Thomas Villmann:
On the Generalization Ability of GRLVQ Networks. Neural Process. Lett. 21(2): 109-120 (2005) - [j12]Bhaskar DasGupta, Barbara Hammer:
On approximate learning by multi-layered feedforward circuits. Theor. Comput. Sci. 348(1): 95-127 (2005) - 2004
- [j11]Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert:
A general framework for unsupervised processing of structured data. Neurocomputing 57: 3-35 (2004) - [j10]Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert:
Recursive self-organizing network models. Neural Networks 17(8-9): 1061-1085 (2004) - 2003
- [j9]Barbara Hammer, Peter Tiño:
Recurrent Neural Networks with Small Weights Implement Definite Memory Machines. Neural Comput. 15(8): 1897-1929 (2003) - [j8]Peter Tiño, Barbara Hammer:
Architectural Bias in Recurrent Neural Networks: Fractal Analysis. Neural Comput. 15(8): 1931-1957 (2003) - [j7]Thomas Villmann, Erzsébet Merényi, Barbara Hammer:
Neural maps in remote sensing image analysis. Neural Networks 16(3-4): 389-403 (2003) - [j6]Barbara Hammer, Kai Gersmann:
A Note on the Universal Approximation Capability of Support Vector Machines. Neural Process. Lett. 17(1): 43-53 (2003) - 2002
- [j5]Barbara Hammer:
Recurrent networks for structured data - A unifying approach and its properties. Cogn. Syst. Res. 3(2): 145-165 (2002) - [j4]Barbara Hammer, Thomas Villmann:
Generalized relevance learning vector quantization. Neural Networks 15(8-9): 1059-1068 (2002) - 2001
- [j3]Barbara Hammer:
Generalization Ability of Folding Networks. IEEE Trans. Knowl. Data Eng. 13(2): 196-206 (2001) - 2000
- [j2]Barbara Hammer:
On the approximation capability of recurrent neural networks. Neurocomputing 31(1-4): 107-123 (2000) - 1999
- [j1]Barbara Hammer:
On the Learnability of Recursive Data. Math. Control. Signals Syst. 12(1): 62-79 (1999)
Conference and Workshop Papers
- 2024
- [c273]Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier:
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. AAAI 2024: 14388-14396 - [c272]Inaam Ashraf, Janine Strotherm, Luca Hermes, Barbara Hammer:
Physics-Informed Graph Neural Networks for Water Distribution Systems. AAAI 2024: 21905-21913 - [c271]Patrick Kolpaczki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier:
SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification. AISTATS 2024: 3520-3528 - [c270]Nils Grimmelsmann, Malte Mechtenberg, Markus Vieth, Alexander Schulz, Barbara Hammer, Axel Schneider:
Predicting the Level of Co-Activation of One Muscle Head from the Other Muscle Head of the Biceps Brachii Muscle by Linear Regression and Shallow Feedforward Neural Networks. BIOSTEC (1) 2024: 611-621 - [c269]Sarah Schröder, Alexander Schulz, Fabian Hinder, Barbara Hammer:
Semantic Properties of Cosine Based Bias Scores for Word Embeddings. ICPRAM 2024: 160-168 - [c268]Valerie Vaquet, Fabian Hinder, Barbara Hammer:
Investigating the Suitability of Concept Drift Detection for Detecting Leakages in Water Distribution Networks. ICPRAM 2024: 296-303 - [c267]Fabian Hinder, Valerie Vaquet, Barbara Hammer:
A Remark on Concept Drift for Dependent Data. IDA (1) 2024: 77-89 - 2023
- [c266]Christoph Schulte, Sven Wagner, Armin Runge, Dimitrios Bariamis, Barbara Hammer:
Best of both, Structured and Unstructured Sparsity in Neural Networks. EuroMLSys@EuroSys 2023: 104-108 - [c265]André Artelt, Alexander Schulz, Barbara Hammer:
"Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction. ICPRAM 2023: 27-38 - [c264]Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer:
On the Hardness and Necessity of Supervised Concept Drift Detection. ICPRAM 2023: 164-175 - [c263]Philip Kenneweg, Sarah Schröder, Alexander Schulz, Barbara Hammer:
Debiasing Sentence Embedders Through Contrastive Word Pairs. ICPRAM 2023: 205-212 - [c262]Sarah Schröder, Alexander Schulz, Philip Kenneweg, Barbara Hammer:
So Can We Use Intrinsic Bias Measures or Not? ICPRAM 2023: 403-410 - [c261]Inaam Ashraf, Luca Hermes, André Artelt, Barbara Hammer:
Spatial Graph Convolution Neural Networks for Water Distribution Systems. IDA 2023: 29-41 - [c260]Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer:
On the Change of Decision Boundary and Loss in Learning with Concept Drift. IDA 2023: 182-194 - [c259]Philip Kenneweg, Leonardo Galli, Tristan Kenneweg, Barbara Hammer:
Faster Convergence for Transformer Fine-tuning with Line Search Methods. IJCNN 2023: 1-8 - [c258]Lars Quakernack, Valerie Vaquet, Barbara Hammer, Jens Haubrock:
A Sensor Fault Detection and Imputation Framework for Electrical Distribution Grids. ISGT EUROPE 2023: 1-5 - [c257]Markus Vieth, Alexander Schulz, Barbara Hammer:
Extending Drift Detection Methods to Identify When Exactly the Change Happened. IWANN (1) 2023: 92-104 - [c256]Janine Strotherm, Barbara Hammer:
Fairness-Enhancing Ensemble Classification in Water Distribution Networks. IWANN (1) 2023: 119-133 - [c255]Sarah Schröder, Alexander Schulz, Ivan Tarakanov, Robert Feldhans, Barbara Hammer:
Measuring Fairness with Biased Data: A Case Study on the Effects of Unsupervised Data in Fairness Evaluation. IWANN (1) 2023: 134-145 - [c254]Paul Stahlhofen, André Artelt, Luca Hermes, Barbara Hammer:
Adversarial Attacks on Leakage Detectors in Water Distribution Networks. IWANN (2) 2023: 451-463 - [c253]Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer:
SHAP-IQ: Unified Approximation of any-order Shapley Interactions. NeurIPS 2023 - [c252]Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier:
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams. ECML/PKDD (3) 2023: 428-445 - [c251]André Artelt, Kleanthis Malialis, Christos G. Panayiotou, Marios M. Polycarpou, Barbara Hammer:
Unsupervised Unlearning of Concept Drift with Autoencoders. SSCI 2023: 703-710 - [c250]Robert Feldhans, Alexander Schulz, Johannes Kummert, Moriz Habigt, Maike Stemmler, Christina Kohler, Dirk Abel, Rolf Rossaint, Barbara Hammer:
Data Augmentation for Cardiovascular Time Series Data Using WaveNet. SSCI 2023: 836-841 - [c249]Jonathan Jakob, Martina Hasenjäger, Barbara Hammer:
Incremental Human Gait Prediction without Catastrophic Forgetting. SSCI 2023: 1004-1011 - [c248]Johannes Kummert, Alexander Schulz, Robert Feldhans, Moriz Habigt, Maike Stemmler, Christina Kohler, Dirk Abel, Rolf Rossaint, Barbara Hammer:
Generating Cardiovascular Data to Improve Training of Assistive Heart Devices. SSCI 2023: 1292-1297 - [c247]Maximilian Muschalik, Fabian Fumagalli, Rohit Jagtani, Barbara Hammer, Eyke Hüllermeier:
iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios. xAI (1) 2023: 177-194 - [c246]Ulrike Kuhl, André Artelt, Barbara Hammer:
For Better or Worse: The Impact of Counterfactual Explanations' Directionality on User Behavior in xAI. xAI (3) 2023: 280-300 - 2022
- [c245]André Artelt, Roel Visser, Barbara Hammer:
Model Agnostic Local Explanations of Reject. ESANN 2022 - [c244]Johannes Brinkrolf, Valerie Vaquet, Fabian Hinder, Patrick Menz, Udo Seiffert, Barbara Hammer:
Federated learning vector quantization for dealing with drift between nodes. ESANN 2022 - [c243]Fabian Hinder, André Artelt, Valerie Vaquet, Barbara Hammer:
Contrasting Explanation of Concept Drift. ESANN 2022 - [c242]Philip Kenneweg, Sarah Schröder, Barbara Hammer:
Neural Architecture Search for Sentence Classification with BERT. ESANN 2022 - [c241]Andreas Mazur, André Artelt, Barbara Hammer:
Improving Zorro Explanations for Sparse Observations with Dense Proxy Data. ESANN 2022 - [c240]Patrick Menz, Valerie Vaquet, Barbara Hammer, Udo Seiffert:
From hyperspectral to multispectral sensing - from simulation to reality: A comprehensive approach for calibration model transfer. ESANN 2022 - [c239]Ulrike Kuhl, André Artelt, Barbara Hammer:
Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract Setting. FAccT 2022: 2125-2137 - [c238]Fabian Hinder, Johannes Brinkrolf, Barbara Hammer:
Feature Selection for Trustworthy Regression Using Higher Moments. ICANN (4) 2022: 76-87 - [c237]Jonathan Jakob, Martina Hasenjäger, Barbara Hammer:
Reject Options for Incremental Regression Scenarios. ICANN (4) 2022: 248-259 - [c236]Andrea Castellani, Sebastian Schmitt, Barbara Hammer:
Stream-Based Active Learning with Verification Latency in Non-stationary Environments. ICANN (4) 2022: 260-272 - [c235]Valerie Vaquet, André Artelt, Johannes Brinkrolf, Barbara Hammer:
Taking Care of Our Drinking Water: Dealing with Sensor Faults in Water Distribution Networks. ICANN (2) 2022: 682-693 - [c234]Jonathan Jakob, André Artelt, Martina Hasenjäger, Barbara Hammer:
