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 | 2011 | |
|---|---|---|
| i1 |      | Peter Geibel, Fritz Wysotzki: Risk-Sensitive Reinforcement Learning Applied to Control under Constraints. CoRR abs/1109.2147 (2011) |
| 2009 | ||
| j13 | | 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) |
| 2005 | ||
| j12 | | Brijnesh J. Jain, Fritz Wysotzki: Solving inexact graph isomorphism problems using neural networks. Neurocomputing 63: 45-67 (2005) |
| j11 | | Brijnesh J. Jain, Peter Geibel, Fritz Wysotzki: SVM learning with the Schur-Hadamard inner product for graphs. Neurocomputing 64: 93-105 (2005) |
| j10 | | Peter Geibel, Fritz Wysotzki: Risk-Sensitive Reinforcement Learning Applied to Control under Constraints. J. Artif. Intell. Res. (JAIR) 24: 81-108 (2005) |
| c41 |  | Christoph Schmoeger, Carsten Gips, Fritz Wysotzki: Spatial Inference with Constraints. LWA 2005: 228-233 |
| 2004 | ||
| j9 | | Peter Geibel, Fritz Wysotzki: Learning Perceptrons and Piecewise Linear Classifiers Sensitive to Example Dependent Costs. Appl. Intell. 21(1): 45-56 (2004) |
| j8 | | Peter Geibel, Ulf Brefeld, Fritz Wysotzki: Perceptron and SVM learning with generalized cost models. Intell. Data Anal. 8(5): 439-455 (2004) |
| j7 | | Stefan Bischoff, Fritz Wysotzki: Applied Connectionistic Methods to compare Segmented Images. KI 18(1): 11- (2004) |
| j6 | | Brijnesh J. Jain, Fritz Wysotzki: Central Clustering of Attributed Graphs. Machine Learning 56(1-3): 169-207 (2004) |
| j5 | | Brijnesh J. Jain, Fritz Wysotzki: Discrimination networks for maximum selection. Neural Networks 17(1): 143-154 (2004) |
| c40 | | Peter Geibel, Brijnesh J. Jain, Fritz Wysotzki: SVM learning with the SH inner product. ESANN 2004: 299-304 |
| c39 | | Brijnesh J. Jain, Fritz Wysotzki: The maximum weighted clique problem and Hopfield networks. ESANN 2004: 331-336 |
| c38 | | Brijnesh J. Jain, Peter Geibel, Fritz Wysotzki: Combining Recurrent Neural Networks and Support Vector Machines for Structural Pattern Recognition. KI 2004: 241-255 |
| c37 | | Carsten Gips, Fritz Wysotzki: Spatial Inference - Application of Machine Learning Algorithms. LWA 2004: 155-160 |
| c36 | | Brijnesh J. Jain, Fritz Wysotzki: Learning with Neural Networks in the Domain of Graphs. LWA 2004: 163-170 |
| c35 | | Brijnesh J. Jain, Fritz Wysotzki: Structural Perceptrons for Attributed Graphs. SSPR/SPR 2004: 85-94 |
| 2003 | ||
| j4 | | Peter Geibel, Kristina Schädler, Fritz Wysotzki: Connectionist construction of prototypes from decision trees for graph classification. Intell. Data Anal. 7(2): 125-140 (2003) |
| j3 | | Brijnesh J. Jain, Fritz Wysotzki: Automorphism Partitioning with Neural Networks. Neural Processing Letters 17(2): 205-215 (2003) |
| c34 | | Ulf Brefeld, Peter Geibel, Fritz Wysotzki: Support Vector Machines with Example Dependent Costs. ECML 2003: 23-34 |
| c33 | | Brijnesh J. Jain, Fritz Wysotzki: A Neural Graph Isomorphism Algorithm based on local Invariants. ESANN 2003: 79-84 |
| c32 | | Brijnesh J. Jain, Fritz Wysotzki: An Associative Memory for the Automorphism Group of Structures. ESANN 2003: 107-112 |
| c31 | | Brijnesh J. Jain, Fritz Wysotzki: A Competitive Winner-Takes-All Architecture for Classification and Pattern Recognition of Structures. GbRPR 2003: 259-270 |
| c30 | | Brijnesh J. Jain, Fritz Wysotzki: A Novel Neural Network Approach to Solve Exact and Inexact Graph Isomorphism Problems. ICANN 2003: 299-306 |
| c29 | | Peter Geibel, Fritz Wysotzki: Perceptron Based Learning with Example Dependent and Noisy Costs. ICML 2003: 218-225 |
| c28 | | Peter Geibel, Ulf Brefeld, Fritz Wysotzki: Learning Linear Classifiers Sensitive to Example Dependent and Noisy Costs. IDA 2003: 167-178 |
