Barbara Hammer

	2009
106		Kerstin Bunte, Barbara Hammer, Michael Biehl: Nonlinear Dimension Reduction and Visualization of Labeled Data. CAIP 2009: 1162-1170
105		Bassam Mokbel, Alexander Hasenfuss, Barbara Hammer: Graph-Based Representation of Symbolic Musical Data. GbRPR 2009: 42-51
104		Thomas Villmann, Barbara Hammer: Functional Principal Component Learning Using Oja's Method and Sobolev Norms. WSOM 2009: 325-333
103		Tina Geweniger, D. Zühlke, Barbara Hammer, Thomas Villmann: Fuzzy Variant of Affinity Propagation in Comparison to Median Fuzzy c-Means. WSOM 2009: 72-79
102		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)
101		Barbara Hammer, Alexander Hasenfuß, Fabrice Rossi: Median topographic maps for biomedical data sets CoRR abs/0909.0638: (2009)
100		Petra Schneider, Michael Biehl, Barbara Hammer: Distance Learning in Discriminative Vector Quantization. Neural Computation 21(10): 2942-2969 (2009)
99		Nikolai Alex, Alexander Hasenfuss, Barbara Hammer: Patch clustering for massive data sets. Neurocomputing 72(7-9): 1455-1469 (2009)
	2008
98		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
97		Alexander Hasenfuss, Barbara Hammer, Fabrice Rossi: Patch Relational Neural Gas - Clustering of Huge Dissimilarity Datasets. ANNPR 2008: 1-12
96		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
95		Alexander Hasenfuss, Barbara Hammer: Single Pass Clustering and Classification of Large Dissimilarity Datasets. Artificial Intelligence and Pattern Recognition 2008: 219-223
94		Marc Strickert, Nese Sreenivasulu, Thomas Villmann, Barbara Hammer: Robust Centroid-Based Clustering using Derivatives of Pearson Correlation. BIOSIGNALS (2) 2008: 197-203
93		Nikolai Alex, Barbara Hammer: Parallelizing single patch pass clustering. ESANN 2008: 227-232
92		Alexander Hasenfuss, Barbara Hammer, Tina Geweniger, Thomas Villmann: Magnification Control in Relational Neural Gas. ESANN 2008: 325-330
91		Banchar Arnonkijpanich, Barbara Hammer, Alexander Hasenfuss, Chidchanok Lursinsap: Matrix Learning for Topographic Neural Maps. ICANN (1) 2008: 572-582
90		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
89		Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: 08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008
88		Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: 08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008
87		Tim Winkler, Jens Drieseberg, Kai Hormann, Alexander Hasenfuss, Barbara Hammer: Thinning Mesh Animations. VMV 2008: 149-158
86		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
85		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)
84		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Prototype based fuzzy classification in clinical proteomics. Int. J. Approx. Reasoning 47(1): 4-16 (2008)
83		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)
	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
80		Aree Witoelar, Michael Biehl, Anarta Ghosh, Barbara Hammer: On the dynamics of Vector Quantization and Neural Gas. ESANN 2007: 127-132
79		Petra Schneider, Michael Biehl, Barbara Hammer: Relevance matrices in LVQ. ESANN 2007: 37-42
78		Barbara Hammer, Thomas Villmann: How to process uncertainty in machine learning?. ESANN 2007: 79-90
77		Alexander Hasenfuss, Barbara Hammer: Relational Topographic Maps. IDA 2007: 93-105
76		Barbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann, Marc Strickert, Udo Seiffert: Intuitive Clustering of Biological Data. IJCNN 2007: 1877-1882
75		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
74		Alexander Hasenfuss, Barbara Hammer, Frank-Michael Schleif, Thomas Villmann: Neural Gas Clustering for Dissimilarity Data with Continuous Prototypes. IWANN 2007: 539-546
73		Thomas Villmann, Frank-Michael Schleif, Erzsébet Merényi, Barbara Hammer: Fuzzy Labeled Self-Organizing Map for Classification of Spectra. IWANN 2007: 556-563
72		Barbara Hammer, Alexander Hasenfuss: Relational Neural Gas. KI 2007: 190-204
71		Barbara Hammer, Alessio Micheli, Alessandro Sperduti: A general framework for unsupervised preocessing of structured data. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007
70		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
69		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
68		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
67		Barbara Hammer, Alexander Hasenfuss: Relational Clustering. Similarity-based Clustering and its Application to Medicine and Biology 2007
66		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps. WILF 2007: 563-570