SAM-kNN Regressor for Online Learning in Water Distribution Networks. ICANN (3) 2022: 752-762 - [c233]Daniel Wiens, Barbara Hammer:
Single-step Adversarial Training for Semantic Segmentation. ICPRAM 2022: 179-187 - [c232]Fabian Hinder, Valerie Vaquet, Barbara Hammer:
Suitability of Different Metric Choices for Concept Drift Detection. IDA 2022: 157-170 - [c231]Philip Kenneweg, Alexander Schulz, Sarah Schröder, Barbara Hammer:
Intelligent Learning Rate Distribution to Reduce Catastrophic Forgetting in Transformers. IDEAL 2022: 252-261 - [c230]Riza Velioglu, Jan Philip Göpfert, André Artelt, Barbara Hammer:
Explainable Artificial Intelligence for Improved Modeling of Processes. IDEAL 2022: 313-325 - [c229]Markus Vieth, Nils Grimmelsmann, Axel Schneider, Barbara Hammer:
Efficient Sensor Selection for Individualized Prediction Based on Biosignals. IDEAL 2022: 326-337 - [c228]André Artelt, Johannes Brinkrolf, Roel Visser, Barbara Hammer:
Explaining Reject Options of Learning Vector Quantization Classifiers. IJCCI 2022: 249-261 - [c227]Luca Hermes, Barbara Hammer, Andrew Melnik, Riza Velioglu, Markus Vieth, Malte Schilling:
A Graph-based U-Net Model for Predicting Traffic in unseen Cities. IJCNN 2022: 1-8 - [c226]Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, André Artelt, Barbara Hammer:
Localization of Concept Drift: Identifying the Drifting Datapoints. IJCNN 2022: 1-9 - [c225]Zafran Hussain Shah, Marcel Müller, Barbara Hammer, Thomas Huser, Wolfram Schenck:
Impact of different loss functions on denoising of microscopic images. IJCNN 2022: 1-10 - [c224]André Artelt, Barbara Hammer:
"Even if ..." - Diverse Semifactual Explanations of Reject. SSCI 2022: 854-859 - 2021
- [c223]Johannes Brinkrolf, Barbara Hammer:
Federated Learning Vector Quantization. ESANN 2021 - [c222]Chris Bronk, Amaury Lendasse, Peggy Lindner, Dan S. Wallach, Barbara Hammer:
Machine Learning for Measuring and Analyzing Online Social Communications. ESANN 2021 - [c221]Luca Hermes, Barbara Hammer, Malte Schilling:
Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting. ESANN 2021 - [c220]Fabian Hinder, Barbara Hammer:
Concept Drift Segmentation via Kolmogorov-Trees. ESANN 2021 - [c219]Valerie Vaquet, Patrick Menz, Udo Seiffert, Barbara Hammer:
Investigating Intensity and Transversal Drift in Hyperspectral Imaging Data. ESANN 2021 - [c218]Benjamin Paassen, Daniele Grattarola, Daniele Zambon, Cesare Alippi, Barbara Hammer:
Graph Edit Networks. ICLR 2021 - [c217]Aleksei Liuliakov, Barbara Hammer:
AutoML Technologies for the Identification of Sparse Models. IDEAL 2021: 65-75 - [c216]Robert Feldhans, Adrian Wilke, Stefan Heindorf, Mohammad Hossein Shaker, Barbara Hammer, Axel-Cyrille Ngonga Ngomo, Eyke Hüllermeier:
Drift Detection in Text Data with Document Embeddings. IDEAL 2021: 107-118 - [c215]Barbara Hammer:
Machine Learning in Non-Stationary Environments. IJCCI 2021: 11 - [c214]André Artelt, Barbara Hammer:
Efficient computation of contrastive explanations. IJCNN 2021: 1-9 - [c213]André Artelt, Fabian Hinder, Valerie Vaquet, Robert Feldhans, Barbara Hammer:
Contrastive Explanations for Explaining Model Adaptations. IWANN (1) 2021: 101-112 - [c212]Timo Friedrich, Barbara Hammer, Stefan Menzel:
Voxel-Based Three-Dimensional Neural Style Transfer. IWANN (1) 2021: 334-346 - [c211]Andrea Castellani, Sebastian Schmitt, Barbara Hammer:
Estimating the Electrical Power Output of Industrial Devices with End-to-End Time-Series Classification in the Presence of Label Noise. ECML/PKDD (1) 2021: 469-484 - [c210]André Artelt, Valerie Vaquet, Riza Velioglu, Fabian Hinder, Johannes Brinkrolf, Malte Schilling, Barbara Hammer:
Evaluating Robustness of Counterfactual Explanations. SSCI 2021: 1-9 - [c209]Andrea Castellani, Sebastian Schmitt, Barbara Hammer:
Task-Sensitive Concept Drift Detector with Constraint Embedding. SSCI 2021: 1-8 - [c208]Fabian Hinder, Johannes Brinkrolf, Valerie Vaquet, Barbara Hammer:
A Shape-Based Method for Concept Drift Detection and Signal Denoising. SSCI 2021: 1-8 - [c207]Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer:
Fast Non-Parametric Conditional Density Estimation using Moment Trees. SSCI 2021: 1-7 - [c206]Jonathan Jakob, Martina Hasenjäger, Barbara Hammer:
On the suitability of incremental learning for regression tasks in exoskeleton control. SSCI 2021: 1-8 - [c205]Valerie Vaquet, Fabian Hinder, Jonas Vaquet, Johannes Brinkrolf, Barbara Hammer:
Online Learning on Non-Stationary Data Streams for Image Recognition using Deep Embeddings. SSCI 2021: 1-7 - 2020
- [c204]André Artelt, Barbara Hammer:
Efficient computation of counterfactual explanations of LVQ models. ESANN 2020: 19-24 - [c203]Johannes Brinkrolf, Barbara Hammer:
Sparse Metric Learning in Prototype-based Classification. ESANN 2020: 375-380 - [c202]Jan Philip Göpfert, Heiko Wersing, Barbara Hammer:
Locally Adaptive Nearest Neighbors. ESANN 2020: 667-672 - [c201]André Artelt, Barbara Hammer:
Convex Density Constraints for Computing Plausible Counterfactual Explanations. ICANN (1) 2020: 353-365 - [c200]Fabian Hinder, Johannes Kummert, Barbara Hammer:
Explaining Concept Drift by Mean of Direction. ICANN (1) 2020: 379-390 - [c199]Valerie Vaquet, Barbara Hammer:
Balanced SAM-kNN: Online Learning with Heterogeneous Drift and Imbalanced Data. ICANN (2) 2020: 850-862 - [c198]Fabian Hinder, André Artelt, Barbara Hammer:
Towards Non-Parametric Drift Detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD). ICML 2020: 4249-4259 - [c197]Jan Philip Göpfert, André Artelt, Heiko Wersing, Barbara Hammer:
Adversarial Attacks Hidden in Plain Sight. IDA 2020: 235-247 - [c196]Alexander Schulz, Fabian Hinder, Barbara Hammer:
DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction. IJCAI 2020: 2305-2311 - [c195]Viktor Losing, Barbara Hammer, Heiko Wersing, Albert Bifet:
Randomizing the Self-Adjusting Memory for Enhanced Handling of Concept Drift. IJCNN 2020: 1-8 - 2019
- [c194]Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer:
FRI-Feature Relevance Intervals for Interpretable and Interactive Data Exploration. CIBCB 2019: 1-10 - [c193]Babak Hosseini, Barbara Hammer:
Interpretable Multiple-Kernel Prototype Learning for Discriminative Representation and Feature Selection. CIKM 2019: 1863-1872 - [c192]Albert Bifet, Barbara Hammer, Frank-Michael Schleif:
Recent trends in streaming data analysis, concept drift and analysis of dynamic data sets. ESANN 2019 - [c191]Babak Hosseini, Barbara Hammer:
Multiple-Kernel dictionary learning for reconstruction and clustering of unseen multivariate time-series. ESANN 2019 - [c190]Lukas Pfannschmidt, Jonathan Jakob, Michael Biehl, Peter Tiño, Barbara Hammer:
Feature relevance bounds for ordinal regression. ESANN 2019 - [c189]Jan Philip Göpfert, Heiko Wersing, Barbara Hammer:
Recovering Localized Adversarial Attacks. ICANN (1) 2019: 302-311 - [c188]Babak Hosseini, Romain Montagné, Barbara Hammer:
Deep-Aligned Convolutional Neural Network for Skeleton-Based Action Recognition and Segmentation. ICDM 2019: 1096-1101 - [c187]Peng Li, Oliver Niggemann, Barbara Hammer:
On the Identification of Decision Boundaries for Anomaly Detection in CPPS. ICIT 2019: 1311-1316 - [c186]Viktor Losing, Taizo Yoshikawa, Martina Hasenjäger, Barbara Hammer, Heiko Wersing:
Personalized Online Learning of Whole-Body Motion Classes using Multiple Inertial Measurement Units. ICRA 2019: 9530-9536 - [c185]Babak Hosseini, Barbara Hammer:
Large-Margin Multiple Kernel Learning for Discriminative Features Selection and Representation Learning. IJCNN 2019: 1-8 - [c184]Christina Göpfert, Jan Philip Göpfert, Barbara Hammer:
Adversarial Robustness Curves. PKDD/ECML Workshops (1) 2019: 172-179 - [c183]Babak Hosseini, Barbara Hammer:
Interpretable Discriminative Dimensionality Reduction and Feature Selection on the Manifold. ECML/PKDD (1) 2019: 310-326 - [c182]Michael Biehl, Fthi Abadi, Christina Göpfert, Barbara Hammer:
Prototype-Based Classifiers in the Presence of Concept Drift: A Modelling Framework. WSOM+ 2019: 210-221 - 2018
- [c181]Johannes Brinkrolf, Kolja Berger, Barbara Hammer:
Differential private relevance learning. ESANN 2018 - [c180]Babak Hosseini, Barbara Hammer:
Feasibility based Large Margin Nearest Neighbor metric learning. ESANN 2018 - [c179]Jan Philip Göpfert, Barbara Hammer, Heiko Wersing:
Mitigating Concept Drift via Rejection. ICANN (1) 2018: 456-467 - [c178]Jeffrey Frederic Queißer, Barbara Hammer, Hisashi Ishihara, Minoru Asada, Jochen Jakob Steil:
