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Barbara Hammer
2010 – today
- 2013
[j60]Barbara Hammer, Daniel A. Keim, Neil D. Lawrence, Guy Lebanon: Preface: Intelligent interactive data visualization. Data Min. Knowl. Discov. 27(1): 1-3 (2013)- [j59]Bassam Mokbel, Wouter Lueks, Andrej Gisbrecht, Barbara Hammer: Visualizing the quality of dimensionality reduction. Neurocomputing 112: 109-123 (2013)
- [c114]Sebastian Gross, Bassam Mokbel, Barbara Hammer, Niels Pinkwart: Towards Providing Feedback to Students in Absence of Formalized Domain Models. AIED 2013: 644-648
- [c113]Sebastian Gross, Bassam Mokbel, Barbara Hammer, Niels Pinkwart: Towards a Domain-Independent ITS Middleware Architecture. ICALT 2013: 408-409
- [c112]Barbara Hammer, Andrej Gisbrecht, Alexander Schulz: Applications of Discriminative Dimensionality Reduction. ICPRAM 2013: 33-41
- [c111]Alexander Schulz, Andrej Gisbrecht, Barbara Hammer: Using Nonlinear Dimensionality Reduction to Visualize Classifiers. IWANN (1) 2013: 59-68
- [c110]Xibin Zhu, Frank-Michael Schleif, Barbara Hammer: Secure Semi-supervised Vector Quantization for Dissimilarity Data. IWANN (1) 2013: 347-356
- 2012
- [j58]Andrej Gisbrecht, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu, Barbara Hammer: Linear Time Relational Prototype Based Learning. Int. J. Neural Syst. 22(5) (2012)
- [j57]Xibin Zhu, Andrej Gisbrecht, Frank-Michael Schleif, Barbara Hammer: Approximation techniques for clustering dissimilarity data. Neurocomputing 90: 72-84 (2012)
- [j56]Marika Kästner, Barbara Hammer, Michael Biehl, Thomas Villmann: Functional relevance learning in generalized learning vector quantization. Neurocomputing 90: 85-95 (2012)
- [j55]
- [j54]
- [j53]Kerstin Bunte, Michael Biehl, Barbara Hammer: A General Framework for Dimensionality-Reducing Data Visualization Mapping. Neural Computation 24(3): 771-804 (2012)
- [j52]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)
- [c109]Frank-Michael Schleif, Xibin Zhu, Barbara Hammer: Soft Competitive Learning for Large Data Sets. ADBIS Workshops 2012: 141-151
- [c108]Bassam Mokbel, Sebastian Gross, Markus Lux, Niels Pinkwart, Barbara Hammer: How to Quantitatively Compare Data Dissimilarities for Unsupervised Machine Learning? ANNPR 2012: 1-13
- [c107]
- [c106]Sebastian Gross, Bassam Mokbel, Barbara Hammer, Niels Pinkwart: Feedback Provision Strategies in Intelligent Tutoring Systems Based on Clustered Solution Spaces. DeLFI 2012: 27-38
- [c105]Barbara Hammer, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu: White Box Classification of Dissimilarity Data. HAIS (1) 2012: 309-321
- [c104]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
- [c103]Frank-Michael Schleif, Xibin Zhu, Andrej Gisbrecht, Barbara Hammer: Fast approximated relational and kernel clustering. ICPR 2012: 1229-1232
- [c102]Andrej Gisbrecht, Daniela Hofmann, Barbara Hammer: Discriminative Dimensionality Reduction Mappings. IDA 2012: 126-138
- [c101]Frank-Michael Schleif, Xibin Zhu, Barbara Hammer: A Conformal Classifier for Dissimilarity Data. AIAI (2) 2012: 234-243
- [c100]Andrej Gisbrecht, Bassam Mokbel, Barbara Hammer: Linear basis-function t-SNE for fast nonlinear dimensionality reduction. IJCNN 2012: 1-8
- [c99]Frank-Michael Schleif, Andrej Gisbrecht, Barbara Hammer: Relevance learning for short high-dimensional time series in the life sciences. IJCNN 2012: 1-8
- [c98]Xibin Zhu, Frank-Michael Schleif, Barbara Hammer: Patch Processing for Relational Learning Vector Quantization. ISNN (1) 2012: 55-63
- [c97]Sebastian Gross, Xibin Zhu, Barbara Hammer, Niels Pinkwart: Cluster Based Feedback Provision Strategies in Intelligent Tutoring Systems. ITS 2012: 699-700
- 2011
- [j51]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer, Petra Schneider: Efficient Kernelized Prototype Based Classification. Int. J. Neural Syst. 21(6): 443-457 (2011)
- [j50]Banchar Arnonkijpanich, Alexander Hasenfuss, Barbara Hammer: Local matrix adaptation in topographic neural maps. Neurocomputing 74(4): 522-539 (2011)
