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Peter Geibel
2010 – today
- 2013
[c27]Peter Geibel, Martin Trautwein, Hebun Erdur, Lothar Zimmermann, Stefan Krüger, Josef Schepers, Kati Jegzentis, Frank Müller, Christian Hans Nolte, Anne Becker, Markus Frick, Jochen Setz, Jan Friedrich Scheitz, Serdar Tütüncü, Tatiana Usnich, Alfred Holzgreve, Thorsten Schaaf, Thomas Tolxdorff: Ontology-Based Semantic Annotation of Documents in the Context of Patient Identification for Clinical Trials. OTM Conferences 2013: 719-736- 2012
- [p2]Peter Geibel, Alexander Mehler, Kai-Uwe Kühnberger: Learning Methods for Graph Models of Document Structure. Modeling, Learning, and Processing of Text Technological Data Structures 2012: 267-298
- 2011
- [c26]Konstantin Todorov, Peter Geibel, Céline Hudelot: A Framework for a Fuzzy Matching between Multiple Domain Ontologies. KES (1) 2011: 538-547
- [c25]Konstantin Todorov, Peter Geibel, Céline Hudelot: Building A Fuzzy Knowledge Body for Integrating Domain Ontologies. URSW 2011: 3-14
- [i1]Peter Geibel, Fritz Wysotzki: Risk-Sensitive Reinforcement Learning Applied to Control under Constraints. CoRR abs/1109.2147 (2011)
- 2010
- [c24]Konstantin Todorov, Peter Geibel, Kai-Uwe Kühnberger: Extensional Ontology Matching with Variable Selection for Support Vector Machines. CISIS 2010: 962-967
- [c23]Konstantin Todorov, Peter Geibel, Kai-Uwe Kühnberger: Mining Concept Similarities for Heterogeneous Ontologies. ICDM 2010: 86-100
2000 – 2009
- 2009
- [j8]Fritz Wysotzki, Peter Geibel: A New Information Measure Based on Example-Dependent Misclassification Costs and Its Application in Decision Tree Learning. Adv. Artificial Intellegence 2009 (2009)
- [c22]Konstantin Todorov, Peter Geibel: Variable Selection as an Instance-Based Ontology Mapping Strategy. SWWS 2009: 3-9
- 2008
- [c21]Kai-Uwe Kühnberger, Peter Geibel, Helmar Gust, Ulf Krumnack, Ekaterina Ovchinnikova, Angela Schwering, Tonio Wandmacher: Learning from Inconsistencies in an Integrated Cognitive Architecture. AGI 2008: 212-223
- [c20]Kai-Uwe Kühnberger, Helmar Gust, Peter Geibel: Perspectives of Neuro--Symbolic Integration -- Extended Abstract --. Recurrent Neural Networks 2008
- [c19]Konstantin Todorov, Peter Geibel: Ontology Mapping via Structural and Instance-based Similarity Measures. OM 2008
- 2007
- [j7]Alexander Mehler, Peter Geibel, Olga Pustylnikov: Structural Classifiers of Text Types: Towards a Novel Model of Text Representation. LDV Forum 22(2): 51-66 (2007)
- [c18]Peter Geibel, Ulf Krumnack, Olga Pustylnikov, Alexander Mehler, Helmar Gust, Kai-Uwe Kühnberger: Structure-Sensitive Learning of Text Types. Australian Conference on Artificial Intelligence 2007: 642-646
- [c17]Helmar Gust, Kai-Uwe Kühnberger, Peter Geibel: Learning and Memorizing Models of Logical Theories in a Hybrid Learning Device. ICONIP (2) 2007: 738-748
- [c16]Peter Geibel, Olga Pustylnikov, Alexander Mehler, Helmar Gust, Kai-Uwe Kühnberger: Classification of Documents Based on the Structure of Their DOM Trees. ICONIP (2) 2007: 779-788