65		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
64		Peter Tino, Barbara Hammer, Mikael Bodén: Markovian Bias of Neural-based Architectures With Feedback Connections. Perspectives of Neural-Symbolic Integration 2007: 95-133
63		Frank-Michael Schleif, Barbara Hammer, Thomas Villmann: Margin-based active learning for LVQ networks. Neurocomputing 70(7-9): 1215-1224 (2007)
62		Barbara Hammer, Alexander Hasenfuss, Thomas Villmann: Magnification control for batch neural gas. Neurocomputing 70(7-9): 1225-1234 (2007)
	2006
61		Barbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann: Supervised Batch Neural Gas. ANNPR 2006: 33-45
60		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
59		Thomas Villmann, Barbara Hammer, Udo Seiffert: Perspectives of Self-adapted Self-organizing Clustering in Organic Computing. BioADIT 2006: 141-159
58		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
57		Udo Seiffert, Barbara Hammer, Samuel Kaski, Thomas Villmann: Neural networks and machine learning in bioinformatics - theory and applications. ESANN 2006: 521-532
56		Frank-Michael Schleif, Barbara Hammer, Thomas Villmann: Margin based Active Learning for LVQ Networks. ESANN 2006: 539-544
55		Barbara Hammer, Alexander Hasenfuss, Thomas Villmann: Magnification control for batch neural gas. ESANN 2006: 7-12
54		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
53		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
52		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)
51		Marie Cottrell, Barbara Hammer, Alexander Hasenfuss, Thomas Villmann: Batch and median neural gas. Neural Networks 19(6-7): 762-771 (2006)
50		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)
49		Anarta Ghosh, Michael Biehl, Barbara Hammer: Performance analysis of LVQ algorithms: A statistical physics approach. Neural Networks 19(6-7): 817-829 (2006)
48		Thomas Villmann, Frank-Michael Schleif, Barbara Hammer: Prototype-based fuzzy classification with local relevance for proteomics. Neurocomputing 69(16-18): 2425-2428 (2006)
47		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)
46		Michael Biehl, Anarta Ghosh, Barbara Hammer: Learning vector quantization: The dynamics of winner-takes-all algorithms. Neurocomputing 69(7-9): 660-670 (2006)
	2005
45		Michael Biehl, Anarta Ghosh, Barbara Hammer: The dynamics of Learning Vector Quantization. ESANN 2005: 13-18
44		Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann: Relevance learning for mental disease classification. ESANN 2005: 139-144
43		Barbara Hammer, Thomas Villmann: Classification using non-standard metrics. ESANN 2005: 303-316
42		Katharina Tluk von Toschanowitz, Barbara Hammer, Helge Ritter: Relevance determination in reinforcement learning. ESANN 2005: 369-374
41		Frank-Michael Schleif, Thomas Villmann, Barbara Hammer: Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data. WILF 2005: 290-296
40		Barbara Hammer, Alessio Micheli, Alessandro Sperduti: Universal Approximation Capability of Cascade Correlation for Structures. Neural Computation 17(5): 1109-1159 (2005)
39		Barbara Hammer, Craig Saunders, Alessandro Sperduti: Special issue on neural networks and kernel methods for structured domains. Neural Networks 18(8): 1015-1018 (2005)
38		Barbara Hammer, Marc Strickert, Thomas Villmann: Supervised Neural Gas with General Similarity Measure. Neural Processing Letters 21(1): 21-44 (2005)
37		Barbara Hammer, Marc Strickert, Thomas Villmann: On the Generalization Ability of GRLVQ Networks. Neural Processing Letters 21(2): 109-120 (2005)
36		Marie Cottrell, Barbara Hammer, Thomas Villmann: New Aspects in Neurocomputing. Neurocomputing 63: 1-3 (2005)
35		Kai Gersmann, Barbara Hammer: Improving iterative repair strategies for scheduling with the SVM. Neurocomputing 63: 271-292 (2005)
34		Marc Strickert, Barbara Hammer, Sebastian Blohm: Unsupervised recursive sequence processing. Neurocomputing 63: 69-97 (2005)
33		Marc Strickert, Barbara Hammer: Merge SOM for temporal data. Neurocomputing 64: 39-71 (2005)
32		Bhaskar DasGupta, Barbara Hammer: On approximate learning by multi-layered feedforward circuits. Theor. Comput. Sci. 348(1): 95-127 (2005)
	2004
31		Barbara Hammer, Brijnesh J. Jain: Neural methods for non-standard data. ESANN 2004: 281-292
30		Marc Strickert, Barbara Hammer: Self-organizing context learning. ESANN 2004: 39-44
29		Barbara Hammer, Marc Strickert, Thomas Villmann: Relevance LVQ versus SVM. ICAISC 2004: 592-597
28		Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert: Recursive self-organizing network models. Neural Networks 17(8-9): 1061-1085 (2004)