- [j49]Kerstin Bunte, Barbara Hammer, Thomas Villmann, Michael Biehl, Axel Wismüller: Neighbor embedding XOM for dimension reduction and visualization. Neurocomputing 74(9): 1340-1350 (2011)
- [j48]Andrej Gisbrecht, Barbara Hammer: Relevance learning in generative topographic mapping. Neurocomputing 74(9): 1351-1358 (2011)
- [j47]Andrej Gisbrecht, Bassam Mokbel, Barbara Hammer: Relational generative topographic mapping. Neurocomputing 74(9): 1359-1371 (2011)
- [c96]Andrej Gisbrecht, Barbara Hammer, Frank-Michael Schleif, Xibin Zhu: Accelerating kernel clustering for biomedical data analysis. CIBCB 2011: 154-161
- [c95]
- [c94]
- [c93]Marika Kästner, Barbara Hammer, Michael Biehl, Thomas Villmann: Generalized functional relevance learning vector quantization. ESANN 2011
- [c92]
- [c91]Frank-Michael Schleif, Andrej Gisbrecht, Barbara Hammer: Accelerating Kernel Neural Gas. ICANN (1) 2011: 150-158
- [c90]Barbara Hammer, Frank-Michael Schleif, Xibin Zhu: Relational Extensions of Learning Vector Quantization. ICONIP (2) 2011: 481-489
- [c89]Barbara Hammer, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu: Prototype-Based Classification of Dissimilarity Data. IDA 2011: 185-197
- [c88]Andrej Gisbrecht, Frank-Michael Schleif, Xibin Zhu, Barbara Hammer: Linear Time Heuristics for Topographic Mapping of Dissimilarity Data. IDEAL 2011: 25-33
- [c87]Barbara Hammer, Andrej Gisbrecht, Alexander Hasenfuss, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu: Topographic Mapping of Dissimilarity Data. WSOM 2011: 1-15
- [c86]Barbara Hammer, Michael Biehl, Kerstin Bunte, Bassam Mokbel: A General Framework for Dimensionality Reduction for Large Data Sets. WSOM 2011: 277-287
- [i4]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)
- [i3]Wouter Lueks, Bassam Mokbel, Michael Biehl, Barbara Hammer: How to Evaluate Dimensionality Reduction? - Improving the Co-ranking Matrix. CoRR abs/1110.3917 (2011)
- [i2]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
- [j46]Marco Gori, Barbara Hammer, Pascal Hitzler, Guenther Palm: Perspectives and challenges for recurrent neural network training. Logic Journal of the IGPL 18(5): 617-619 (2010)
- [j45]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)
- [j44]Tina Geweniger, Dietlind Zühlke, Barbara Hammer, Thomas Villmann: Median fuzzy c-means for clustering dissimilarity data. Neurocomputing 73(7-9): 1109-1116 (2010)
- [j43]Petra Schneider, Michael Biehl, Barbara Hammer: Hyperparameter learning in probabilistic prototype-based models. Neurocomputing 73(7-9): 1117-1124 (2010)
- [j42]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)
- [j41]Barbara Hammer, Alexander Hasenfuss: Topographic Mapping of Large Dissimilarity Data Sets. Neural Computation 22(9): 2229-2284 (2010)
- [j40]Aree Witoelar, Anarta Ghosh, J. J. G. de Vries, Barbara Hammer, Michael Biehl: Window-Based Example Selection in Learning Vector Quantization. Neural Computation 22(11): 2924-2961 (2010)
- [j39]Banchar Arnonkijpanich, Alexander Hasenfuss, Barbara Hammer: Local matrix learning in clustering and applications for manifold visualization. Neural Networks 23(4): 476-486 (2010)
- [j38]Petra Schneider, Kerstin Bunte, Han Stiekema, Barbara Hammer, Thomas Villmann, Michael Biehl: Regularization in matrix relevance learning. IEEE Transactions on Neural Networks 21(5): 831-840 (2010)
- [c85]Banchar Arnonkijpanich, Barbara Hammer: Global Coordination Based on Matrix Neural Gas for Dynamic Texture Synthesis. ANNPR 2010: 84-95
- [c84]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
- [c83]Barbara Hammer, Alexander Hasenfuss: Clustering Very Large Dissimilarity Data Sets. ANNPR 2010: 259-273
- [c82]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
- [c81]
- [c80]
- [c79]
- [c78]Thomas Villmann, Sven Haase, Frank-Michael Schleif, Barbara Hammer: Divergence Based Online Learning in Vector Quantization. ICAISC (1) 2010: 479-486
- [c77]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer, Petra Schneider, Michael Biehl: Generalized Derivative Based Kernelized Learning Vector Quantization. IDEAL 2010: 21-28
