Fritz Wysotzki

	2005
53		Christoph Schmoeger, Carsten Gips, Fritz Wysotzki: Spatial Inference with Constraints. LWA 2005: 228-233
52		Peter Geibel, Fritz Wysotzki: Risk-Sensitive Reinforcement Learning Applied to Control under Constraints. J. Artif. Intell. Res. (JAIR) 24: 81-108 (2005)
51		Brijnesh J. Jain, Fritz Wysotzki: Solving inexact graph isomorphism problems using neural networks. Neurocomputing 63: 45-67 (2005)
50		Brijnesh J. Jain, Peter Geibel, Fritz Wysotzki: SVM learning with the Schur-Hadamard inner product for graphs. Neurocomputing 64: 93-105 (2005)
	2004
49		Peter Geibel, Brijnesh J. Jain, Fritz Wysotzki: SVM learning with the SH inner product. ESANN 2004: 299-304
48		Brijnesh J. Jain, Fritz Wysotzki: The maximum weighted clique problem and Hopfield networks. ESANN 2004: 331-336
47		Brijnesh J. Jain, Peter Geibel, Fritz Wysotzki: Combining Recurrent Neural Networks and Support Vector Machines for Structural Pattern Recognition. KI 2004: 241-255
46		Carsten Gips, Fritz Wysotzki: Spatial Inference - Application of Machine Learning Algorithms. LWA 2004: 155-160
45		Brijnesh J. Jain, Fritz Wysotzki: Learning with Neural Networks in the Domain of Graphs. LWA 2004: 163-170
44		Brijnesh J. Jain, Fritz Wysotzki: Structural Perceptrons for Attributed Graphs. SSPR/SPR 2004: 85-94
43		Peter Geibel, Fritz Wysotzki: Learning Perceptrons and Piecewise Linear Classifiers Sensitive to Example Dependent Costs. Appl. Intell. 21(1): 45-56 (2004)
42		Peter Geibel, Ulf Brefeld, Fritz Wysotzki: Perceptron and SVM learning with generalized cost models. Intell. Data Anal. 8(5): 439-455 (2004)
41		Stefan Bischoff, Fritz Wysotzki: Applied Connectionistic Methods to compare Segmented Images. KI 18(1): 11- (2004)
40		Brijnesh J. Jain, Fritz Wysotzki: Central Clustering of Attributed Graphs. Machine Learning 56(1-3): 169-207 (2004)
39		Brijnesh J. Jain, Fritz Wysotzki: Discrimination networks for maximum selection. Neural Networks 17(1): 143-154 (2004)
	2003
38		Ulf Brefeld, Peter Geibel, Fritz Wysotzki: Support Vector Machines with Example Dependent Costs. ECML 2003: 23-34
37		Brijnesh J. Jain, Fritz Wysotzki: An Associative Memory for the Automorphism Group of Structures. ESANN 2003: 107-112
36		Brijnesh J. Jain, Fritz Wysotzki: A Neural Graph Isomorphism Algorithm based on local Invariants. ESANN 2003: 79-84
35		Brijnesh J. Jain, Fritz Wysotzki: A Competitive Winner-Takes-All Architecture for Classification and Pattern Recognition of Structures. GbRPR 2003: 259-270
34		Brijnesh J. Jain, Fritz Wysotzki: A Novel Neural Network Approach to Solve Exact and Inexact Graph Isomorphism Problems. ICANN 2003: 299-306
33		Peter Geibel, Fritz Wysotzki: Perceptron Based Learning with Example Dependent and Noisy Costs. ICML 2003: 218-225
32		Peter Geibel, Ulf Brefeld, Fritz Wysotzki: Learning Linear Classifiers Sensitive to Example Dependent and Noisy Costs. IDA 2003: 167-178
31		Carsten Gips, Fritz Wysotzki: Spatial Inference - Combining Learning and Constraint Solving. KI 2003: 282-296
30		Stefan Bischoff, D. Reuss, Fritz Wysotzki: Applied Connectionistic Methods in Computer Vision to Compare Segmented Images. KI 2003: 312-326
29		Brijnesh J. Jain, Fritz Wysotzki: A k-Winner-Takes-All Classifier for Structured Data. KI 2003: 342-354
28		Peter Geibel, Kristina Schädler, Fritz Wysotzki: Connectionist construction of prototypes from decision trees for graph classification. Intell. Data Anal. 7(2): 125-140 (2003)
27		Brijnesh J. Jain, Fritz Wysotzki: Automorphism Partitioning with Neural Networks. Neural Processing Letters 17(2): 205-215 (2003)
	2002
26		Emanuel Kitzelmann, Ute Schmid, Martin Mühlpfordt, Fritz Wysotzki: Inductive Synthesis of Functional Programs. AISC 2002: 26-37
25		Ute Schmid, Marina Müller, Fritz Wysotzki: Integrating Function Application in State-Based Planning. KI 2002: 144-162
24		Brijnesh J. Jain, Fritz Wysotzki: Fast Winner-Takes-All Networks for the Maximum Clique Problem. KI 2002: 163-173
23		Peter Geibel, Kristina Schädler, Fritz Wysotzki: Learning of Class Descriptions from Class Discriminations: A Hybrid Approach for Relational Objects. KI 2002: 186-204
22		Carsten Gips, Petra Hofstedt, Fritz Wysotzki: Spatial Inference - Learning vs. Constraint Solving. KI 2002: 299-316
	2001
21		Brijnesh J. Jain, Fritz Wysotzki: On the short-term-memory of WTA nets. ESANN 2001: 289-294
20		Brijnesh J. Jain, Fritz Wysotzki: Efficient Pattern Discrimination with Inhibitory WTA Nets. ICANN 2001: 827-834
	2000
19		Ute Schmid, Fritz Wysotzki: Applying Inductive Program Synthesis to Macro Learning. AIPS 2000: 371-378
18		Sylvia Wiebrock, Lars Wittenburg, Ute Schmid, Fritz Wysotzki: Inference and Visualization of Spatial Relations. Spatial Cognition 2000: 212-224
17		Peter Geibel, Fritz Wysotzki: Graphbasierte Lernverfahren für relationale Daten. Inform., Forsch. Entwickl. 15(1): 1-15 (2000)
	1999
16		Kristina Schädler, Fritz Wysotzki: Comparing Structures Using a Hopfield-Style Neural Network. Appl. Intell. 11(1): 15-30 (1999)
	1998
15		Ute Schmid, Fritz Wysotzki: Induction of Recursive Program Schemes. ECML 1998: 214-225
14		Kristina Schädler, Fritz Wysotzki: Application of a neural net in classification and knowledge discovery. ESANN 1998: 117-122
13		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
12		Kristina Schädler, Fritz Wysotzki: A Connectionist Approach to the Distance-Based Analysis of Relational Data. IDA 1997: 137-148
11		Peter Geibel, Fritz Wysotzki: A Logical Framework for Graph Theoretical Decision Tree Learning. ILP 1997: 173-180
10		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
9		Peter Geibel, Fritz Wysotzki: Relational Learning with Decision Trees. ECAI 1996: 428-432
8		Peter Geibel, Fritz Wysotzki: Learning Relational Concepts with Decision Trees. ICML 1996: 166-174
7		Tobias Scheffer, Ralf Herbrich, Fritz Wysotzki: Efficient Theta-Subsumption Based on Graph Algorithms. Inductive Logic Programming Workshop 1996: 212-228
	1995
6		Wolfgang Müller, Fritz Wysotzki: Automatic Synthesis of Control Programs by Combination of Learning and Problem Solving Methods (Extended Abstract). ECML 1995: 323-326
5		Christel Wisotzki, Fritz Wysotzki: Prototype, Nearest Neighbor and Hybrid Algorithms for Time Series Classification (Extended Abstract). ECML 1995: 364-367
	1994
4		Barbara Schulmeister, Fritz Wysotzki: The Piecewise Linear Classifier DIPOL92. ECML 1994: 411-414
	1986
3		Fritz Wysotzki: Program Synthesis by Hierarchical Planning. AIMSA 1986: 3-11
	1983
2		Fritz Wysotzki: Representation and Induction of Infinite Concepts and Recursive Action Sequences. IJCAI 1983: 409-414
	1981
1		Fritz Wysotzki, Werner Kolbe, Joachim Selbig: Concept Learning by Structured Examples - An Algebraic Approach. IJCAI 1981: 153-158

