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Books and Theses
- 2004
[b1]Marc Strickert:
Self-organizing neural networks for sequence processing. University of Osnabrück, Germany, 2004, pp. 1-125
Journal Articles
- 2020
- [j20]Ali Fallah Tehrani
, Marc Strickert, Diane Ahrens:
A class of monotone kernelized classifiers on the basis of the Choquet integral. Expert Syst. J. Knowl. Eng. 37(3) (2020) - 2016
- [j19]Matthias Leinweber, Thomas Fober, Marc Strickert, Lars Baumgärtner, Gerhard Klebe, Bernd Freisleben, Eyke Hüllermeier:
CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites. IEEE Trans. Knowl. Data Eng. 28(6): 1423-1434 (2016) - 2014
- [j18]Sascha Henzgen, Marc Strickert, Eyke Hüllermeier:
Visualization of evolving fuzzy rule-based systems. Evol. Syst. 5(3): 175-191 (2014) - [j17]Marc Strickert, Kerstin Bunte, Frank-Michael Schleif, Eyke Hüllermeier:
Correlation-based embedding of pairwise score data. Neurocomputing 141: 97-109 (2014) - 2013
- [j16]Jan Grau, Jens Keilwagen, André Gohr, Ivan A. Paponov, Stefan Posch, Michael Seifert, Marc Strickert, Ivo Grosse:
Dispom: a Discriminative de-novo Motif Discovery Tool Based on the Jstacs Library. J. Bioinform. Comput. Biol. 11(1) (2013) - 2012
- [j15]Michael Seifert, André Gohr, Marc Strickert, Ivo Grosse:
Parsimonious Higher-Order Hidden Markov Models for Improved Array-CGH Analysis with Applications to Arabidopsis thaliana. PLoS Comput. Biol. 8(1) (2012) - 2011
- [j14]Michael Seifert, Marc Strickert, Alexander Schliep, Ivo Grosse:
Exploiting prior knowledge and gene distances in the analysis of tumor expression profiles with extended Hidden Markov Models. Bioinform. 27(12): 1645-1652 (2011) - [j13]Jens Keilwagen, Jan Grau, Ivan A. Paponov, Stefan Posch, Marc Strickert, Ivo Grosse:
De-Novo Discovery of Differentially Abundant Transcription Factor Binding Sites Including Their Positional Preference. PLoS Comput. Biol. 7(2) (2011) - 2010
- [j12]Jens Keilwagen, Jan Grau, Stefan Posch, Marc Strickert, Ivo Grosse:
Unifying generative and discriminative learning principles. BMC Bioinform. 11: 98 (2010) - [j11]Axel J. Soto, Marc Strickert, Gustavo E. Vazquez:
Adaptive matrix metrics for molecular descriptor assessment in QSPR classification. J. Cheminformatics 2(S-1): 47 (2010) - 2009
- [j10]Michael Seifert, Jens Keilwagen, Marc Strickert, Ivo Grosse:
Utilizing gene pair orientations for HMM-based analysis of promoter array ChIP-chip data. Bioinform. 25(16): 2118-2125 (2009) - 2008
- [j9]Marc Strickert, Frank-Michael Schleif, Udo Seiffert, Thomas Villmann:
Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data. Inteligencia Artif. 12(37): 37-44 (2008) - 2007
- [j8]Marc Strickert, Nese Sreenivasulu, Björn Usadel, Udo Seiffert:
Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue. BMC Bioinform. 8 (2007) - 2006
- [j7]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) - 2005
- [j6]Marc Strickert, Barbara Hammer, Sebastian Blohm:
Unsupervised recursive sequence processing. Neurocomputing 63: 69-97 (2005) - [j5]Marc Strickert, Barbara Hammer:
Merge SOM for temporal data. Neurocomputing 64: 39-71 (2005) - [j4]Barbara Hammer, Marc Strickert, Thomas Villmann:
