Concept Learning by Structured Examples - An Algebraic Approach. - Fritz Wysotzki; Werner Kolbe; Joachim Selbig (IJCAI, 1981)

Representation and Induction of Infinite Concepts and Recursive Action Sequences. - Fritz Wysotzki (IJCAI, 1983)

Program Synthesis by Hierarchical Planning. - Fritz Wysotzki (AIMSA, 1986)

The Piecewise Linear Classifier DIPOL92. - Barbara Schulmeister; Fritz Wysotzki (ECML, 1994)

Automatic construction of decision trees for classification. - Wolfgang Müller 012; Fritz Wysotzki (Ann. Oper. Res., 1994)

Automatic Synthesis of Control Programs by Combination of Learning and Problem Solving Methods (Extended Abstract). - Wolfgang Müller 012; Fritz Wysotzki (ECML, 1995)

Prototype, Nearest Neighbor and Hybrid Algorithms for Time Series Classification (Extended Abstract). - Christel Wisotzki; Fritz Wysotzki (ECML, 1995)

Relational Learning with Decision Trees. - Peter Geibel; Fritz Wysotzki (ECAI, 1996)

Learning Relational Concepts with Decision Trees. - Peter Geibel; Fritz Wysotzki (ICML, 1996)

Efficient Theta-Subsumption Based on Graph Algorithms. - Tobias Scheffer; Ralf Herbrich; Fritz Wysotzki (Inductive Logic Programming Workshop, 1996)

Aerial Robotics in Computer Science Education. - Marion Finke; Günter Hommel; Tobias Scheffer; Fritz Wysotzki (Comput. Sci. Educ., 1996)

A Connectionist Approach to the Distance-Based Analysis of Relational Data. - Kristina Schädler; Fritz Wysotzki (IDA, 1997)

A Logical Framework for Graph Theoretical Decision Tree Learning. - Peter Geibel; Fritz Wysotzki (ILP, 1997)

A Connectionist Approach to Structural Simiarity Determination as a Basis of Clustering, Classification and Feature Detection. - Kristina Schädler; Fritz Wysotzki (PKDD, 1997)

Induction of Recursive Program Schemes. - Ute Schmid; Fritz Wysotzki (ECML, 1998)

Application of a neural net in classification and knowledge discovery. - Kristina Schädler; Fritz Wysotzki (ESANN, 1998)

Reference Frames for Spatial Inference in Text Understanding. - Berry Claus; Klaus Eyferth; Carsten Gips; Robin Hörnig; Ute Schmid; Sylvia Wiebrock; Fritz Wysotzki (Spatial Cognition, 1998)

Comparing Structures Using a Hopfield-Style Neural Network. - Kristina Schädler; Fritz Wysotzki (Appl. Intell., 1999)

Applying Inductive Program Synthesis to Macro Learning. - Ute Schmid; Fritz Wysotzki (AIPS, 2000)

Inference and Visualization of Spatial Relations. - Sylvia Wiebrock; Lars Wittenburg; Ute Schmid; Fritz Wysotzki (Spatial Cognition, 2000)

Graphbasierte Lernverfahren für relationale Daten. - Peter Geibel; Fritz Wysotzki (Inform. Forsch. Entwickl., 2000)

On the short-term-memory of WTA nets. - Brijnesh J. Jain; Fritz Wysotzki (ESANN, 2001)

Efficient Pattern Discrimination with Inhibitory WTA Nets. - Brijnesh J. Jain; Fritz Wysotzki (ICANN, 2001)

Inductive Synthesis of Functional Programs. - Emanuel Kitzelmann; Ute Schmid; Martin Mühlpfordt; Fritz Wysotzki (AISC, 2002)

Learning of Class Descriptions from Class Discriminations: A Hybrid Approach for Relational Objects. - Peter Geibel; Kristina Schädler; Fritz Wysotzki (KI, 2002)

Spatial Inference - Learning vs. Constraint Solving. - Carsten Gips; Petra Hofstedt; Fritz Wysotzki (KI, 2002)

Fast Winner-Takes-All Networks for the Maximum Clique Problem. - Brijnesh J. Jain; Fritz Wysotzki (KI, 2002)

Integrating Function Application in State-Based Planning. - Ute Schmid; Marina Müller; Fritz Wysotzki (KI, 2002)

Support Vector Machines with Example Dependent Costs. - Ulf Brefeld; Peter Geibel; Fritz Wysotzki (ECML, 2003)