Skill Memories for Parameterized Dynamic Action Primitives on the Pneumatically Driven Humanoid Robot Child Affetto. ICDL-EPIROB 2018: 39-45 - [c177]Viktor Losing, Heiko Wersing, Barbara Hammer:
Enhancing Very Fast Decision Trees with Local Split-Time Predictions. ICDM 2018: 287-296 - [c176]Babak Hosseini, Barbara Hammer:
Confident Kernel Sparse Coding and Dictionary Learning. ICDM 2018: 1031-1036 - [c175]Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli, Barbara Hammer:
Tree Edit Distance Learning via Adaptive Symbol Embeddings. ICML 2018: 3973-3982 - [c174]Babak Hosseini, Barbara Hammer:
Non-negative Local Sparse Coding for Subspace Clustering. IDA 2018: 137-150 - [c173]Stefan Meyer, Olivier J. N. Bertrand, Martin Egelhaaf, Barbara Hammer:
Inferring Temporal Structure from Predictability in Bumblebee Learning Flight. IDEAL (1) 2018: 508-519 - [c172]Peng Li, Oliver Niggemann, Barbara Hammer:
A Geometric Approach to Clustering Based Anomaly Detection for Industrial Applications. IECON 2018: 5345-5352 - [c171]Felix Specht, Jens Otto, Oliver Niggemann, Barbara Hammer:
Generation of Adversarial Examples to Prevent Misclassification of Deep Neural Network based Condition Monitoring Systems for Cyber-Physical Production Systems. INDIN 2018: 760-765 - 2017
- [c170]Cosima Prahm, Alexander Schulz, Benjamin Paaßen, Oskar Aszmann, Barbara Hammer, Georg Dorffner:
Echo State Networks as Novel Approach for Low-Cost Myoelectric Control. AIME 2017: 338-342 - [c169]Christina Göpfert, Lukas Pfannschmidt, Barbara Hammer:
Feature Relevance Bounds for Linear Classification. ESANN 2017 - [c168]Benjamin Paassen, Alexander Schulz, Janne Hahne, Barbara Hammer:
An EM transfer learning algorithm with applications in bionic hand prostheses. ESANN 2017 - [c167]Viktor Losing, Barbara Hammer, Heiko Wersing:
Self-Adjusting Memory: How to Deal with Diverse Drift Types. IJCAI 2017: 4899-4903 - [c166]Benoît Frénay, Barbara Hammer:
Label-noise-tolerant classification for streaming data. IJCNN 2017: 1748-1755 - [c165]Viktor Losing, Barbara Hammer, Heiko Wersing:
Personalized maneuver prediction at intersections. ITSC 2017: 1-6 - [c164]Kolja Berger, Alexander Schulz, Benjamin Paaßen, Barbara Hammer:
Linear supervised transfer learning for the large margin nearest neighbor classifier. SSCI 2017: 1-6 - [c163]Jan Philip Göpfert, Christina Göpfert, Mario Botsch, Barbara Hammer:
Effects of variability in synthetic training data on convolutional neural networks for 3D head reconstruction. SSCI 2017: 1-7 - [c162]Johannes Brinkrolf, Barbara Hammer:
Probabilistic extension and reject options for pairwise LVQ. WSOM 2017: 205-212 - 2016
- [c161]Michael Biehl, Barbara Hammer, Thomas Villmann:
Prototype-based Models for the Supervised Learning of Classification Schemes. Astroinformatics 2016: 129-138 - [c160]Benjamin Paaßen, Joris Jensen, Barbara Hammer:
Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming. EDM 2016: 183-190 - [c159]Alexander Schulz, Barbara Hammer:
Discriminative dimensionality reduction in kernel space. ESANN 2016 - [c158]Alexander Gepperth, Barbara Hammer:
Incremental learning algorithms and applications. ESANN 2016 - [c157]Viktor Losing, Barbara Hammer, Heiko Wersing:
Choosing the best algorithm for an incremental on-line learning task. ESANN 2016 - [c156]Benjamin Paassen, Christina Göpfert, Barbara Hammer:
Gaussian process prediction for time series of structured data. ESANN 2016 - [c155]Johannes Kummert, Benjamin Paassen, Joris Jensen, Christina Göpfert, Barbara Hammer:
Local Reject Option for Deterministic Multi-class SVM. ICANN (2) 2016: 251-258 - [c154]Babak Hosseini, Felix Hülsmann, Mario Botsch, Barbara Hammer:
Non-negative Kernel Sparse Coding for the Analysis of Motion Data. ICANN (2) 2016: 506-514 - [c153]Christina Göpfert, Benjamin Paassen, Barbara Hammer:
Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning. ICANN (1) 2016: 510-517 - [c152]Viktor Losing, Barbara Hammer, Heiko Wersing:
KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift. ICDM 2016: 291-300 - [c151]Lydia Fischer, Barbara Hammer, Heiko Wersing:
Online metric learning for an adaptation to confidence drift. IJCNN 2016: 748-755 - [c150]Thomas Villmann, Marika Kaden, Andrea Bohnsack, J.-M. Villmann, T. Drogies, Sascha Saralajew, Barbara Hammer:
Self-Adjusting Reject Options in Prototype Based Classification. WSOM 2016: 269-279 - 2015
- [c149]Alexander Schulz, Barbara Hammer:
Visualization of Regression Models Using Discriminative Dimensionality Reduction. CAIP (2) 2015: 437-449 - [c148]Babak Hosseini, Barbara Hammer:
Efficient metric learning for the analysis of motion data. DSAA 2015: 1-10 - [c147]Benjamin Paaßen, Bassam Mokbel, Barbara Hammer:
A Toolbox for Adaptive Sequence Dissimilarity Measures for Intelligent Tutoring Systems. EDM 2015: 632 - [c146]Patrick Blöbaum, Alexander Schulz, Barbara Hammer:
Unsupervised Dimensionality Reduction for Transfer Learning. ESANN 2015 - [c145]Lydia Fischer, Barbara Hammer, Heiko Wersing:
Certainty-based prototype insertion/deletion for classification with metric adaptation. ESANN 2015 - [c144]Benjamin Paassen, Bassam Mokbel, Barbara Hammer:
Adaptive structure metrics for automated feedback provision in Java programming. ESANN 2015 - [c143]Alexander Schulz, Barbara Hammer:
Metric Learning in Dimensionality Reduction. ICPRAM (1) 2015: 232-239 - [c142]Michael Biehl, Barbara Hammer, Frank-Michael Schleif, Petra Schneider, Thomas Villmann:
Stationarity of Matrix Relevance LVQ. IJCNN 2015: 1-8 - [c141]Lydia Fischer, Barbara Hammer, Heiko Wersing:
Combining offline and online classifiers for life-long learning. IJCNN 2015: 1-8 - [c140]Viktor Losing, Barbara Hammer, Heiko Wersing:
Interactive online learning for obstacle classification on a mobile robot. IJCNN 2015: 1-8 - [c139]Markus Lux, Alexander Sczyrba, Barbara Hammer:
Automatic discovery of metagenomic structure. IJCNN 2015: 1-8 - [c138]Alexander Schulz, Barbara Hammer:
Discriminative dimensionality reduction for regression problems using the Fisher metric. IJCNN 2015: 1-8 - [c137]Alexander Schulz, Bassam Mokbel, Michael Biehl, Barbara Hammer:
Inferring Feature Relevances From Metric Learning. SSCI 2015: 1599-1606 - 2014
- [c136]Benoît Frénay, Daniela Hofmann, Alexander Schulz, Michael Biehl, Barbara Hammer:
Valid interpretation of feature relevance for linear data mappings. CIDM 2014: 149-156 - [c135]Lydia Fischer, Barbara Hammer, Heiko Wersing:
Rejection strategies for learning vector quantization. ESANN 2014 - [c134]Barbara Hammer, Haibo He, Thomas Martinetz:
Learning and modeling big data. ESANN 2014 - [c133]Bassam Mokbel, Benjamin Paaßen, Barbara Hammer:
Adaptive distance measures for sequential data. ESANN 2014 - [c132]David Nebel, Barbara Hammer, Thomas Villmann:
Supervised Generative Models for Learning Dissimilarity Data. ESANN 2014 - [c131]Alexander Schulz, Andrej Gisbrecht, Barbara Hammer:
Relevance Learning for Dimensionality Reduction. ESANN 2014 - [c130]Lydia Fischer, Barbara Hammer, Heiko Wersing:
Local Rejection Strategies for Learning Vector Quantization. ICANN 2014: 563-570 - [c129]Bassam Mokbel, Benjamin Paaßen, Barbara Hammer:
Efficient Adaptation of Structure Metrics in Prototype-Based Classification. ICANN 2014: 571-578 - [c128]Sebastian Gross, Bassam Mokbel, Barbara Hammer, Niels Pinkwart:
How to Select an Example? A Comparison of Selection Strategies in Example-Based Learning. Intelligent Tutoring Systems 2014: 340-347 - [c127]Lydia Fischer, David Nebel, Thomas Villmann, Barbara Hammer, Heiko Wersing:
Rejection Strategies for Learning Vector Quantization - A Comparison of Probabilistic and Deterministic Approaches. WSOM 2014: 109-118 - [c126]Barbara Hammer, David Nebel, Martin Riedel, Thomas Villmann:
Generative versus Discriminative Prototype Based Classification. WSOM 2014: 123-132 - 2013
- [c125]Sebastian Gross, Bassam Mokbel, Barbara Hammer, Niels Pinkwart:
Towards Providing Feedback to Students in Absence of Formalized Domain Models. AIED 2013: 644-648 - [c124]Michael Biehl, Barbara Hammer, Thomas Villmann:
Distance Measures for Prototype Based Classification. BrainComp 2013: 100-116 - [c123]Marc Strickert, Barbara Hammer, Thomas Villmann, Michael Biehl:
Regularization and improved interpretation of linear data mappings and adaptive distance measures. CIDM 2013: 10-17 - [c122]Bassam Mokbel, Sebastian Gross, Benjamin Paaßen, Niels Pinkwart, Barbara Hammer:
Domain-Independent Proximity Measures in Intelligent Tutoring Systems. EDM 2013: 334-335 - [c121]Andrej Gisbrecht, Yoan Miché, Barbara Hammer, Amaury Lendasse:
Visualizing dependencies of spectral features using mutual information. ESANN 2013 - [c120]Daniela Hofmann, Barbara Hammer:
Sparse approximations for kernel learning vector quantization. ESANN 2013 - [c119]Xibin Zhu, Frank-Michael Schleif, Barbara Hammer:
Semi-Supervised Vector Quantization for proximity data. ESANN 2013 - [c118]Sebastian Gross, Bassam Mokbel, Barbara Hammer, Niels Pinkwart:
Towards a Domain-Independent ITS Middleware Architecture. ICALT 2013: 408-409 - [c117]David Nebel, Barbara Hammer, Thomas Villmann:
A Median Variant of Generalized Learning Vector Quantization. ICONIP (2) 2013: 19-26 - [c116]Barbara Hammer, Andrej Gisbrecht, Alexander Schulz:
Applications of Discriminative Dimensionality Reduction. ICPRAM 2013: 33-41 - [c115]Andrej Gisbrecht, Alexander Schulz, Barbara Hammer:
Discriminative Dimensionality Reduction for the Visualization of Classifiers. ICPRAM (Selected Papers) 2013: 39-56 - [c114]Frank-Michael Schleif, Xibin Zhu, Barbara Hammer:
Sparse Prototype Representation by Core Sets. IDEAL 2013: 302-309 - [c113]Andrej Gisbrecht, Barbara Hammer, Bassam Mokbel, Alexander Sczyrba:
Nonlinear Dimensionality Reduction for Cluster Identification in Metagenomic Samples. IV 2013: 174-179 - [c112]Alexander Schulz, Andrej Gisbrecht, Barbara Hammer:
Using Nonlinear Dimensionality Reduction to Visualize Classifiers. IWANN (1) 2013: 59-68 - [c111]Xibin Zhu, Frank-Michael Schleif, Barbara Hammer:
Secure Semi-supervised Vector Quantization for Dissimilarity Data. IWANN (1) 2013: 347-356 - 2012
- [c110]Frank-Michael Schleif, Xibin Zhu, Barbara Hammer:
Soft Competitive Learning for Large Data Sets. ADBIS Workshops 2012: 141-151 - [c109]Bassam Mokbel, Sebastian Gross, Markus Lux, Niels Pinkwart, Barbara Hammer:
How to Quantitatively Compare Data Dissimilarities for Unsupervised Machine Learning? ANNPR 2012: 1-13 - [c108]Daniela Hofmann, Barbara Hammer:
Kernel Robust Soft Learning Vector Quantization. ANNPR 2012: 14-23 - [c107]Sebastian Gross, Bassam Mokbel, Barbara Hammer, Niels Pinkwart:
Feedback Provision Strategies in Intelligent Tutoring Systems Based on Clustered Solution Spaces. DeLFI 2012: 27-38 - [c106]Charles Bouveyron, Barbara Hammer, Thomas Villmann:
Recent developments in clustering algorithms. ESANN 2012 - [c105]Andrej Gisbrecht, Wouter Lueks, Bassam Mokbel, Barbara Hammer:
Out-of-sample kernel extensions for nonparametric dimensionality reduction. ESANN 2012 - [c104]Andrej Gisbrecht, Dusan Sovilj, Barbara Hammer, Amaury Lendasse:
Relevance learning for time series inspection. ESANN 2012 - [c103]Bassam Mokbel, Wouter Lueks, Andrej Gisbrecht, Michael Biehl, Barbara Hammer:
Visualizing the quality of dimensionality reduction. ESANN 2012 - [c102]Barbara Hammer, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu:
White Box Classification of Dissimilarity Data. HAIS (1) 2012: 309-321 - [c101]Frank-Michael Schleif, Bassam Mokbel, Andrej Gisbrecht, Leslie Theunissen, Volker Dürr, Barbara Hammer:
Learning Relevant Time Points for Time-Series Data in the Life Sciences. ICANN (2) 2012: 531-539 - [c100]Frank-Michael Schleif, Xibin Zhu, Andrej Gisbrecht, Barbara Hammer:
Fast approximated relational and kernel clustering. ICPR 2012: 1229-1232 - [c99]Andrej Gisbrecht, Daniela Hofmann, Barbara Hammer:
Discriminative Dimensionality Reduction Mappings. IDA 2012: 126-138 - [c98]Frank-Michael Schleif, Xibin Zhu, Barbara Hammer:
A Conformal Classifier for Dissimilarity Data. AIAI (2) 2012: 234-243 - [c97]Andrej Gisbrecht, Bassam Mokbel, Barbara Hammer:
Linear basis-function t-SNE for fast nonlinear dimensionality reduction. IJCNN 2012: 1-8 - [c96]Frank-Michael Schleif, Andrej Gisbrecht, Barbara Hammer:
Relevance learning for short high-dimensional time series in the life sciences. IJCNN 2012: 1-8 - [c95]Xibin Zhu, Frank-Michael Schleif, Barbara Hammer:
Patch Processing for Relational Learning Vector Quantization. ISNN (1) 2012: 55-63 - [c94]Sebastian Gross, Xibin Zhu, Barbara Hammer, Niels Pinkwart:
Cluster Based Feedback Provision Strategies in Intelligent Tutoring Systems. ITS 2012: 699-700 - [c93]Barbara Hammer, Andrej Gisbrecht, Alexander Schulz:
How to Visualize Large Data Sets? WSOM 2012: 1-12 - [c92]Daniela Hofmann, Andrej Gisbrecht, Barbara Hammer:
Efficient Approximations of Kernel Robust Soft LVQ. WSOM 2012: 183-192 - 2011
- [c91]Andrej Gisbrecht, Barbara Hammer, Frank-Michael Schleif, Xibin Zhu:
Accelerating kernel clustering for biomedical data analysis. CIBCB 2011: 154-161 - [c90]Kerstin Bunte, Michael Biehl, Barbara Hammer:
Dimensionality reduction mappings. CIDM 2011: 349-356 - [c89]Kerstin Bunte, Michael Biehl, Barbara Hammer:
Supervised dimension reduction mappings. ESANN 2011 - [c88]Marika Kästner, Barbara Hammer, Michael Biehl, Thomas Villmann:
Generalized functional relevance learning vector quantization. ESANN 2011 - [c87]Xibin Zhu, Barbara Hammer:
Patch Affinity Propagation. ESANN 2011 - [c86]Frank-Michael Schleif, Andrej Gisbrecht, Barbara Hammer:
Accelerating Kernel Neural Gas. ICANN (1) 2011: 150-158 - [c85]Barbara Hammer, Frank-Michael Schleif, Xibin Zhu:
Relational Extensions of Learning Vector Quantization. ICONIP (2) 2011: 481-489 - [c84]Barbara Hammer, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu:
Prototype-Based Classification of Dissimilarity Data. IDA 2011: 185-197 - [c83]Andrej Gisbrecht, Frank-Michael Schleif, Xibin Zhu, Barbara Hammer:
Linear Time Heuristics for Topographic Mapping of Dissimilarity Data. IDEAL 2011: 25-33 - [c82]Barbara Hammer, Andrej Gisbrecht, Alexander Hasenfuss, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu:
Topographic Mapping of Dissimilarity Data. WSOM 2011: 1-15 - [c81]Barbara Hammer, Michael Biehl, Kerstin Bunte, Bassam Mokbel:
A General Framework for Dimensionality Reduction for Large Data Sets. WSOM 2011: 277-287 - 2010
- [c80]Banchar Arnonkijpanich, Barbara Hammer:
Global Coordination Based on Matrix Neural Gas for Dynamic Texture Synthesis. ANNPR 2010: 84-95 - [c79]Thomas Villmann, Sven Haase, Frank-Michael Schleif, Barbara Hammer, Michael Biehl:
The Mathematics of Divergence Based Online Learning in Vector Quantization. ANNPR 2010: 108-119 - [c78]Barbara Hammer, Alexander Hasenfuss:
Clustering Very Large Dissimilarity Data Sets. ANNPR 2010: 259-273 - [c77]Kerstin Bunte, Barbara Hammer, Thomas Villmann, Michael Biehl, Axel Wismüller:
Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization. ESANN 2010 - [c76]Andrej Gisbrecht, Barbara Hammer:
Relevance learning in generative topographic maps. ESANN 2010 - [c75]Andrej Gisbrecht, Bassam Mokbel, Barbara Hammer:
Relational Generative Topographic Map. ESANN 2010 - [c74]Thomas Villmann, Frank-Michael Schleif, Barbara Hammer:
Sparse representation of data. ESANN 2010 - [c73]Thomas Villmann, Sven Haase, Frank-Michael Schleif, Barbara Hammer:
Divergence Based Online Learning in Vector Quantization. ICAISC (1) 2010: 479-486 - [c72]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer, Petra Schneider, Michael Biehl:
Generalized Derivative Based Kernelized Learning Vector Quantization. IDEAL 2010: 21-28 - [c71]Andrej Gisbrecht, Bassam Mokbel, Alexander Hasenfuss, Barbara Hammer:
Visualizing Dissimilarity Data Using Generative Topographic Mapping. KI 2010: 227-237 - 2009
- [c70]Kerstin Bunte, Barbara Hammer, Michael Biehl:
Nonlinear Dimension Reduction and Visualization of Labeled Data. CAIP 2009: 1162-1170 - [c69]Thomas Villmann, Barbara Hammer, Michael Biehl:
Some Theoretical Aspects of the Neural Gas Vector Quantizer. Similarity-Based Clustering 2009: 23-34 - [c68]Barbara Hammer, Alexander Hasenfuss, Fabrice Rossi:
Median Topographic Maps for Biomedical Data Sets. Similarity-Based Clustering 2009: 92-117 - [c67]Kerstin Bunte, Barbara Hammer, Petra Schneider, Michael Biehl:
Nonlinear Discriminative Data Visualization. ESANN 2009 - [c66]Tina Geweniger, Dietlind Zühlke, Barbara Hammer, Thomas Villmann:
Median Variant of Fuzzy c-Means. ESANN 2009 - [c65]Barbara Hammer, Benjamin Schrauwen, Jochen J. Steil:
Recent advances in efficient learning of recurrent networks. ESANN 2009 - [c64]Petra Schneider, Michael Biehl, Barbara Hammer:
Hyperparameter Learning in Robust Soft LVQ. ESANN 2009 - [c63]Aree Witoelar, Michael Biehl, Barbara Hammer:
Equilibrium properties of off-line LVQ. ESANN 2009 - [c62]Bassam Mokbel, Alexander Hasenfuss, Barbara Hammer:
Graph-Based Representation of Symbolic Musical Data. GbRPR 2009: 42-51 - [c61]Tina Geweniger, Dietlind Zühlke, Barbara Hammer, Thomas Villmann:
Fuzzy Variant of Affinity Propagation in Comparison to Median Fuzzy c-Means. WSOM 2009: 72-79 - [c60]Thomas Villmann, Barbara Hammer:
Functional Principal Component Learning Using Oja's Method and Sobolev Norms. WSOM 2009: 325-333 - 2008
- [c59]Alexander Hasenfuss, Barbara Hammer:
Single Pass Clustering and Classification of Large Dissimilarity Datasets. Artificial Intelligence and Pattern Recognition 2008: 219-223 - [c58]Alexander Hasenfuss, Barbara Hammer, Fabrice Rossi:
Patch Relational Neural Gas - Clustering of Huge Dissimilarity Datasets. ANNPR 2008: 1-12 - [c57]Marc Strickert, Petra Schneider, Jens Keilwagen, Thomas Villmann, Michael Biehl, Barbara Hammer:
Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics. ANNPR 2008: 78-89 - [c56]Marc Strickert, Nese Sreenivasulu, Thomas Villmann, Barbara Hammer:
Robust Centroid-Based Clustering using Derivatives of Pearson Correlation. BIOSIGNALS (2) 2008: 197-203 - [c55]Nikolai Alex, Barbara Hammer:
Parallelizing single patch pass clustering. ESANN 2008: 227-232 - [c54]Alexander Hasenfuss, Barbara Hammer, Tina Geweniger, Thomas Villmann:
Magnification Control in Relational Neural Gas. ESANN 2008: 325-330 - [c53]Banchar Arnonkijpanich, Barbara Hammer, Alexander Hasenfuss, Chidchanok Lursinsap:
Matrix Learning for Topographic Neural Maps. ICANN (1) 2008: 572-582 - [c52]Tina Geweniger, Frank-Michael Schleif, Alexander Hasenfuss, Barbara Hammer, Thomas Villmann:
Comparison of Cluster Algorithms for the Analysis of Text Data Using Kolmogorov Complexity. ICONIP (2) 2008: 61-69 - [c51]Tim Winkler, Jens Drieseberg, Kai Hormann, Alexander Hasenfuss, Barbara Hammer:
Thinning Mesh Animations. VMV 2008: 149-158 - 2007
- [c50]Petra Schneider, Michael Biehl, Barbara Hammer:
Relevance matrices in LVQ. ESANN 2007: 37-42 - [c49]Barbara Hammer, Thomas Villmann:
How to process uncertainty in machine learning?. ESANN 2007: 79-90 - [c48]Aree Witoelar, Michael Biehl, Anarta Ghosh, Barbara Hammer:
On the dynamics of Vector Quantization and Neural Gas. ESANN 2007: 127-132 - [c47]Alexander Hasenfuss, Barbara Hammer:
Relational Topographic Maps. IDA 2007: 93-105 - [c46]Barbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann, Marc Strickert, Udo Seiffert:
Intuitive Clustering of Biological Data. IJCNN 2007: 1877-1882 - [c45]Alexander Hasenfuss, Barbara Hammer, Frank-Michael Schleif, Thomas Villmann:
Neural Gas Clustering for Dissimilarity Data with Continuous Prototypes. IWANN 2007: 539-546 - [c44]Thomas Villmann, Frank-Michael Schleif, Erzsébet Merényi, Barbara Hammer:
Fuzzy Labeled Self-Organizing Map for Classification of Spectra. IWANN 2007: 556-563 - [c43]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer:
Supervised Neural Gas for Classification of Functional Data and Its Application to the Analysis of Clinical Proteom Spectra. IWANN 2007: 1036-1044 - [c42]Barbara Hammer, Alexander Hasenfuss:
Relational Neural Gas. KI 2007: 190-204 - [c41]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer:
Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps. WILF 2007: 563-570 - 2006
- [c40]Barbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann:
Supervised Batch Neural Gas. ANNPR 2006: 33-45 - [c39]Thomas Villmann, Udo Seiffert, Frank-Michael Schleif, Cornelia Brüß, Tina Geweniger, Barbara Hammer:
Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes. ANNPR 2006: 46-56 - [c38]Thomas Villmann, Barbara Hammer, Udo Seiffert:
Perspectives of Self-adapted Self-organizing Clustering in Organic Computing. BioADIT 2006: 141-159 - [c37]Frank-Michael Schleif, Thomas Elssner, Markus Kostrzewa, Thomas Villmann, Barbara Hammer:
Analysis and Visualization of Proteomic Data by Fuzzy Labeled Self-Organizing Maps. CBMS 2006: 919-924 - [c36]Barbara Hammer, Alexander Hasenfuss, Thomas Villmann:
Magnification control for batch neural gas. ESANN 2006: 7-12 - [c35]Udo Seiffert, Barbara Hammer, Samuel Kaski, Thomas Villmann:
Neural networks and machine learning in bioinformatics - theory and applications. ESANN 2006: 521-532 - [c34]Frank-Michael Schleif, Barbara Hammer, Thomas Villmann:
Margin based Active Learning for LVQ Networks. ESANN 2006: 539-544 - [c33]Barbara Hammer, Thomas Villmann, Frank-Michael Schleif, Cornelia Albani, Wieland Hermann:
Learning Vector Quantization Classification with Local Relevance Determination for Medical Data. ICAISC 2006: 603-612 - [c32]Thomas Villmann, Barbara Hammer, Frank-Michael Schleif, Tina Geweniger, Tom Fischer, Marie Cottrell:
Prototype Based Classification Using Information Theoretic Learning. ICONIP (2) 2006: 40-49 - 2005
- [c31]Michael Biehl, Anarta Ghosh, Barbara Hammer:
The dynamics of Learning Vector Quantization. ESANN 2005: 13-18 - [c30]Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann:
Relevance learning for mental disease classification. ESANN 2005: 139-144 - [c29]Barbara Hammer, Thomas Villmann:
Classification using non-standard metrics. ESANN 2005: 303-316 - [c28]Katharina Tluk von Toschanowitz, Barbara Hammer, Helge J. Ritter:
Relevance determination in reinforcement learning. ESANN 2005: 369-374 - [c27]Thomas Villmann, Frank-Michael Schleif, Barbara Hammer:
Fuzzy Labeled Soft Nearest Neighbor Classification with Relevance Learning. ICMLA 2005 - [c26]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer:
Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data. WILF 2005: 290-296 - 2004
- [c25]Peter Tiño, Barbara Hammer:
On Early Stages of Learning in Connectionist Models with Feedback Connections. AAAI Technical Report (3) 2004: 69-71 - [c24]Marc Strickert, Barbara Hammer:
Self-organizing context learning. ESANN 2004: 39-44 - [c23]Barbara Hammer, Brijnesh J. Jain:
Neural methods for non-standard data. ESANN 2004: 281-292 - [c22]Barbara Hammer, Marc Strickert, Thomas Villmann:
Relevance LVQ versus SVM. ICAISC 2004: 592-597 - [c21]Frank-Michael Schleif, U. Clauss, Thomas Villmann, Barbara Hammer:
Supervised relevance neural gas and unified maximum separability analysis for classification of mass spectrometric data. ICMLA 2004: 374-379 - 2003
- [c20]Marc Strickert, Barbara Hammer:
Unsupervised Recursive Sequence Processing. ESANN 2003: 27-32 - [c19]Barbara Hammer, Thomas Villmann:
Mathematical Aspects of Neural Networks. ESANN 2003: 59-72 - [c18]Kai Gersmann, Barbara Hammer:
Improving iterative repair strategies for scheduling with the SVM. ESANN 2003: 235-240 - 2002
- [c17]Barbara Hammer, Thomas Villmann:
Batch-RLVQ. ESANN 2002: 295-300 - [c16]Barbara Hammer, Jochen J. Steil:
Perspectives on learning with recurrent neural networks. ESANN 2002: 357-368 - [c15]Barbara Hammer, Alessio Micheli, Alessandro Sperduti:
A general framework for unsupervised processing of structured data. ESANN 2002: 389-394 - [c14]Barbara Hammer, Marc Strickert, Thomas Villmann:
Learning Vector Quantization for Multimodal Data. ICANN 2002: 370-376 - [c13]Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann:
Rule Extraction from Self-Organizing Networks. ICANN 2002: 877-883 - [c12]Peter Tiño, Barbara Hammer:
Architectural Bias in Recurrent Neural Networks - Fractal Analysis. ICANN 2002: 1359-1364 - 2001
- [c11]Thorsten Bojer, Barbara Hammer, Daniel Schunk, Katharina Tluk von Toschanowitz:
Relevance determination in Learning Vector Quantization. ESANN 2001: 271-276 - [c10]Barbara Hammer, Thomas Villmann:
Input pruning for neural gas architectures. ESANN 2001: 283-288 - [c9]Marc Strickert, Thorsten Bojer, Barbara Hammer:
Generalized Relevance LVQ for Time Series. ICANN 2001: 677-683 - [c8]Barbara Hammer:
On the Generalization Ability of Recurrent Networks. ICANN 2001: 731-736 - [c7]Barbara Hammer, Thomas Villmann:
Estimating Relevant Input Dimensions for Self-organizing Algorithms. WSOM 2001: 173-180 - 2000
- [c6]Bhaskar DasGupta, Barbara Hammer:
On Approximate Learning by Multi-layered Feedforward Circuits. ALT 2000: 264-278 - [c5]Barbara Hammer:
Limitations of hybrid systems. ESANN 2000: 213-218 - 1999
- [c4]Barbara Hammer:
Approximation capabilities of folding networks. ESANN 1999: 33-38 - 1998
- [c3]Barbara Hammer:
Training a sigmoidal network is difficult. ESANN 1998: 255-260 - [c2]Barbara Hammer:
On the Approximation Capability of Recurrent Neural Networks. NC 1998: 512-518 - 1997
- [c1]Barbara Hammer:
Generalization of Elman Networks. ICANN 1997: 409-414
Parts in Books or Collections
- 2009
- [p4]Michael Biehl, Barbara Hammer, Petra Schneider, Thomas Villmann:
Metric Learning for Prototype-Based Classification. Innovations in Neural Information Paradigms and Applications 2009: 183-199 - 2008
- [p3]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer, Martijn van der Werff, André M. Deelder, Rob A. E. M. Tollenaar:
Analysis of Spectral Data in Clinical Proteomics by Use of Learning Vector Quantizers. Computational Intelligence in Biomedicine and Bioinformatics 2008: 141-167 - 2007
- [p2]Barbara Hammer, Alessio Micheli, Alessandro Sperduti:
Adaptive Contextual Processing of Structured Data by Recursive Neural Networks: A Survey of Computational Properties. Perspectives of Neural-Symbolic Integration 2007: 67-94 - [p1]Peter Tiño, Barbara Hammer, Mikael Bodén:
Markovian Bias of Neural-based Architectures With Feedback Connections. Perspectives of Neural-Symbolic Integration 2007: 95-133
Editorship
- 2023
- [e16]Mirko Bunse, Barbara Hammer, Georg Krempl, Vincent Lemaire, Alaa Tharwat, Amal Saadallah:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2023), Torino, Italy, September 22nd, 2023. CEUR Workshop Proceedings 3470, CEUR-WS.org 2023 [contents] - 2022
- [e15]Joshua Zhexue Huang, Yi Pan, Barbara Hammer, Muhammad Khurram Khan, Xing Xie, Laizhong Cui, Yulin He:
9th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2022, Shenzhen, China, October 13-16, 2022. IEEE 2022, ISBN 978-1-6654-7330-9 [contents] - [e14]Georg Krempl, Vincent Lemaire, Daniel Kottke, Andreas Holzinger, Barbara Hammer:
Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2021) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Bilbao, Spain, September 13, 2021. CEUR Workshop Proceedings 3079, CEUR-WS.org 2022 [contents] - [e13]Daniel Kottke, Georg Krempl, Andreas Holzinger, Barbara Hammer:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2022), Grenoble, France, September 23, 2022. CEUR Workshop Proceedings 3259, CEUR-WS.org 2022 [contents] - 2021
- [e12]Yuxiao Dong, Nicolas Kourtellis, Barbara Hammer, José Antonio Lozano:
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part IV. Lecture Notes in Computer Science 12978, Springer 2021, ISBN 978-3-030-86513-9 [contents] - [e11]Yuxiao Dong, Nicolas Kourtellis, Barbara Hammer, José Antonio Lozano:
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part V. Lecture Notes in Computer Science 12979, Springer 2021, ISBN 978-3-030-86516-0 [contents] - 2018
- [e10]Vera Kurková, Yannis Manolopoulos, Barbara Hammer, Lazaros S. Iliadis, Ilias Maglogiannis:
Artificial Neural Networks and Machine Learning - ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part I. Lecture Notes in Computer Science 11139, Springer 2018, ISBN 978-3-030-01417-9 [contents] - [e9]Vera Kurková, Yannis Manolopoulos, Barbara Hammer, Lazaros S. Iliadis, Ilias Maglogiannis:
Artificial Neural Networks and Machine Learning - ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part II. Lecture Notes in Computer Science 11140, Springer 2018, ISBN 978-3-030-01420-9 [contents] - [e8]Vera Kurková, Yannis Manolopoulos, Barbara Hammer, Lazaros S. Iliadis, Ilias Maglogiannis:
Artificial Neural Networks and Machine Learning - ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III. Lecture Notes in Computer Science 11141, Springer 2018, ISBN 978-3-030-01423-0 [contents] - 2013
- [e7]Ebad Banissi, Hanane Azzag, Mark W. McK. Bannatyne, Stefan Bertschi, Fatma Bouali, Remo Burkhard, John Counsell, Alfredo Cuzzocrea, Martin J. Eppler, Barbara Hammer, Mustapha Lebbah, Francis T. Marchese, Muhammad Sarfraz, Anna Ursyn, Gilles Venturini, Theodor G. Wyeld:
17th International Conference on Information Visualisation, IV 2013, London, United Kingdom, July 16-18, 2013. IEEE Computer Society 2013, ISBN 978-0-7695-5049-7 [contents] - 2010
- [e6]Barbara Hammer, Pascal Hitzler, Wolfgang Maass, Marc Toussaint:
Learning paradigms in dynamic environments, 25.07. - 30.07.2010. Dagstuhl Seminar Proceedings 10302, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany 2010 [contents] - 2009
- [e5]Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann:
Similarity-Based Clustering, Recent Developments and Biomedical Applications [outcome of a Dagstuhl Seminar]. Lecture Notes in Computer Science 5400, Springer 2009, ISBN 978-3-642-01804-6 [contents] - [e4]Michael Biehl, Barbara Hammer, Sepp Hochreiter, Stefan C. Kremer, Thomas Villmann:
Similarity-based learning on structures, 15.02. - 20.02.2009. Dagstuhl Seminar Proceedings 09081, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany 2009 [contents] - 2008
- [e3]Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass:
Recurrent Neural Networks - Models, Capacities, and Applications, 20.01. - 25.01.2008. Dagstuhl Seminar Proceedings 08041, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2008 [contents] - 2007
- [e2]Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann:
Similarity-based Clustering and its Application to Medicine and Biology, 25.03. - 30.03.2007. Dagstuhl Seminar Proceedings 07131, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2007 [contents] - [e1]Barbara Hammer, Pascal Hitzler:
Perspectives of Neural-Symbolic Integration. Studies in Computational Intelligence 77, Springer 2007, ISBN 978-3-540-73953-1 [contents]
Reference Works
- 2009
- [r1]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer:
Prototype Based Classification in Bioinformatics. Encyclopedia of Artificial Intelligence 2009: 1337-1342
Informal and Other Publications
- 2024
- [i108]Valerie Vaquet, Fabian Hinder, Barbara Hammer:
Investigating the Suitability of Concept Drift Detection for Detecting Leakages in Water Distribution Networks. CoRR abs/2401.01733 (2024) - [i107]Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier:
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. CoRR abs/2401.12069 (2024) - [i106]Patrick Kolpaczki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier:
SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification. CoRR abs/2401.13371 (2024) - [i105]Sarah Schröder, Alexander Schulz, Fabian Hinder, Barbara Hammer:
Semantic Properties of cosine based bias scores for word embeddings. CoRR abs/2401.15499 (2024) - [i104]André Artelt, Shubham Sharma, Freddy Lécué, Barbara Hammer:
The Effect of Data Poisoning on Counterfactual Explanations. CoRR abs/2402.08290 (2024) - [i103]Tristan Kenneweg, Philip Kenneweg, Barbara Hammer:
Retrieval Augmented Generation Systems: Automatic Dataset Creation, Evaluation and Boolean Agent Setup. CoRR abs/2403.00820 (2024) - [i102]Philip Kenneweg, Leonardo Galli, Tristan Kenneweg, Barbara Hammer:
Faster Convergence for Transformer Fine-tuning with Line Search Methods. CoRR abs/2403.18506 (2024) - [i101]Philip Kenneweg, Tristan Kenneweg, Barbara Hammer:
Improving Line Search Methods for Large Scale Neural Network Training. CoRR abs/2403.18519 (2024) - [i100]Philip Kenneweg, Sarah Schröder, Barbara Hammer:
Neural Architecture Search for Sentence Classification with BERT. CoRR abs/2403.18547 (2024) - [i99]Philip Kenneweg, Sarah Schröder, Alexander Schulz, Barbara Hammer:
Debiasing Sentence Embedders through Contrastive Word Pairs. CoRR abs/2403.18555 (2024) - [i98]Inaam Ashraf, Janine Strotherm, Luca Hermes, Barbara Hammer:
Physics-Informed Graph Neural Networks for Water Distribution Systems. CoRR abs/2403.18570 (2024) - [i97]Isaac Roberts, Alexander Schulz, Luca Hermes, Barbara Hammer:
Targeted Visualization of the Backbone of Encoder LLMs. CoRR abs/2403.18872 (2024) - [i96]Philip Kenneweg, Alexander Schulz, Sarah Schröder, Barbara Hammer:
Intelligent Learning Rate Distribution to reduce Catastrophic Forgetting in Transformers. CoRR abs/2404.01317 (2024) - 2023
- [i95]Valerie Vaquet, Fabian Hinder, Johannes Brinkrolf, Barbara Hammer:
Combining self-labeling and demand based active learning for non-stationary data streams. CoRR abs/2302.04141 (2023) - [i94]Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer:
SHAP-IQ: Unified Approximation of any-order Shapley Interactions. CoRR abs/2303.01179 (2023) - [i93]Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier:
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams. CoRR abs/2303.01181 (2023) - [i92]Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer:
Model Based Explanations of Concept Drift. CoRR abs/2303.09331 (2023) - [i91]Paul Stahlhofen, André Artelt, Luca Hermes, Barbara Hammer:
Adversarial Attacks on Leakage Detectors in Water Distribution Networks. CoRR abs/2306.06107 (2023) - [i90]Ulrike Kuhl, André Artelt, Barbara Hammer:
For Better or Worse: The Impact of Counterfactual Explanations' Directionality on User Behavior in xAI. CoRR abs/2306.07637 (2023) - [i89]Maximilian Muschalik, Fabian Fumagalli, Rohit Jagtani, Barbara Hammer, Eyke Hüllermeier:
iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios. CoRR abs/2306.07775 (2023) - [i88]Janine Strotherm, Alissa Müller, Barbara Hammer, Benjamin Paaßen:
Fairness in KI-Systemen. CoRR abs/2307.08486 (2023) - [i87]Fabian Hinder, Valerie Vaquet, Barbara Hammer:
One or Two Things We know about Concept Drift - A Survey on Monitoring Evolving Environments. CoRR abs/2310.15826 (2023) - [i86]Valerie Vaquet, Fabian Hinder, Kathrin Lammers, Jonas Vaquet, Barbara Hammer:
Localization of Small Leakages in Water Distribution Networks using Concept Drift Explanation Methods. CoRR abs/2310.15830 (2023) - [i85]Roel Visser, Tobias M. Peters, Ingrid Scharlau, Barbara Hammer:
Trust, distrust, and appropriate reliance in (X)AI: a survey of empirical evaluation of user trust. CoRR abs/2312.02034 (2023) - [i84]Fabian Hinder, Valerie Vaquet, Barbara Hammer:
A Remark on Concept Drift for Dependent Data. CoRR abs/2312.10212 (2023) - 2022
- [i83]Luca Hermes, Barbara Hammer, Andrew Melnik, Riza Velioglu, Markus Vieth, Malte Schilling:
A Graph-based U-Net Model for Predicting Traffic in unseen Cities. CoRR abs/2202.06725 (2022) - [i82]André Artelt, Johannes Brinkrolf, Roel Visser, Barbara Hammer:
Explaining Reject Options of Learning Vector Quantization Classifiers. CoRR abs/2202.07244 (2022) - [i81]Fabian Hinder, Valerie Vaquet, Barbara Hammer:
Suitability of Different Metric Choices for Concept Drift Detection. CoRR abs/2202.09486 (2022) - [i80]Lisa Langnickel, Alexander Schulz, Barbara Hammer, Juliane Fluck:
BERT WEAVER: Using WEight AVERaging to Enable Lifelong Learning for Transformer-based Models. CoRR abs/2202.10101 (2022) - [i79]Sarah Schröder, Alexander Schulz, Philip Kenneweg, Robert Feldhans, Fabian Hinder, Barbara Hammer:
The SAME score: Improved cosine based bias score for word embeddings. CoRR abs/2203.14603 (2022) - [i78]Jonathan Jakob, André Artelt, Martina Hasenjäger, Barbara Hammer:
SAM-kNN Regressor for Online Learning in Water Distribution Networks. CoRR abs/2204.01436 (2022) - [i77]Andrea Castellani, Sebastian Schmitt, Barbara Hammer:
Stream-based Active Learning with Verification Latency in Non-stationary Environments. CoRR abs/2204.06822 (2022) - [i76]Ulrike Kuhl, André Artelt, Barbara Hammer:
Let's Go to the Alien Zoo: Introducing an Experimental Framework to Study Usability of Counterfactual Explanations for Machine Learning. CoRR abs/2205.03398 (2022) - [i75]Ulrike Kuhl, André Artelt, Barbara Hammer:
Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract Setting. CoRR abs/2205.05515 (2022) - [i74]Fabian Hinder, André Artelt, Valerie Vaquet, Barbara Hammer:
Precise Change Point Detection using Spectral Drift Detection. CoRR abs/2205.06507 (2022) - [i73]André Artelt, Roel Visser, Barbara Hammer:
Model Agnostic Local Explanations of Reject. CoRR abs/2205.07623 (2022) - [i72]André Artelt, Stelios G. Vrachimis, Demetrios G. Eliades, Marios M. Polycarpou, Barbara Hammer:
One Explanation to Rule them All - Ensemble Consistent Explanations. CoRR abs/2205.08974 (2022) - [i71]André Artelt, Alexander Schulz, Barbara Hammer:
"Why Here and Not There?" - Diverse Contrasting Explanations of Dimensionality Reduction. CoRR abs/2206.07391 (2022) - [i70]André Artelt, Barbara Hammer:
"Even if ..." - Diverse Semifactual Explanations of Reject. CoRR abs/2207.01898 (2022) - [i69]Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer:
Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams. CoRR abs/2209.01939 (2022) - [i68]Inaam Ashraf, Luca Hermes, André Artelt, Barbara Hammer:
Spatial Graph Convolution Neural Networks for Water Distribution Systems. CoRR abs/2211.09587 (2022) - [i67]Dominik Stallmann, Philip Kenneweg, Barbara Hammer:
Novel transfer learning schemes based on Siamese networks and synthetic data. CoRR abs/2211.11308 (2022) - [i66]André Artelt, Kleanthis Malialis, Christos G. Panayiotou, Marios M. Polycarpou, Barbara Hammer:
Unsupervised Unlearning of Concept Drift with Autoencoders. CoRR abs/2211.12989 (2022) - [i65]André Artelt, Barbara Hammer:
"Explain it in the Same Way!" - Model-Agnostic Group Fairness of Counterfactual Explanations. CoRR abs/2211.14858 (2022) - [i64]Riza Velioglu, Jan Philip Göpfert, André Artelt, Barbara Hammer:
Explainable Artificial Intelligence for Improved Modeling of Processes. CoRR abs/2212.00695 (2022) - [i63]Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer:
On the Change of Decision Boundaries and Loss in Learning with Concept Drift. CoRR abs/2212.01223 (2022) - 2021
- [i62]André Artelt, Barbara Hammer:
Fairness and Robustness of Contrasting Explanations. CoRR abs/2103.02354 (2021) - [i61]André Artelt, Fabian Hinder, Valerie Vaquet, Robert Feldhans, Barbara Hammer:
Contrastive Explanations for Explaining Model Adaptations. CoRR abs/2104.02459 (2021) - [i60]Andrea Castellani, Sebastian Schmitt, Barbara Hammer:
Estimating the electrical power output of industrial devices with end-to-end time-series classification in the presence of label noise. CoRR abs/2105.00349 (2021) - [i59]Benjamin Paaßen, Alexander Schulz, Barbara Hammer:
Reservoir Stack Machines. CoRR abs/2105.01616 (2021) - [i58]André Artelt, Barbara Hammer:
Convex optimization for actionable \& plausible counterfactual explanations. CoRR abs/2105.07630 (2021) - [i57]Daniel Wiens, Barbara Hammer:
Single-Step Adversarial Training for Semantic Segmentation. CoRR abs/2106.15998 (2021) - [i56]Andrea Castellani, Sebastian Schmitt, Barbara Hammer:
Task-Sensitive Concept Drift Detector with Constraint Embedding. CoRR abs/2108.06980 (2021) - [i55]Luca Hermes, Barbara Hammer, Malte Schilling:
Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting. CoRR abs/2110.04810 (2021) - [i54]Sarah Schröder, Alexander Schulz, Philip Kenneweg, Robert Feldhans, Fabian Hinder, Barbara Hammer:
Evaluating Metrics for Bias in Word Embeddings. CoRR abs/2111.07864 (2021) - 2020
- [i53]André Artelt, Barbara Hammer:
Convex Density Constraints for Computing Plausible Counterfactual Explanations. CoRR abs/2002.04862 (2020) - [i52]Lukas Pfannschmidt, Barbara Hammer:
Sequential Feature Classification in the Context of Redundancies. CoRR abs/2004.00658 (2020) - [i51]Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl:
Supervised Learning in the Presence of Concept Drift: A modelling framework. CoRR abs/2005.10531 (2020) - [i50]Fabian Hinder, Barbara Hammer:
Counterfactual Explanations of Concept Drift. CoRR abs/2006.12822 (2020) - [i49]Benjamin Paaßen, Alexander Schulz, Terrence C. Stewart, Barbara Hammer:
Reservoir Memory Machines as Neural Computers. CoRR abs/2009.06342 (2020) - [i48]André Artelt, Barbara Hammer:
Efficient computation of contrastive explanations. CoRR abs/2010.02647 (2020) - [i47]Dominik Stallmann, Jan Philip Göpfert, Julian Schmitz, Alexander Grünberger, Barbara Hammer:
Towards an Automatic Analysis of CHO-K1 Suspension Growth in Microfluidic Single-cell Cultivation. CoRR abs/2010.10124 (2020) - [i46]Jan Philip Göpfert, Heiko Wersing, Barbara Hammer:
Locally Adaptive Nearest Neighbors. CoRR abs/2011.03904 (2020) - [i45]Fabian Hinder, Jonathan Jakob, Barbara Hammer:
Analysis of Drifting Features. CoRR abs/2012.00499 (2020) - [i44]Jan Philip Göpfert, Ulrike Kuhl, Lukas Hindemith, Heiko Wersing, Barbara Hammer:
Intuitiveness in Active Teaching. CoRR abs/2012.13551 (2020) - 2019
- [i43]Lukas Pfannschmidt, Jonathan Jakob, Michael Biehl, Peter Tiño, Barbara Hammer:
Feature Relevance Bounds for Ordinal Regression. CoRR abs/1902.07662 (2019) - [i42]Jan Philip Göpfert, Heiko Wersing, Barbara Hammer:
Adversarial attacks hidden in plain sight. CoRR abs/1902.09286 (2019) - [i41]Lukas Pfannschmidt, Christina Göpfert, Ursula Neumann, Dominik Heider, Barbara Hammer:
FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration. CoRR abs/1903.00719 (2019) - [i40]Babak Hosseini, Barbara Hammer:
Multiple-Kernel Dictionary Learning for Reconstruction and Clustering of Unseen Multivariate Time-series. CoRR abs/1903.01867 (2019) - [i39]Babak Hosseini, Barbara Hammer:
Large-Margin Multiple Kernel Learning for Discriminative Features Selection and Representation Learning. CoRR abs/1903.03364 (2019) - [i38]Babak Hosseini, Felix Hülsmann, Mario Botsch, Barbara Hammer:
Non-Negative Kernel Sparse Coding for the Classification of Motion Data. CoRR abs/1903.03891 (2019) - [i37]Babak Hosseini, Barbara Hammer:
Confident Kernel Sparse Coding and Dictionary Learning. CoRR abs/1903.05219 (2019) - [i36]Babak Hosseini, Barbara Hammer:
Non-Negative Local Sparse Coding for Subspace Clustering. CoRR abs/1903.05239 (2019) - [i35]Michael Biehl, Fthi Abadi, Christina Göpfert, Barbara Hammer:
Prototype-based classifiers in the presence of concept drift: A modelling framework. CoRR abs/1903.07273 (2019) - [i34]Christina Göpfert, Jan Philip Göpfert, Barbara Hammer:
Adversarial Robustness Curves. CoRR abs/1908.00096 (2019) - [i33]André Artelt, Barbara Hammer:
Efficient computation of counterfactual explanations of LVQ models. CoRR abs/1908.00735 (2019) - [i32]Alexander Schulz, Fabian Hinder, Barbara Hammer:
DeepView: Visualizing the behavior of deep neural networks in a part of the data space. CoRR abs/1909.09154 (2019) - [i31]Babak Hosseini, Barbara Hammer:
Interpretable Discriminative Dimensionality Reduction and Feature Selection on the Manifold. CoRR abs/1909.09218 (2019) - [i30]Jan Philip Göpfert, Heiko Wersing, Barbara Hammer:
Recovering Localized Adversarial Attacks. CoRR abs/1910.09239 (2019) - [i29]Babak Hosseini, Barbara Hammer:
Interpretable Multiple-Kernel Prototype Learning for Discriminative Representation and Feature Selection. CoRR abs/1911.03949 (2019) - [i28]Babak Hosseini, Romain Montagné, Barbara Hammer:
Deep-Aligned Convolutional Neural Network for Skeleton-based Action Recognition and Segmentation. CoRR abs/1911.04969 (2019) - [i27]André Artelt, Barbara Hammer:
On the computation of counterfactual explanations - A survey. CoRR abs/1911.07749 (2019) - [i26]Fabian Hinder, André Artelt, Barbara Hammer:
A probability theoretic approach to drifting data in continuous time domains. CoRR abs/1912.01969 (2019) - [i25]Lukas Pfannschmidt, Jonathan Jakob, Fabian Hinder, Michael Biehl, Peter Tiño, Barbara Hammer:
Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information. CoRR abs/1912.04832 (2019) - 2018
- [i24]Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli, Barbara Hammer:
Tree Edit Distance Learning via Adaptive Symbol Embeddings. CoRR abs/1806.05009 (2018) - [i23]Cagatay Turkay, Nicola Pezzotti, Carsten Binnig, Hendrik Strobelt, Barbara Hammer, Daniel A. Keim, Jean-Daniel Fekete, Themis Palpanas, Yunhai Wang, Florin Rusu:
Progressive Data Science: Potential and Challenges. CoRR abs/1812.08032 (2018) - 2017
- [i22]Benjamin Paaßen, Christina Göpfert, Barbara Hammer:
Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces. CoRR abs/1704.06498 (2017) - [i21]Benjamin Paaßen, Barbara Hammer, Thomas William Price, Tiffany Barnes, Sebastian Gross, Niels Pinkwart:
The Continuous Hint Factory - Providing Hints in Vast and Sparsely Populated Edit Distance Spaces. CoRR abs/1708.06564 (2017) - [i20]Benjamin Paaßen, Alexander Schulz, Janne Hahne, Barbara Hammer:
Expectation maximization transfer learning and its application for bionic hand prostheses. CoRR abs/1711.09256 (2017) - 2016
- [i19]Babak Hosseini, Barbara Hammer:
Efficient Metric Learning for the Analysis of Motion Data. CoRR abs/1610.05083 (2016) - [i18]Babak Hosseini, Barbara Hammer:
Feasibility Based-Large Margin Nearest Neighbor Metric Learning. CoRR abs/1610.05710 (2016) - 2015
- [i17]Lydia Fischer, Barbara Hammer, Heiko Wersing:
Optimum Reject Options for Prototype-based Classification. CoRR abs/1503.06549 (2015) - 2011
- [i16]Frank-Michael Schleif, Andrej Gisbrecht, Barbara Hammer:
Supervised learning of short and high-dimensional temporal sequences for life science measurements. CoRR abs/1110.2416 (2011) - [i15]Wouter Lueks, Bassam Mokbel, Michael Biehl, Barbara Hammer:
How to Evaluate Dimensionality Reduction? - Improving the Co-ranking Matrix. CoRR abs/1110.3917 (2011) - [i14]Michael Biehl, Barbara Hammer, Erzsébet Merényi, Alessandro Sperduti, Thomas Villmann:
Learning in the context of very high dimensional data (Dagstuhl Seminar 11341). Dagstuhl Reports 1(8): 67-95 (2011) - 2010
- [i13]Barbara Hammer, Kerstin Bunte, Michael Biehl:
Some steps towards a general principle for dimensionality reduction mappings. Learning paradigms in dynamic environments 2010 - [i12]Barbara Hammer, Pascal Hitzler, Wolfgang Maass, Marc Toussaint:
10302 Abstracts Collection - Learning paradigms in dynamic environments. Learning paradigms in dynamic environments 2010 - [i11]Barbara Hammer, Pascal Hitzler, Wolfgang Maass, Marc Toussaint:
10302 Summary - Learning paradigms in dynamic environments. Learning paradigms in dynamic environments 2010 - 2009
- [i10]Michael Biehl, Barbara Hammer, Sepp Hochreiter, Stefan C. Kremer, Thomas Villmann:
09081 Abstracts Collection - Similarity-based learning on structures. Similarity-based learning on structures 2009 - [i9]Michael Biehl, Barbara Hammer, Sepp Hochreiter, Stefan C. Kremer, Thomas Villmann:
09081 Summary - Similarity-based learning on structures. Similarity-based learning on structures 2009 - [i8]Barbara Hammer, Alexander Hasenfuß, Fabrice Rossi:
Median topographic maps for biomedical data sets. CoRR abs/0909.0638 (2009) - 2008
- [i7]Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass:
08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008 - [i6]Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass:
08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008 - 2007
- [i5]Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann:
07131 Summary -- Similarity-based Clustering and its Application to Medicine and Biology. Similarity-based Clustering and its Application to Medicine and Biology 2007 - [i4]Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann:
07131 Abstracts Collection -- Similarity-based Clustering and its Application to Medicine and Biology. Similarity-based Clustering and its Application to Medicine and Biology 2007 - [i3]Barbara Hammer, Alexander Hasenfuss:
Relational Clustering. Similarity-based Clustering and its Application to Medicine and Biology 2007 - [i2]Barbara Hammer, Alessio Micheli, Alessandro Sperduti:
A general framework for unsupervised preocessing of structured data. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007 - [i1]Aree Witoelar, Michael Biehl, Barbara Hammer:
Learning Vector Quantization: generalization ability and dynamics of competing prototypes. Similarity-based Clustering and its Application to Medicine and Biology 2007
Coauthor Index
[j123] [j120] [j118] [j115] [j113] [c265] [c261] [c254] [c251] [c246] [c245] [c243] [c241] [c239] [c235] [c234] [c230] [c228] [c226] [c224] [c214] [c213] [c210] [c204] [c201] [c198] [c197] [i104] [i91] [i90] [i82] [i78] [i76] [i75] [i74] [i73] [i72] [i71] [i70] [i68] [i66] [i65] [i64] [i62] [i61] [i58] [i53] [i48] [i33] [i27] [i26]
[j108] [j99] [j91] [j80] [j58] [j55] [j54] [j51] [j47] [j45] [j42] [j40] [j37] [j36] [j33] [j29] [j27] [j21] [c190] [c182] [c161] [c142] [c137] [c136] [c124] [c123] [c103] [c90] [c89] [c88] [c81] [c79] [c77] [c72] [c70] [c69] [c67] [c64] [c63] [c57] [c50] [c48] [c31] [p4] [e5] [e4] [e2] [i51] [i43] [i35] [i25] [i15] [i14] [i13] [i10] [i9] [i5] [i4] [i1]
Alexander Hasenfuss
aka: Alexander Hasenfuß
aka: Alexander Hasenfuß
Benjamin Paaßen
aka: Benjamin Paassen
aka: Benjamin Paassen
[j80] [j79] [j75] [j65] [j64] [j63] [j60] [j59] [j54] [j53] [j44] [j39] [j35] [j34] [j32] [j31] [j26] [j24] [j22] [c192] [c142] [c119] [c114] [c111] [c110] [c102] [c101] [c100] [c98] [c96] [c95] [c91] [c86] [c85] [c84] [c83] [c82] [c79] [c74] [c73] [c72] [c52] [c46] [c45] [c44] [c43] [c41] [c40] [c39] [c37] [c34] [c33] [c32] [c27] [c26] [c21] [p3] [r1] [i16]
[j114] [j111] [j106] [j102] [j88] [j85] [j78] [j70] [c270] [c269] [c265] [c263] [c262] [c257] [c255] [c250] [c248] [c231] [c196] [c170] [c168] [c164] [c159] [c149] [c146] [c143] [c138] [c137] [c136] [c131] [c116] [c115] [c112] [c93] [i105] [i99] [i97] [i96] [i80] [i79] [i71] [i59] [i54] [i49] [i32] [i20]
[j76] [j66] [j58] [j54] [j53] [j51] [j46] [j44] [j40] [j39] [j35] [j34] [j32] [j31] [j30] [j28] [j26] [j25] [j24] [j23] [j22] [j20] [j14] [j13] [j7] [j4] [c161] [c150] [c142] [c132] [c127] [c126] [c124] [c123] [c117] [c106] [c88] [c79] [c77] [c74] [c73] [c72] [c69] [c66] [c61] [c60] [c57] [c56] [c54] [c52] [c49] [c46] [c45] [c44] [c43] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c30] [c29] [c27] [c26] [c22] [c21] [c19] [c17] [c14] [c13] [c10] [c7] [p4] [p3] [e5] [e4] [e2] [r1] [i14] [i10] [i9] [i5] [i4]
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