- [c15]Kai-Uwe Kühnberger, Tonio Wandmacher, Angela Schwering, Ekaterina Ovchinnikova, Ulf Krumnack, Helmar Gust, Peter Geibel: Modeling Human-Level Intelligence by Integrated Cognition in a Hybrid Architecture. FAInt 2007
- [c14]Kai-Uwe Kühnberger, Tonio Wandmacher, Angela Schwering, Ekaterina Ovchinnikova, Ulf Krumnack, Helmar Gust, Peter Geibel: I-Cog: A Computational Framework for Integrated Cognition of Higher Cognitive Abilities. MICAI 2007: 203-214
- [c13]Florian Halbritter, Peter Geibel: Learning Models of Relational MDPs Using Graph Kernels. MICAI 2007: 409-419
- [c12]Peter Geibel, Helmar Gust, Kai-Uwe Kühnberger: Variants of Tree Kernels for XML Documents. MICAI 2007: 850-860
- [p1]Helmar Gust, Kai-Uwe Kühnberger, Peter Geibel: Learning Models of Predicate Logical Theories with Neural Networks Based on Topos Theory. Perspectives of Neural-Symbolic Integration 2007: 233-264
- 2006
- [c11]
- 2005
- [j6]Brijnesh J. Jain, Peter Geibel, Fritz Wysotzki: SVM learning with the Schur-Hadamard inner product for graphs. Neurocomputing 64: 93-105 (2005)
- [j5]Peter Geibel, Fritz Wysotzki: Risk-Sensitive Reinforcement Learning Applied to Control under Constraints. J. Artif. Intell. Res. (JAIR) 24: 81-108 (2005)
- 2004
- [j4]Peter Geibel, Fritz Wysotzki: Learning Perceptrons and Piecewise Linear Classifiers Sensitive to Example Dependent Costs. Appl. Intell. 21(1): 45-56 (2004)
- [j3]Peter Geibel, Ulf Brefeld, Fritz Wysotzki: Perceptron and SVM learning with generalized cost models. Intell. Data Anal. 8(5): 439-455 (2004)
- [c10]Peter Geibel, Brijnesh J. Jain, Fritz Wysotzki: SVM learning with the SH inner product. ESANN 2004: 299-304
- [c9]Brijnesh J. Jain, Peter Geibel, Fritz Wysotzki: Combining Recurrent Neural Networks and Support Vector Machines for Structural Pattern Recognition. KI 2004: 241-255
- 2003
- [j2]Peter Geibel, Kristina Schädler, Fritz Wysotzki: Connectionist construction of prototypes from decision trees for graph classification. Intell. Data Anal. 7(2): 125-140 (2003)
- [c8]Ulf Brefeld, Peter Geibel, Fritz Wysotzki: Support Vector Machines with Example Dependent Costs. ECML 2003: 23-34
- [c7]Peter Geibel, Fritz Wysotzki: Perceptron Based Learning with Example Dependent and Noisy Costs. ICML 2003: 218-225
- [c6]Peter Geibel, Ulf Brefeld, Fritz Wysotzki: Learning Linear Classifiers Sensitive to Example Dependent and Noisy Costs. IDA 2003: 167-178
- 2002
- [c5]Peter Geibel, Kristina Schädler, Fritz Wysotzki: Learning of Class Descriptions from Class Discriminations: A Hybrid Approach for Relational Objects. KI 2002: 186-204
- 2001
- [c4]
- 2000
- [j1]Peter Geibel, Fritz Wysotzki: Graphbasierte Lernverfahren für relationale Daten. Inform., Forsch. Entwickl. 15(1): 1-15 (2000)
1990 – 1999
- 1999
- [b1]Peter Geibel: Induktive Konstruktion von merkmalsbasierten und logischen Klassifikatoren für relationale Strukturen. DISKI 212, Infix 1999, ISBN 978-3-89601-212-8, pp. I-XIII, 1-187
- 1997
- [c3]Peter Geibel, Fritz Wysotzki: A Logical Framework for Graph Theoretical Decision Tree Learning. ILP 1997: 173-180
- 1996
- [c2]
- [c1]
Coauthor Index
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last updated on 2013-10-02 11:02 CEST by the dblp team