Peter A. Flach Vis

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75 John F. Elder IV, Françoise Fogelman-Soulié, Peter A. Flach, Mohammed Javeed Zaki: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28 - July 1, 2009 ACM 2009
74EEWilliam Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin: Cost-Based Sampling of Individual Instances. Canadian Conference on AI 2009: 86-97
73EEAntonis C. Kakas, Peter A. Flach: Abduction and Induction in Artificial Intelligence. J. Applied Logic 7(3): 251 (2009)
72EESusanne Hoche, Peter A. Flach, David Hardcastle: A Fast Method for Property Prediction in Graph-Structured Data from Positive and Unlabelled Examples. ECAI 2008: 162-166
71EESimon Price, Peter A. Flach: Querying and Merging Heterogeneous Data by Approximate Joins on Higher-Order Terms. ILP 2008: 226-243
70EEShaomin Wu, Peter A. Flach, Cèsar Ferri Ramirez: An Improved Model Selection Heuristic for AUC. ECML 2007: 478-489
69EEPeter A. Flach, Edson Takashi Matsubara: A Simple Lexicographic Ranker and Probability Estimator. ECML 2007: 575-582
68EEPeter A. Flach: Putting Things in Order: On the Fundamental Role of Ranking in Classification and Probability Estimation. ECML/PKDD 2007: 2-3
67EEPeter A. Flach, Edson Takashi Matsubara: On classification, ranking, and probability estimation. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007
66EESusanne Hoche, Andreas Nürnberger, Peter A. Flach: Network analysis in natural sciences and engineering. AI Commun. 20(4): 229-230 (2007)
65EEPeter A. Flach: Reinventing Machine Learning with ROC Analysis. IBERAMIA-SBIA 2006: 4-5
64EEKerstin Eder, Peter A. Flach, Hsiou-Wen Hsueh: Towards Automating Simulation-Based Design Verification Using ILP. ILP 2006: 154-168
63EEElias Gyftodimos, Peter A. Flach: Combining Bayesian Networks with Higher-Order Data Representations. IDA 2005: 145-156
62EEPeter A. Flach, Shaomin Wu: Repairing Concavities in ROC Curves. IJCAI 2005: 702-707
61EERonaldo C. Prati, Peter A. Flach: ROCCER: An Algorithm for Rule Learning Based on ROC Analysis. IJCAI 2005: 823-828
60EEElias Gyftodimos, Peter A. Flach: Combining Bayesian Networks with Higher-Order Data Representations. Probabilistic, Logical and Relational Learning 2005
59EETom Fawcett, Peter A. Flach: A Response to Webb and Ting's On the Application of ROC Analysis to Predict Classification Performance Under Varying Class Distributions. Machine Learning 58(1): 33-38 (2005)
58EEJohannes Fürnkranz, Peter A. Flach: ROC 'n' Rule Learning-Towards a Better Understanding of Covering Algorithms. Machine Learning 58(1): 39-77 (2005)
57 José Hernández-Orallo, César Ferri, Nicolas Lachiche, Peter A. Flach: ROC Analysis in Artificial Intelligence, 1st International Workshop, ROCAI-2004, Valencia, Spain, August 22, 2004 ROCAI 2004
56EEJohannes Fürnkranz, Peter A. Flach: An Analysis of Stopping and Filtering Criteria for Rule Learning. ECML 2004: 123-133
55EECésar Ferri, Peter A. Flach, José Hernández-Orallo: Delegating classifiers. ICML 2004
54EEAnnalisa Appice, Michelangelo Ceci, Simon Rawles, Peter A. Flach: Redundant feature elimination for multi-class problems. ICML 2004
53EEElias Gyftodimos, Peter A. Flach: Hierarchical Bayesian Networks: An Approach to Classification and Learning for Structured Data. SETN 2004: 291-300
52EENada Lavrac, Branko Kavsek, Peter A. Flach, Ljupco Todorovski: Subgroup Discovery with CN2-SD. Journal of Machine Learning Research 5: 153-188 (2004)
