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Barbara Hammer Vis

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*2009
104EEKerstin Bunte, Barbara Hammer, Michael Biehl: Nonlinear Dimension Reduction and Visualization of Labeled Data. CAIP 2009: 1162-1170
103EEBassam Mokbel, Alexander Hasenfuss, Barbara Hammer: Graph-Based Representation of Symbolic Musical Data. GbRPR 2009: 42-51
102EEThomas Villmann, Barbara Hammer: Functional Principal Component Learning Using Oja's Method and Sobolev Norms. WSOM 2009: 325-333
101EETina Geweniger, D. Zühlke, Barbara Hammer, Thomas Villmann: Fuzzy Variant of Affinity Propagation in Comparison to Median Fuzzy c-Means. WSOM 2009: 72-79
100EEFrank-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)
99EEBarbara Hammer, Alexander Hasenfuß, Fabrice Rossi: Median topographic maps for biomedical data sets CoRR abs/0909.0638: (2009)
98EENikolai Alex, Alexander Hasenfuss, Barbara Hammer: Patch clustering for massive data sets. Neurocomputing 72(7-9): 1455-1469 (2009)
2008
97 Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: Recurrent Neural Networks - Models, Capacities, and Applications, 20.01. - 25.01.2008 Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2008
96EEAlexander Hasenfuss, Barbara Hammer, Fabrice Rossi: Patch Relational Neural Gas - Clustering of Huge Dissimilarity Datasets. ANNPR 2008: 1-12
95EEMarc Strickert, Petra Schneider, Jens Keilwagen, Thomas Villmann, Michael Biehl, Barbara Hammer: Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics. ANNPR 2008: 78-89
94 Alexander Hasenfuss, Barbara Hammer: Single Pass Clustering and Classification of Large Dissimilarity Datasets. Artificial Intelligence and Pattern Recognition 2008: 219-223
93 Marc Strickert, Nese Sreenivasulu, Thomas Villmann, Barbara Hammer: Robust Centroid-Based Clustering using Derivatives of Pearson Correlation. BIOSIGNALS (2) 2008: 197-203
92EENikolai Alex, Barbara Hammer: Parallelizing single patch pass clustering. ESANN 2008: 227-232
91EEAlexander Hasenfuss, Barbara Hammer, Tina Geweniger, Thomas Villmann: Magnification Control in Relational Neural Gas. ESANN 2008: 325-330
90EEBanchar Arnonkijpanich, Barbara Hammer, Alexander Hasenfuss, Chidchanok Lursinsap: Matrix Learning for Topographic Neural Maps. ICANN (1) 2008: 572-582
89EETina 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
88EELuc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: 08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008
87EELuc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: 08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008
86EEFrank-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
85EEThomas 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)
84EEFrank-Michael Schleif, Thomas Villmann, Barbara Hammer: Prototype based fuzzy classification in clinical proteomics. Int. J. Approx. Reasoning 47(1): 4-16 (2008)
83EEAree Witoelar, Michael Biehl, Anarta Ghosh, Barbara Hammer: Learning dynamics and robustness of vector quantization and neural gas. Neurocomputing 71(7-9): 1210-1219 (2008)
2007
82 Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann: Similarity-based Clustering and its Application to Medicine and Biology, 25.03. - 30.03.2007 Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2007
81 Barbara Hammer, Pascal Hitzler: Perspectives of Neural-Symbolic Integration Springer 2007
80EEAree Witoelar, Michael Biehl, Anarta Ghosh, Barbara Hammer: On the dynamics of Vector Quantization and Neural Gas. ESANN 2007: 127-132
79EEPetra Schneider, Michael Biehl, Barbara Hammer: Relevance matrices in LVQ. ESANN 2007: 37-42
78EEBarbara Hammer, Thomas Villmann: How to process uncertainty in machine learning?. ESANN 2007: 79-90
77EEAlexander Hasenfuss, Barbara Hammer: Relational Topographic Maps. IDA 2007: 93-105
76EEBarbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann, Marc Strickert, Udo Seiffert: Intuitive Clustering of Biological Data. IJCNN 2007: 1877-1882
75EEFrank-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
74EEAlexander Hasenfuss, Barbara Hammer, Frank-Michael Schleif, Thomas Villmann: Neural Gas Clustering for Dissimilarity Data with Continuous Prototypes. IWANN 2007: 539-546
73EEThomas Villmann, Frank-Michael Schleif, Erzsébet Merényi, Barbara Hammer: Fuzzy Labeled Self-Organizing Map for Classification of Spectra. IWANN 2007: 556-563
72EEBarbara Hammer, Alexander Hasenfuss: Relational Neural Gas. KI 2007: 190-204
71EEBarbara Hammer, Alessio Micheli, Alessandro Sperduti: A general framework for unsupervised preocessing of structured data. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007
70EEMichael 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
69EEMichael 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
68EEAree 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
67EEBarbara Hammer, Alexander Hasenfuss: Relational Clustering. Similarity-based Clustering and its Application to Medicine and Biology 2007
66EEFrank-Michael Schleif, Thomas Villmann, Barbara Hammer: Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps. WILF 2007: 563-570
65EEBarbara 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
64EEPeter Tino, Barbara Hammer, Mikael Bodén: Markovian Bias of Neural-based Architectures With Feedback Connections. Perspectives of Neural-Symbolic Integration 2007: 95-133
63EEFrank-Michael Schleif, Barbara Hammer, Thomas Villmann: Margin-based active learning for LVQ networks. Neurocomputing 70(7-9): 1215-1224 (2007)
62EEBarbara Hammer, Alexander Hasenfuss, Thomas Villmann: Magnification control for batch neural gas. Neurocomputing 70(7-9): 1225-1234 (2007)
2006
61EEBarbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann: Supervised Batch Neural Gas. ANNPR 2006: 33-45
60EEThomas 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
59EEThomas Villmann, Barbara Hammer, Udo Seiffert: Perspectives of Self-adapted Self-organizing Clustering in Organic Computing. BioADIT 2006: 141-159
58EEFrank-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
57EEUdo Seiffert, Barbara Hammer, Samuel Kaski, Thomas Villmann: Neural networks and machine learning in bioinformatics - theory and applications. ESANN 2006: 521-532
56EEFrank-Michael Schleif, Barbara Hammer, Thomas Villmann: Margin based Active Learning for LVQ Networks. ESANN 2006: 539-544
55EEBarbara Hammer, Alexander Hasenfuss, Thomas Villmann: Magnification control for batch neural gas. ESANN 2006: 7-12
54EEBarbara 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
53EEThomas Villmann, Barbara Hammer, Frank-Michael Schleif, Tina Geweniger, Tom Fischer, Marie Cottrell: Prototype Based Classification Using Information Theoretic Learning. ICONIP (2) 2006: 40-49
52EEThomas 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)
51EEMarie Cottrell, Barbara Hammer, Alexander Hasenfuss, Thomas Villmann: Batch and median neural gas. Neural Networks 19(6-7): 762-771 (2006)
50EEThomas 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)
49EEAnarta Ghosh, Michael Biehl, Barbara Hammer: Performance analysis of LVQ algorithms: A statistical physics approach. Neural Networks 19(6-7): 817-829 (2006)
48EEThomas Villmann, Frank-Michael Schleif, Barbara Hammer: Prototype-based fuzzy classification with local relevance for proteomics. Neurocomputing 69(16-18): 2425-2428 (2006)
47EEMarc 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)
46EEMichael Biehl, Anarta Ghosh, Barbara Hammer: Learning vector quantization: The dynamics of winner-takes-all algorithms. Neurocomputing 69(7-9): 660-670 (2006)
2005
45EEMichael Biehl, Anarta Ghosh, Barbara Hammer: The dynamics of Learning Vector Quantization. ESANN 2005: 13-18
44EEBarbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann: Relevance learning for mental disease classification. ESANN 2005: 139-144
43EEBarbara Hammer, Thomas Villmann: Classification using non-standard metrics. ESANN 2005: 303-316
42EEKatharina Tluk von Toschanowitz, Barbara Hammer, Helge Ritter: Relevance determination in reinforcement learning. ESANN 2005: 369-374
41EEFrank-Michael Schleif, Thomas Villmann, Barbara Hammer: Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data. WILF 2005: 290-296
40EEBarbara Hammer, Alessio Micheli, Alessandro Sperduti: Universal Approximation Capability of Cascade Correlation for Structures. Neural Computation 17(5): 1109-1159 (2005)
39EEBarbara Hammer, Craig Saunders, Alessandro Sperduti: Special issue on neural networks and kernel methods for structured domains. Neural Networks 18(8): 1015-1018 (2005)
38EEBarbara Hammer, Marc Strickert, Thomas Villmann: Supervised Neural Gas with General Similarity Measure. Neural Processing Letters 21(1): 21-44 (2005)
37EEBarbara Hammer, Marc Strickert, Thomas Villmann: On the Generalization Ability of GRLVQ Networks. Neural Processing Letters 21(2): 109-120 (2005)
36EEMarie Cottrell, Barbara Hammer, Thomas Villmann: New Aspects in Neurocomputing. Neurocomputing 63: 1-3 (2005)
35EEKai Gersmann, Barbara Hammer: Improving iterative repair strategies for scheduling with the SVM. Neurocomputing 63: 271-292 (2005)
34EEMarc Strickert, Barbara Hammer, Sebastian Blohm: Unsupervised recursive sequence processing. Neurocomputing 63: 69-97 (2005)
33EEMarc Strickert, Barbara Hammer: Merge SOM for temporal data. Neurocomputing 64: 39-71 (2005)
32EEBhaskar DasGupta, Barbara Hammer: On approximate learning by multi-layered feedforward circuits. Theor. Comput. Sci. 348(1): 95-127 (2005)
2004
31EEBarbara Hammer, Brijnesh J. Jain: Neural methods for non-standard data. ESANN 2004: 281-292
30EEMarc Strickert, Barbara Hammer: Self-organizing context learning. ESANN 2004: 39-44
29EEBarbara Hammer, Marc Strickert, Thomas Villmann: Relevance LVQ versus SVM. ICAISC 2004: 592-597
28EEBarbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert: Recursive self-organizing network models. Neural Networks 17(8-9): 1061-1085 (2004)
27EEBarbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert: A general framework for unsupervised processing of structured data. Neurocomputing 57: 3-35 (2004)
2003
26EEKai Gersmann, Barbara Hammer: Improving iterative repair strategies for scheduling with the SVM. ESANN 2003: 235-240
25EEMarc Strickert, Barbara Hammer: Unsupervised Recursive Sequence Processing. ESANN 2003: 27-32
24EEBarbara Hammer, Thomas Villmann: Mathematical Aspects of Neural Networks. ESANN 2003: 59-72
23EEBarbara Hammer, Peter Tiño: Recurrent Neural Networks with Small Weights Implement Definite Memory Machines. Neural Computation 15(8): 1897-1929 (2003)
22EEPeter Tiño, Barbara Hammer: Architectural Bias in Recurrent Neural Networks: Fractal Analysis. Neural Computation 15(8): 1931-1957 (2003)
21EEThomas Villmann, Erzsébet Merényi, Barbara Hammer: Neural maps in remote sensing image analysis. Neural Networks 16(3-4): 389-403 (2003)
20 Barbara Hammer, Kai Gersmann: A Note on the Universal Approximation Capability of Support Vector Machines. Neural Processing Letters 17(1): 43-53 (2003)
2002
19 Barbara Hammer, Thomas Villmann: Batch-RLVQ. ESANN 2002: 295-300
18 Barbara Hammer, Jochen J. Steil: Perspectives on learning with recurrent neural networks. ESANN 2002: 357-368
17 Barbara Hammer, Alessio Micheli, Alessandro Sperduti: A general framework for unsupervised processing of structured data. ESANN 2002: 389-394
16EEPeter Tiño, Barbara Hammer: Architectural Bias in Recurrent Neural Networks - Fractal Analysis. ICANN 2002: 1359-1364