Coauthor Index

1	Stefan Bischoff	[30] [41]
2	Ulf Brefeld	[32] [38] [42]
3	Berry Claus	[13]
4	Klaus Eyferth	[13]
5	Peter Geibel	[8] [9] [11] [17] [23] [28] [32] [33] [38] [42] [43] [47] [49] [50] [52]
6	Carsten Gips	[13] [22] [31] [46] [53]
7	Ralf Herbrich	[7]
8	Petra Hofstedt	[22]
9	Robin Hörnig	[13]
10	Brijnesh J. Jain	[20] [21] [24] [27] [29] [34] [35] [36] [37] [39] [40] [44] [45] [47] [48] [49] [50] [51]
11	Emanuel Kitzelmann	[26]
12	Werner Kolbe	[1]
13	Martin Mühlpfordt	[26]
14	Marina Müller	[25]
15	Wolfgang Müller	[6]
16	D. Reuss	[30]
17	Kristina Schädler	[10] [12] [14] [16] [23] [28]
18	Tobias Scheffer	[7]
19	Ute Schmid	[13] [15] [18] [19] [25] [26]
20	Christoph Schmoeger	[53]
21	Barbara Schulmeister	[4]
22	Joachim Selbig	[1]
23	Sylvia Wiebrock	[13] [18]
24	Christel Wisotzki	[5]
25	Lars Wittenburg	[18]

Colors in the list of coauthors