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ORCIDBarbara Hammer
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- 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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2020 – today
- 2020
[j98]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)- [j97]Lazaros S. Iliadis, Vera Kurková, Barbara Hammer:
Brain-inspired computing and machine learning. Neural Comput. Appl. 32(11): 6641-6643 (2020) - [c196]Jan Philip Göpfert, André Artelt, Heiko Wersing, Barbara Hammer:
Adversarial Attacks Hidden in Plain Sight. IDA 2020: 235-247 - [c195]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 - [i48]André Artelt, Barbara Hammer:
Convex Density Constraints for Computing Plausible Counterfactual Explanations. CoRR abs/2002.04862 (2020) - [i47]Lukas Pfannschmidt, Barbara Hammer:
Sequential Feature Classification in the Context of Redundancies. CoRR abs/2004.00658 (2020) - [i46]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) - [i45]Fabian Hinder, Barbara Hammer:
Counterfactual Explanations of Concept Drift. CoRR abs/2006.12822 (2020) - [i44]Benjamin Paaßen, Alexander Schulz, Terrence C. Stewart, Barbara Hammer:
Reservoir Memory Machines as Neural Computers. CoRR abs/2009.06342 (2020)
2010 – 2019
- 2019
- [j96]Johannes Brinkrolf, Christina Göpfert, Barbara Hammer:
Differential privacy for learning vector quantization. Neurocomputing 342: 125-136 (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 - [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
- [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) - [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 - [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] - [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
- [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) - [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 - [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
- [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) - [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 - [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
- [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. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 5(2): 51-73 (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 - [i17]Lydia Fischer, Barbara Hammer, Heiko Wersing:
Optimum Reject Options for Prototype-based Classification. CoRR abs/1503.06549 (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]