- [c76]Andrej Gisbrecht, Bassam Mokbel, Alexander Hasenfuss, Barbara Hammer: Visualizing Dissimilarity Data Using Generative Topographic Mapping. KI 2010: 227-237
2000 – 2009
- 2009
- [j37]Frank-Michael Schleif, Thomas Villmann, Markus Kostrzewa, Barbara Hammer, Alexander Gammerman: Cancer informatics by prototype networks in mass spectrometry. Artificial Intelligence in Medicine 45(2-3): 215-228 (2009)
- [j36]Nikolai Alex, Alexander Hasenfuss, Barbara Hammer: Patch clustering for massive data sets. Neurocomputing 72(7-9): 1455-1469 (2009)
- [j35]Petra Schneider, Michael Biehl, Barbara Hammer: Distance Learning in Discriminative Vector Quantization. Neural Computation 21(10): 2942-2969 (2009)
- [j34]Petra Schneider, Michael Biehl, Barbara Hammer: Adaptive Relevance Matrices in Learning Vector Quantization. Neural Computation 21(12): 3532-3561 (2009)
- [c75]Kerstin Bunte, Barbara Hammer, Michael Biehl: Nonlinear Dimension Reduction and Visualization of Labeled Data. CAIP 2009: 1162-1170
- [c74]Thomas Villmann, Barbara Hammer, Michael Biehl: Some Theoretical Aspects of the Neural Gas Vector Quantizer. Similarity-Based Clustering 2009: 23-34
- [c73]Barbara Hammer, Alexander Hasenfuss, Fabrice Rossi: Median Topographic Maps for Biomedical Data Sets. Similarity-Based Clustering 2009: 92-117
- [c72]Kerstin Bunte, Barbara Hammer, Petra Schneider, Michael Biehl: Nonlinear Discriminative Data Visualization. ESANN 2009
- [c71]Tina Geweniger, Dietlind Zühlke, Barbara Hammer, Thomas Villmann: Median Variant of Fuzzy c-Means. ESANN 2009
- [c70]Barbara Hammer, Benjamin Schrauwen, Jochen J. Steil: Recent advances in efficient learning of recurrent networks. ESANN 2009
- [c69]Petra Schneider, Michael Biehl, Barbara Hammer: Hyperparameter Learning in Robust Soft LVQ. ESANN 2009
- [c68]
- [c67]Bassam Mokbel, Alexander Hasenfuss, Barbara Hammer: Graph-Based Representation of Symbolic Musical Data. GbRPR 2009: 42-51
- [c66]Tina Geweniger, Dietlind Zühlke, Barbara Hammer, Thomas Villmann: Fuzzy Variant of Affinity Propagation in Comparison to Median Fuzzy c-Means. WSOM 2009: 72-79
- [c65]Thomas Villmann, Barbara Hammer: Functional Principal Component Learning Using Oja's Method and Sobolev Norms. WSOM 2009: 325-333
- [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
- [e4]Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann (Eds.): 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
- [r1]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Prototype Based Classification in Bioinformatics. Encyclopedia of Artificial Intelligence 2009: 1337-1342
- [i1]Barbara Hammer, Alexander Hasenfuß, Fabrice Rossi: Median topographic maps for biomedical data sets. CoRR abs/0909.0638 (2009)
- 2008
- [j33]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 in Bioinformatics 9(2): 129-143 (2008)
- [j32]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Prototype based fuzzy classification in clinical proteomics. Int. J. Approx. Reasoning 47(1): 4-16 (2008)
- [j31]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)
- [c64]Alexander Hasenfuss, Barbara Hammer: Single Pass Clustering and Classification of Large Dissimilarity Datasets. Artificial Intelligence and Pattern Recognition 2008: 219-223
- [c63]Alexander Hasenfuss, Barbara Hammer, Fabrice Rossi: Patch Relational Neural Gas - Clustering of Huge Dissimilarity Datasets. ANNPR 2008: 1-12
- [c62]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
- [c61]Marc Strickert, Nese Sreenivasulu, Thomas Villmann, Barbara Hammer: Robust Centroid-Based Clustering using Derivatives of Pearson Correlation. BIOSIGNALS (2) 2008: 197-203
- [c60]Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: 08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008
- [c59]Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: 08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008
- [c58]
- [c57]Alexander Hasenfuss, Barbara Hammer, Tina Geweniger, Thomas Villmann: Magnification Control in Relational Neural Gas. ESANN 2008: 325-330
- [c56]Banchar Arnonkijpanich, Barbara Hammer, Alexander Hasenfuss, Chidchanok Lursinsap: Matrix Learning for Topographic Neural Maps. ICANN (1) 2008: 572-582