A Neural Graph Isomorphism Algorithm based on local Invariants. - Brijnesh J. Jain; Fritz Wysotzki (ESANN, 2003)

An Associative Memory for the Automorphism Group of Structures. - Brijnesh J. Jain; Fritz Wysotzki (ESANN, 2003)

A Competitive Winner-Takes-All Architecture for Classification and Pattern Recognition of Structures. - Brijnesh J. Jain; Fritz Wysotzki (GbRPR, 2003)

A Novel Neural Network Approach to Solve Exact and Inexact Graph Isomorphism Problems. - Brijnesh J. Jain; Fritz Wysotzki (ICANN, 2003)

Perceptron Based Learning with Example Dependent and Noisy Costs. - Peter Geibel; Fritz Wysotzki (ICML, 2003)

Learning Linear Classifiers Sensitive to Example Dependent and Noisy Costs. - Peter Geibel; Ulf Brefeld; Fritz Wysotzki (IDA, 2003)

Perceptron learning in the domain of graphs. - Brijnesh J. Jain; Fritz Wysotzki (IJCNN, 2003)

Applied Connectionistic Methods in Computer Vision to Compare Segmented Images. - Stefan Bischoff; D. Reuss; Fritz Wysotzki (KI, 2003)

Spatial Inference - Combining Learning and Constraint Solving. - Carsten Gips; Fritz Wysotzki (KI, 2003)

A k-Winner-Takes-All Classifier for Structured Data. - Brijnesh J. Jain; Fritz Wysotzki (KI, 2003)

Connectionist construction of prototypes from decision trees for graph classification. - Peter Geibel; Kristina Schädler; Fritz Wysotzki (Intell. Data Anal., 2003)

Automorphism Partitioning with Neural Networks. - Brijnesh J. Jain; Fritz Wysotzki (Neural Process. Lett., 2003)

SVM learning with the SH inner product. - Peter Geibel; Brijnesh J. Jain; Fritz Wysotzki (ESANN, 2004)

The maximum weighted clique problem and Hopfield networks. - Brijnesh J. Jain; Fritz Wysotzki (ESANN, 2004)

Multi-layer perceptron learning in the domain of attributed graphs. - Brijnesh J. Jain; Fritz Wysotzki (IJCNN, 2004)

Combining Recurrent Neural Networks and Support Vector Machines for Structural Pattern Recognition. - Brijnesh J. Jain; Peter Geibel; Fritz Wysotzki (KI, 2004)

Spatial Inference - Application of Machine Learning Algorithms. - Carsten Gips; Fritz Wysotzki (LWA, 2004)

Learning with Neural Networks in the Domain of Graphs. - Brijnesh J. Jain; Fritz Wysotzki (LWA, 2004)

Structural Perceptrons for Attributed Graphs. - Brijnesh J. Jain; Fritz Wysotzki (SSPR/SPR, 2004)

Learning Perceptrons and Piecewise Linear Classifiers Sensitive to Example Dependent Costs. - Peter Geibel; Fritz Wysotzki (Appl. Intell., 2004)

Perceptron and SVM learning with generalized cost models. - Peter Geibel; Ulf Brefeld; Fritz Wysotzki (Intell. Data Anal., 2004)

Applied Connectionistic Methods to compare Segmented Images. - Stefan Bischoff; Fritz Wysotzki (Künstliche Intell., 2004)

Central Clustering of Attributed Graphs. - Brijnesh J. Jain; Fritz Wysotzki (Mach. Learn., 2004)

Discrimination networks for maximum selection. - Brijnesh J. Jain; Fritz Wysotzki (Neural Networks, 2004)

Development of Inductive Synthesis of Functional Programs. - Fritz Wysotzki (AAIP, 2005)

Spatial Inference with Constraints. - Christoph Schmoeger; Carsten Gips; Fritz Wysotzki (LWA, 2005)

SVM learning with the Schur-Hadamard inner product for graphs. - Brijnesh J. Jain; Peter Geibel; Fritz Wysotzki (Neurocomputing, 2005)

Solving inexact graph isomorphism problems using neural networks. - Brijnesh J. Jain; Fritz Wysotzki (Neurocomputing, 2005)

Risk-Sensitive Reinforcement Learning Applied to Control under Constraints. - Peter Geibel; Fritz Wysotzki (J. Artif. Intell. Res., 2005)

A New Information Measure Based on Example-Dependent Misclassification Costs and Its Application in Decision Tree Learning. - Fritz Wysotzki; Peter Geibel (Adv. Artif. Intell., 2009)