15EEBarbara Hammer, Marc Strickert, Thomas Villmann: Learning Vector Quantization for Multimodal Data. ICANN 2002: 370-376
14EEBarbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann: Rule Extraction from Self-Organizing Networks. ICANN 2002: 877-883
13EEBarbara Hammer, Thomas Villmann: Generalized relevance learning vector quantization. Neural Networks 15(8-9): 1059-1068 (2002)
2001
12EEThorsten Bojer, Barbara Hammer, Daniel Schunk, Katharina Tluk von Toschanowitz: Relevance determination in Learning Vector Quantization. ESANN 2001: 271-276
11EEBarbara Hammer, Thomas Villmann: Input pruning for neural gas architectures. ESANN 2001: 283-288
10EEMarc Strickert, Thorsten Bojer, Barbara Hammer: Generalized Relevance LVQ for Time Series. ICANN 2001: 677-683
9EEBarbara Hammer: On the Generalization Ability of Recurrent Networks. ICANN 2001: 731-736
8EEBarbara Hammer: Generalization Ability of Folding Networks. IEEE Trans. Knowl. Data Eng. 13(2): 196-206 (2001)
2000
7EEBhaskar DasGupta, Barbara Hammer: On Approximate Learning by Multi-layered Feedforward Circuits. ALT 2000: 264-278
6EEBarbara Hammer: Limitations of hybrid systems. ESANN 2000: 213-218
5EEBarbara Hammer: On the approximation capability of recurrent neural networks. Neurocomputing 31(1-4): 107-123 (2000)
1999
4EEBarbara Hammer: Approximation capabilities of folding networks. ESANN 1999: 33-38
1998
3EEBarbara Hammer: Training a sigmoidal network is difficult. ESANN 1998: 255-260
2 Barbara Hammer: On the Approximation Capability of Recurrent Neural Networks. NC 1998: 512-518
1997
1 Barbara Hammer: Generalization of Elman Networks. ICANN 1997: 409-414

Coauthor Index

1Cornelia Albani [54]
2Nikolai Alex [92] [98]
3Banchar Arnonkijpanich [90]
4Michael Biehl [45] [46] [49] [68] [69] [70] [79] [80] [82] [83] [95] [104]
5Sebastian Blohm [34]
6Mikael Bodén [64]
7Thorsten Bojer [10] [12]
8Cornelia Brüß [60]
9Kerstin Bunte [104]
10Marie Cottrell [36] [51] [53]
11Bhaskar DasGupta [7] [32]
12André M. Deelder [86]
13Thomas Elssner [58]
14Tom Fischer [53]
15Alexander Gammerman (Alex J. Gammerman) [100]
16Kai Gersmann [20] [26] [35]
17Tina Geweniger [50] [53] [60] [89] [91] [101]
18Anarta Ghosh [45] [46] [49] [80] [83]
19Alexander Hasenfuss (Alexander Hasenfuß) [51] [55] [61] [62] [67] [72] [74] [76] [77] [89] [90] [91] [94] [96] [98] [99] [103]
20Wieland Hermann [50] [54]
21Pascal Hitzler [81] [87] [88] [97]
22Brijnesh J. Jain [31]
23Samuel Kaski [57]
24Jens Keilwagen [95]
25Markus Kostrzewa [58] [85] [100]
26Chidchanok Lursinsap [90]
27Wolfgang Maass [87] [88] [97]
28Erzsébet Merényi [21] [73]
29Alessio Micheli [17] [27] [28] [40] [65] [71]
30Bassam Mokbel [103]
31Luc De Raedt [87] [88] [97]
32Andreas Rechtien [14] [44]
33Helge Ritter [42]
34Fabrice Rossi [96] [99]
35Craig Saunders [39]
36Frank-Michael Schleif [41] [48] [50] [52] [53] [54] [56] [58] [60] [61] [63] [66] [73] [74] [75] [76] [84] [85] [86] [89] [100]
37Petra Schneider [79] [95]
38Daniel Schunk [12]
39Udo Seiffert [47] [57] [59] [60] [76]
40Alessandro Sperduti [17] [27] [28] [39] [40] [65] [71]
41Nese Sreenivasulu [47] [93]
42Jochen J. Steil [18]
43Marc Strickert [10] [14] [15] [25] [27] [28] [29] [30] [33] [34] [37] [38] [44] [47] [76] [93] [95]
44Peter Tiño (Peter Tino) [16] [22] [23] [64]
45Rob A. E. M. Tollenaar [86]
46Katharina Tluk von Toschanowitz [12] [42]
47Michel Verleysen [69] [70] [82]
48Thomas Villmann [11] [13] [14] [15] [19] [21] [24] [29] [36] [37] [38] [41] [43] [44] [47] [48] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61] [62] [63] [66] [69] [70] [73] [74] [75] [76] [78] [82] [84] [85] [86] [89] [91] [93] [95] [100] [101] [102]
49Axel Walch [85]
50Martijn van der Werff [86]
51Winfriede Weschke [47]
52Aree Witoelar [68] [80] [83]
53D. Zühlke [101]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)