- [c55]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
- [c54]Tim Winkler, Jens Drieseberg, Kai Hormann, Alexander Hasenfuss, Barbara Hammer: Thinning Mesh Animations. VMV 2008: 149-158
- [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
- [e3]Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass (Eds.): 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
- 2007
- [j30]Frank-Michael Schleif, Barbara Hammer, Thomas Villmann: Margin-based active learning for LVQ networks. Neurocomputing 70(7-9): 1215-1224 (2007)
- [j29]Barbara Hammer, Alexander Hasenfuss, Thomas Villmann: Magnification control for batch neural gas. Neurocomputing 70(7-9): 1225-1234 (2007)
- [j28]Michael Biehl, Anarta Ghosh, Barbara Hammer: Dynamics and Generalization Ability of LVQ Algorithms. Journal of Machine Learning Research 8: 323-360 (2007)
- [c53]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
- [c52]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
- [c51]Barbara Hammer, Alexander Hasenfuss: Relational Clustering. Similarity-based Clustering and its Application to Medicine and Biology 2007
- [c50]Barbara Hammer, Alessio Micheli, Alessandro Sperduti: A general framework for unsupervised preocessing of structured data. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007
- [c49]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
- [c48]
- [c47]
- [c46]Aree Witoelar, Michael Biehl, Anarta Ghosh, Barbara Hammer: On the dynamics of Vector Quantization and Neural Gas. ESANN 2007: 127-132
- [c45]
- [c44]Barbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann, Marc Strickert, Udo Seiffert: Intuitive Clustering of Biological Data. IJCNN 2007: 1877-1882
- [c43]Alexander Hasenfuss, Barbara Hammer, Frank-Michael Schleif, Thomas Villmann: Neural Gas Clustering for Dissimilarity Data with Continuous Prototypes. IWANN 2007: 539-546
- [c42]Thomas Villmann, Frank-Michael Schleif, Erzsébet Merényi, Barbara Hammer: Fuzzy Labeled Self-Organizing Map for Classification of Spectra. IWANN 2007: 556-563
- [c41]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
- [c40]
- [c39]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps. WILF 2007: 563-570
- [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 Tino, Barbara Hammer, Mikael Bodén: Markovian Bias of Neural-based Architectures With Feedback Connections. Perspectives of Neural-Symbolic Integration 2007: 95-133
- [e2]Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann (Eds.): 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
- [e1]Barbara Hammer, Pascal Hitzler (Eds.): Perspectives of Neural-Symbolic Integration. Studies in Computational Intelligence 77, Springer 2007, ISBN 978-3-540-73953-1
- 2006
- [j27]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)
- [j26]Michael Biehl, Anarta Ghosh, Barbara Hammer: Learning vector quantization: The dynamics of winner-takes-all algorithms. Neurocomputing 69(7-9): 660-670 (2006)
- [j25]Thomas Villmann, Frank-Michael Schleif, Barbara Hammer: Prototype-based fuzzy classification with local relevance for proteomics. Neurocomputing 69(16-18): 2425-2428 (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)
- [c38]Barbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann: Supervised Batch Neural Gas. ANNPR 2006: 33-45
- [c37]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
- [c36]Thomas Villmann, Barbara Hammer, Udo Seiffert: Perspectives of Self-adapted Self-organizing Clustering in Organic Computing. BioADIT 2006: 141-159
- [c35]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
- [c34]Barbara Hammer, Alexander Hasenfuss, Thomas Villmann: Magnification control for batch neural gas. ESANN 2006: 7-12
- [c33]Udo Seiffert, Barbara Hammer, Samuel Kaski, Thomas Villmann: Neural networks and machine learning in bioinformatics - theory and applications. ESANN 2006: 521-532
- [c32]Frank-Michael Schleif, Barbara Hammer, Thomas Villmann: Margin based Active Learning for LVQ Networks. ESANN 2006: 539-544
- [c31]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
- [c30]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