Supervised Neural Gas with General Similarity Measure. Neural Process. Lett. 21(1): 21-44 (2005) - [j3]Barbara Hammer, Marc Strickert, Thomas Villmann:
On the Generalization Ability of GRLVQ Networks. Neural Process. Lett. 21(2): 109-120 (2005) - 2004
- [j2]Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert:
A general framework for unsupervised processing of structured data. Neurocomputing 57: 3-35 (2004) - [j1]Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert:
Recursive self-organizing network models. Neural Networks 17(8-9): 1061-1085 (2004)
Conference and Workshop Papers
- 2014
- [c37]Ali Fallah Tehrani, Marc Strickert, Eyke Hüllermeier:
The Choquet kernel for monotone data. ESANN 2014 - [c36]Amira Abdel-Aziz, Marc Strickert, Eyke Hüllermeier:
Learning Solution Similarity in Preference-Based CBR. ICCBR 2014: 17-31 - 2013
- [c35]Marc Strickert, Barbara Hammer, Thomas Villmann, Michael Biehl:
Regularization and improved interpretation of linear data mappings and adaptive distance measures. CIDM 2013: 10-17 - [c34]Sascha Henzgen, Marc Strickert, Eyke Hüllermeier:
Rule Chains for Visualizing Evolving Fuzzy Rule-Based Systems. CORES 2013: 279-288 - [c33]Marika Kästner, Marc Strickert, Thomas Villmann:
A sparse kernelized matrix learning vector quantization model for human activity recognition. ESANN 2013 - [c32]Marc Strickert, Kerstin Bunte:
Soft rank neighbor embeddings. ESANN 2013 - [c31]Amira Abdel-Aziz, Weiwei Cheng, Marc Strickert, Eyke Hüllermeier:
Preference-Based CBR: A Search-Based Problem Solving Framework. ICCBR 2013: 1-14 - [c30]Marika Kästner, Martin Riedel, Marc Strickert, Wieland Hermann, Thomas Villmann:
Border-Sensitive Learning in Kernelized Learning Vector Quantization. IWANN (1) 2013: 357-366 - [c29]Marc Strickert, Eyke Hüllermeier:
Neighbor Embedding by Soft Kendall Correlation. EuroVis (Short Papers) 2013 - 2012
- [c28]Marc Strickert, Michael Seifert:
Posterior regularization and attribute assessment of under-determined linear mappings. ESANN 2012 - [c27]Gabriele Peters, Kerstin Bunte, Marc Strickert, Michael Biehl, Thomas Villmann:
Visualization of processes in self-learning systems. PST 2012: 244-249 - 2011
- [c26]Axel J. Soto, Marc Strickert, Gustavo E. Vazquez, Evangelos E. Milios:
Subspace Mapping of Noisy Text Documents. Canadian AI 2011: 377-383 - [c25]Marc Strickert, Björn Labitzke, Volker Blanz:
Partial generalized correlation for hyperspectral data. CIDM 2011: 365-372 - [c24]Marc Strickert, Björn Labitzke, Andreas Kolb, Thomas Villmann:
Multispectral image characterization by partial generalized covariance. ESANN 2011 - 2010
- [c23]Marc Strickert, Axel J. Soto, Gustavo E. Vazquez:
Adaptive matrix distances aiming at optimum regression subspaces. ESANN 2010 - 2009
- [c22]Michael Seifert, Ali Banaei, Jens Keilwagen, Michael Florian Mette, Andreas Houben, François Roudier, Vincent Colot, Ivo Grosse, Marc Strickert:
Array-based Genome Comparison of Arabidopsis Ecotypes using Hidden Markov Models. BIOSIGNALS 2009: 3-11 - [c21]Marc Strickert, Frank-Michael Schleif, Thomas Villmann, Udo Seiffert:
Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data. Similarity-Based Clustering 2009: 70-91 - [c20]Thilo Fester, Falk Schreiber, Marc Strickert:
CUDA-based Multi-core Implementation of MDS-based Bioinformatics Algorithms. GCB 2009: 67-79 - [c19]Marc Strickert, Jens Keilwagen, Frank-Michael Schleif, Thomas Villmann, Michael Biehl:
Matrix Metric Adaptation Linear Discriminant Analysis of Biomedical Data. IWANN (1) 2009: 933-940 - 2008
- [c18]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 - [c17]Marc Strickert, Nese Sreenivasulu, Thomas Villmann, Barbara Hammer:
Robust Centroid-Based Clustering using Derivatives of Pearson Correlation. BIOSIGNALS (2) 2008: 197-203 - [c16]Marc Strickert, Frank-Michael Schleif, Thomas Villmann:
Metric adaptation for supervised attribute rating. ESANN 2008: 31-36 - [c15]Michael Seifert, Jens Keilwagen, Marc Strickert, Ivo Grosse:
Utilizing Promoter Pair Orientations for HMM-based Analysis of ChIP-chip Data. German Conference on Bioinformatics 2008: 116-127 - 2007
- [c14]Thomas Villmann, Marc Strickert, Cornelia Brüß, Frank-Michael Schleif, Udo Seiffert:
Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS. ESANN 2007: 103-108 - [c13]Barbara Hammer, Alexander Hasenfuss, Frank-Michael Schleif, Thomas Villmann, Marc Strickert, Udo Seiffert:
Intuitive Clustering of Biological Data. IJCNN 2007: 1877-1882 - 2006
- [c12]Marc Strickert, Nese Sreenivasulu, Silke Peterek, Winfriede Weschke, Hans-Peter Mock, Udo Seiffert:
Unsupervised Feature Selection for Biomarker Identification in Chromatography and Gene Expression Data. ANNPR 2006: 274-285 - [c11]Cornelia Brüß, Marc Strickert, Udo Seiffert:
Towards Automatic Segmentation of Serial High-Resolution Images. Bildverarbeitung für die Medizin 2006: 126-130 - [c10]Marc Strickert, Nese Sreenivasulu, Udo Seiffert:
Sanger-driven MDSLocalize - a comparative study for genomic data. ESANN 2006: 265-270 - 2005
- [c9]Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann:
Relevance learning for mental disease classification. ESANN 2005: 139-144 - [c8]Marc Strickert, Nese Sreenivasulu, Winfriede Weschke, Udo Seiffert, Thomas Villmann:
Generalized Relevance LVQ with Correlation Measures for Biological Data. ESANN 2005: 331-338 - [c7]Marc Strickert, Stefan Teichmann, Nese Sreenivasulu, Udo Seiffert:
High-Throughput Multi-dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data. ICANN (1) 2005: 625-633 - 2004
- [c6]Marc Strickert, Barbara Hammer:
Self-organizing context learning. ESANN 2004: 39-44 - [c5]Barbara Hammer, Marc Strickert, Thomas Villmann:
Relevance LVQ versus SVM. ICAISC 2004: 592-597 - 2003
- [c4]Marc Strickert, Barbara Hammer:
Unsupervised Recursive Sequence Processing. ESANN 2003: 27-32 - 2002
- [c3]Barbara Hammer, Marc Strickert, Thomas Villmann:
Learning Vector Quantization for Multimodal Data. ICANN 2002: 370-376 - [c2]Barbara Hammer, Andreas Rechtien, Marc Strickert, Thomas Villmann:
Rule Extraction from Self-Organizing Networks. ICANN 2002: 877-883 - 2001
- [c1]Marc Strickert, Thorsten Bojer, Barbara Hammer:
Generalized Relevance LVQ for Time Series. ICANN 2001: 677-683
Informal and Other Publications
- 2007
- [i1]Marc Strickert, Udo Seiffert:
Correlation-based Data Representation. Similarity-based Clustering and its Application to Medicine and Biology 2007
Coauthor Index
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