27		Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert: A general framework for unsupervised processing of structured data. Neurocomputing 57: 3-35 (2004)
	2003
26		Kai Gersmann, Barbara Hammer: Improving iterative repair strategies for scheduling with the SVM. ESANN 2003: 235-240
25		Marc Strickert, Barbara Hammer: Unsupervised Recursive Sequence Processing. ESANN 2003: 27-32
24		Barbara Hammer, Thomas Villmann: Mathematical Aspects of Neural Networks. ESANN 2003: 59-72
23		Barbara Hammer, Peter Tiño: Recurrent Neural Networks with Small Weights Implement Definite Memory Machines. Neural Computation 15(8): 1897-1929 (2003)
22		Peter Tiño, Barbara Hammer: Architectural Bias in Recurrent Neural Networks: Fractal Analysis. Neural Computation 15(8): 1931-1957 (2003)
21		Thomas 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
16		Peter Tiño, Barbara Hammer: Architectural Bias in Recurrent Neural Networks - Fractal Analysis. ICANN 2002: 1359-1364
15		Barbara Hammer, Marc Strickert, Thomas Villmann: Learning Vector Quantization for Multimodal Data. ICANN 2002: 370-376
14		Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann: Rule Extraction from Self-Organizing Networks. ICANN 2002: 877-883
13		Barbara Hammer, Thomas Villmann: Generalized relevance learning vector quantization. Neural Networks 15(8-9): 1059-1068 (2002)
	2001
12		Thorsten Bojer, Barbara Hammer, Daniel Schunk, Katharina Tluk von Toschanowitz: Relevance determination in Learning Vector Quantization. ESANN 2001: 271-276
11		Barbara Hammer, Thomas Villmann: Input pruning for neural gas architectures. ESANN 2001: 283-288
10		Marc Strickert, Thorsten Bojer, Barbara Hammer: Generalized Relevance LVQ for Time Series. ICANN 2001: 677-683
9		Barbara Hammer: On the Generalization Ability of Recurrent Networks. ICANN 2001: 731-736
8		Barbara Hammer: Generalization Ability of Folding Networks. IEEE Trans. Knowl. Data Eng. 13(2): 196-206 (2001)
	2000
7		Bhaskar DasGupta, Barbara Hammer: On Approximate Learning by Multi-layered Feedforward Circuits. ALT 2000: 264-278
6		Barbara Hammer: Limitations of hybrid systems. ESANN 2000: 213-218
5		Barbara Hammer: On the approximation capability of recurrent neural networks. Neurocomputing 31(1-4): 107-123 (2000)
	1999
4		Barbara Hammer: Approximation capabilities of folding networks. ESANN 1999: 33-38
	1998
3		Barbara 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

1	Cornelia Albani	[54]
2	Nikolai Alex	[93] [99]
3	Banchar Arnonkijpanich	[91]
4	Michael Biehl	[45] [46] [49] [68] [69] [70] [79] [80] [82] [83] [96] [100] [106]
5	Sebastian Blohm	[34]
6	Mikael Bodén	[64]
7	Thorsten Bojer	[10] [12]
8	Cornelia Brüß	[60]
9	Kerstin Bunte	[106]
10	Marie Cottrell	[36] [51] [53]
11	Bhaskar DasGupta	[7] [32]
12	André M. Deelder	[86]
13	Jens Drieseberg	[87]
14	Thomas Elssner	[58]
15	Tom Fischer	[53]
16	Alexander Gammerman (Alex J. Gammerman)	[102]
17	Kai Gersmann	[20] [26] [35]
18	Tina Geweniger	[50] [53] [60] [90] [92] [103]
19	Anarta Ghosh	[45] [46] [49] [80] [83]
20	Alexander Hasenfuss (Alexander Hasenfuß)	[51] [55] [61] [62] [67] [72] [74] [76] [77] [87] [90] [91] [92] [95] [97] [99] [101] [105]
21	Wieland Hermann	[50] [54]
22	Pascal Hitzler	[81] [88] [89] [98]
23	Kai Hormann	[87]
24	Brijnesh J. Jain	[31]
25	Samuel Kaski	[57]
26	Jens Keilwagen	[96]
27	Markus Kostrzewa	[58] [85] [102]
28	Chidchanok Lursinsap	[91]
29	Wolfgang Maass	[88] [89] [98]
30	Erzsébet Merényi	[21] [73]
31	Alessio Micheli	[17] [27] [28] [40] [65] [71]
32	Bassam Mokbel	[105]
33	Luc De Raedt	[88] [89] [98]
34	Andreas Rechtien	[14] [44]
35	Helge Ritter	[42]
36	Fabrice Rossi	[97] [101]
37	Craig Saunders	[39]
38	Frank-Michael Schleif	[41] [48] [50] [52] [53] [54] [56] [58] [60] [61] [63] [66] [73] [74] [75] [76] [84] [85] [86] [90] [102]
39	Petra Schneider	[79] [96] [100]
40	Daniel Schunk	[12]
41	Udo Seiffert	[47] [57] [59] [60] [76]
42	Alessandro Sperduti	[17] [27] [28] [39] [40] [65] [71]
43	Nese Sreenivasulu	[47] [94]
44	Jochen J. Steil	[18]
45	Marc Strickert	[10] [14] [15] [25] [27] [28] [29] [30] [33] [34] [37] [38] [44] [47] [76] [94] [96]
46	Peter Tiño (Peter Tino)	[16] [22] [23] [64]
47	Rob A. E. M. Tollenaar	[86]
48	Katharina Tluk von Toschanowitz	[12] [42]
49	Michel Verleysen	[69] [70] [82]
50	Thomas 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] [90] [92] [94] [96] [102] [103] [104]
51	Axel Walch	[85]
52	Martijn van der Werff	[86]
53	Winfriede Weschke	[47]
54	Tim Winkler	[87]
55	Aree Witoelar	[68] [80] [83]
56	D. Zühlke	[103]

Colors in the list of coauthors