- [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]
- [j16]Barbara Hammer, Alessio Micheli, Alessandro Sperduti: Universal Approximation Capability of Cascade Correlation for Structures. Neural Computation 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 Processing Letters 21(1): 21-44 (2005)
- [j13]Barbara Hammer, Marc Strickert, Thomas Villmann: On the Generalization Ability of GRLVQ Networks. Neural Processing Letters 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)
- [c29]Michael Biehl, Anarta Ghosh, Barbara Hammer: The dynamics of Learning Vector Quantization. ESANN 2005: 13-18
- [c28]Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann: Relevance learning for mental disease classification. ESANN 2005: 139-144
- [c27]
- [c26]Katharina Tluk von Toschanowitz, Barbara Hammer, Helge Ritter: Relevance determination in reinforcement learning. ESANN 2005: 369-374
- [c25]Thomas Villmann, Frank-Michael Schleif, Barbara Hammer: Fuzzy Labeled Soft Nearest Neighbor Classification with Relevance Learning. ICMLA 2005
- [c24]Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data. WILF 2005: 290-296
- 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)
- [c23]
- [c22]
- [c21]
- [c20]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
- [j9]Barbara Hammer, Peter Tiño: Recurrent Neural Networks with Small Weights Implement Definite Memory Machines. Neural Computation 15(8): 1897-1929 (2003)
- [j8]Peter Tiño, Barbara Hammer: Architectural Bias in Recurrent Neural Networks: Fractal Analysis. Neural Computation 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 Processing Letters 17(1): 43-53 (2003)
- [c19]
- [c18]
- [c17]Kai Gersmann, Barbara Hammer: Improving iterative repair strategies for scheduling with the SVM. ESANN 2003: 235-240
- 2002
- [j5]Barbara Hammer: Recurrent networks for structured data - A unifying approach and its properties. Cognitive Systems Research 3(2): 145-165 (2002)
- [j4]Barbara Hammer, Thomas Villmann: Generalized relevance learning vector quantization. Neural Networks 15(8-9): 1059-1068 (2002)
- [c16]
- [c15]Barbara Hammer, Jochen J. Steil: Perspectives on learning with recurrent neural networks. ESANN 2002: 357-368
- [c14]Barbara Hammer, Alessio Micheli, Alessandro Sperduti: A general framework for unsupervised processing of structured data. ESANN 2002: 389-394
- [c13]Barbara Hammer, Marc Strickert, Thomas Villmann: Learning Vector Quantization for Multimodal Data. ICANN 2002: 370-376
- [c12]Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann: Rule Extraction from Self-Organizing Networks. ICANN 2002: 877-883
- [c11]Peter Tiño, Barbara Hammer: Architectural Bias in Recurrent Neural Networks - Fractal Analysis. ICANN 2002: 1359-1364
- 2001
- [j3]Barbara Hammer: Generalization Ability of Folding Networks. IEEE Trans. Knowl. Data Eng. 13(2): 196-206 (2001)
- [c10]Thorsten Bojer, Barbara Hammer, Daniel Schunk, Katharina Tluk von Toschanowitz: Relevance determination in Learning Vector Quantization. ESANN 2001: 271-276
- [c9]
- [c8]Marc Strickert, Thorsten Bojer, Barbara Hammer: Generalized Relevance LVQ for Time Series. ICANN 2001: 677-683
- [c7]
- 2000
- [j2]Barbara Hammer: On the approximation capability of recurrent neural networks. Neurocomputing 31(1-4): 107-123 (2000)
- [c6]Bhaskar DasGupta, Barbara Hammer: On Approximate Learning by Multi-layered Feedforward Circuits. ALT 2000: 264-278
- [c5]
1990 – 1999
- 1999
- [j1]
- [c4]
- 1998
- [c3]
- [c2]
- 1997
- [c1]
- 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
Coauthor Index
[j56] [j52] [j51] [j49] [c93] [i2] [j44] [j42] [j38] [c84] [c82] [c79] [c78] [c77] [j37] [c74] [c71] [c66] [c65] [p4] [e4] [r1] [j33] [j32] [c62] [c61] [c57] [c55] [p3] [j30] [j29] [c53] [c52] [c47] [c44] [c43] [c42] [c41] [c39] [e2] [j27] [j25] [j24] [j23] [j22] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [j20] [j14] [j13] [c28] [c27] [c25] [c24] [c21] [c20] [j7] [c18] [j4] [c16] [c13] [c12] [c9]
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last updated on 2013-10-02 11:11 CEST by the dblp team