| c27 | | Carsten Gips, Fritz Wysotzki: Spatial Inference - Combining Learning and Constraint Solving. KI 2003: 282-296 |
| c26 | | Stefan Bischoff, D. Reuss, Fritz Wysotzki: Applied Connectionistic Methods in Computer Vision to Compare Segmented Images. KI 2003: 312-326 |
| c25 | | Brijnesh J. Jain, Fritz Wysotzki: A k-Winner-Takes-All Classifier for Structured Data. KI 2003: 342-354 |
| 2002 | ||
| c24 | | Emanuel Kitzelmann, Ute Schmid, Martin Mühlpfordt, Fritz Wysotzki: Inductive Synthesis of Functional Programs. AISC 2002: 26-37 |
| c23 | | Ute Schmid, Marina Müller, Fritz Wysotzki: Integrating Function Application in State-Based Planning. KI 2002: 144-162 |
| c22 | | Brijnesh J. Jain, Fritz Wysotzki: Fast Winner-Takes-All Networks for the Maximum Clique Problem. KI 2002: 163-173 |
| c21 | | Peter Geibel, Kristina Schädler, Fritz Wysotzki: Learning of Class Descriptions from Class Discriminations: A Hybrid Approach for Relational Objects. KI 2002: 186-204 |
| c20 | | Carsten Gips, Petra Hofstedt, Fritz Wysotzki: Spatial Inference - Learning vs. Constraint Solving. KI 2002: 299-316 |
| 2001 | ||
| c19 | | |
| c18 | | Brijnesh J. Jain, Fritz Wysotzki: Efficient Pattern Discrimination with Inhibitory WTA Nets. ICANN 2001: 827-834 |
| 2000 | ||
| j2 | | Peter Geibel, Fritz Wysotzki: Graphbasierte Lernverfahren für relationale Daten. Inform., Forsch. Entwickl. 15(1): 1-15 (2000) |
| c17 | | Ute Schmid, Fritz Wysotzki: Applying Inductive Program Synthesis to Macro Learning. AIPS 2000: 371-378 |
| c16 | | Sylvia Wiebrock, Lars Wittenburg, Ute Schmid, Fritz Wysotzki: Inference and Visualization of Spatial Relations. Spatial Cognition 2000: 212-224 |
| 1999 | ||
| j1 | | Kristina Schädler, Fritz Wysotzki: Comparing Structures Using a Hopfield-Style Neural Network. Appl. Intell. 11(1): 15-30 (1999) |
| 1998 | ||
| c15 | | |
| c14 | | Kristina Schädler, Fritz Wysotzki: Application of a neural net in classification and knowledge discovery. ESANN 1998: 117-122 |
| c13 | | Berry Claus, Klaus Eyferth, Carsten Gips, Robin Hörnig, Ute Schmid, Sylvia Wiebrock, Fritz Wysotzki: Reference Frames for Spatial Inference in Text Understanding. Spatial Cognition 1998: 241-266 |
| 1997 | ||
| c12 | | Kristina Schädler, Fritz Wysotzki: A Connectionist Approach to the Distance-Based Analysis of Relational Data. IDA 1997: 137-148 |
| c11 | | Peter Geibel, Fritz Wysotzki: A Logical Framework for Graph Theoretical Decision Tree Learning. ILP 1997: 173-180 |
| c10 | | Kristina Schädler, Fritz Wysotzki: A Connectionist Approach to Structural Simiarity Determination as a Basis of Clustering, Classification and Feature Detection. PKDD 1997: 254-264 |
| 1996 | ||
| c9 | | |
| c8 | | |
| c7 | | Tobias Scheffer, Ralf Herbrich, Fritz Wysotzki: Efficient Theta-Subsumption Based on Graph Algorithms. Inductive Logic Programming Workshop 1996: 212-228 |
| 1995 | ||
| c6 | | Wolfgang Müller, Fritz Wysotzki: Automatic Synthesis of Control Programs by Combination of Learning and Problem Solving Methods (Extended Abstract). ECML 1995: 323-326 |
| c5 | | Christel Wisotzki, Fritz Wysotzki: Prototype, Nearest Neighbor and Hybrid Algorithms for Time Series Classification (Extended Abstract). ECML 1995: 364-367 |
| 1994 | ||
| c4 | | |
| 1986 | ||
| c3 | | |
| 1983 | ||
| c2 | | Fritz Wysotzki: Representation and Induction of Infinite Concepts and Recursive Action Sequences. IJCAI 1983: 409-414 |
| 1981 | ||
| c1 | | Fritz Wysotzki, Werner Kolbe, Joachim Selbig: Concept Learning by Structured Examples - An Algebraic Approach. IJCAI 1981: 153-158 |
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