51EENada Lavrac, Bojan Cestnik, Dragan Gamberger, Peter A. Flach: Decision Support Through Subgroup Discovery: Three Case Studies and the Lessons Learned. Machine Learning 57(1-2): 115-143 (2004)
50EEThomas Gärtner, John W. Lloyd, Peter A. Flach: Kernels and Distances for Structured Data. Machine Learning 57(3): 205-232 (2004)
49EEPeter A. Flach, Nicolas Lachiche: Naive Bayesian Classification of Structured Data. Machine Learning 57(3): 233-269 (2004)
48EEJosé Hernández-Orallo, César Ferri, Nicolas Lachiche, Peter A. Flach: The 1st workshop on ROC analysis in artificial intelligence (ROCAI-2004). SIGKDD Explorations 6(2): 159-161 (2004)
47 Peter A. Flach: Book review: Logic for Learning: Learning Comprehensible Theories from Structured Data by John W. Lloyd, Springer-Verlag, 2003, ISBN 3-540-42027-4. TPLP 4(5-6): 753-755 (2004)
46EEThomas Gärtner, Peter A. Flach, Stefan Wrobel: On Graph Kernels: Hardness Results and Efficient Alternatives. COLT 2003: 129-143
45EECésar Ferri, Peter A. Flach, José Hernández-Orallo: Improving the AUC of Probabilistic Estimation Trees. ECML 2003: 121-132
44 Peter A. Flach: The Geometry of ROC Space: Understanding Machine Learning Metrics through ROC Isometrics. ICML 2003: 194-201
43 Johannes Fürnkranz, Peter A. Flach: An Analysis of Rule Evaluation Metrics. ICML 2003: 202-209
42 Nicolas Lachiche, Peter A. Flach: Improving Accuracy and Cost of Two-class and Multi-class Probabilistic Classifiers Using ROC Curves. ICML 2003: 416-423
41EEMark-A. Krogel, Simon Rawles, Filip Zelezný, Peter A. Flach, Nada Lavrac, Stefan Wrobel: Comparative Evaluation of Approaches to Propositionalization. ILP 2003: 197-214
40EEDimitrios Mavroeidis, Peter A. Flach: Improved Distances for Structured Data. ILP 2003: 251-268
39EEPeter A. Flach, Nada Lavrac: Learning in Clausal Logic: A Perspective on Inductive Logic Programming. Computational Logic: Logic Programming and Beyond 2002: 437-471
38EEYonghong Peng, Peter A. Flach, Carlos Soares, Pavel Brazdil: Improved Dataset Characterisation for Meta-learning. Discovery Science 2002: 141-152
37EENada Lavrac, Peter A. Flach, Branko Kavsek, Ljupco Todorovski: Adapting classification rule induction to subgroup discovery. ICDM 2002: 266-273
36 César Ferri, Peter A. Flach, José Hernández-Orallo: Learning Decision Trees Using the Area Under the ROC Curve. ICML 2002: 139-146
35 Thomas Gärtner, Peter A. Flach, Adam Kowalczyk, Alex J. Smola: Multi-Instance Kernels. ICML 2002: 179-186
34EENicolas Lachiche, Peter A. Flach: 1BC2: A True First-Order Bayesian Classifier. ILP 2002: 133-148
33EENada Lavrac, Filip Zelezný, Peter A. Flach: RSD: Relational Subgroup Discovery through First-Order Feature Construction. ILP 2002: 149-165
32EEThomas Gärtner, John W. Lloyd, Peter A. Flach: Kernels for Structured Data. ILP 2002: 66-83
31EETanja Urbancic, Maja Skrjanc, Peter A. Flach: Web-based analysis of data mining and decision support education. AI Commun. 15(4): 199-204 (2002)
30 Luc De Raedt, Peter A. Flach: Machine Learning: EMCL 2001, 12th European Conference on Machine Learning, Freiburg, Germany, September 5-7, 2001, Proceedings Springer 2001
29EEPeter A. Flach: Multi-relational Data Mining: a perspective. EPIA 2001: 3-4
28 Thomas Gärtner, Peter A. Flach: WBCsvm: Weighted Bayesian Classification based on Support Vector Machines. ICML 2001: 154-161
27EENada Lavrac, Peter A. Flach: An extended transformation approach to inductive logic programming. ACM Trans. Comput. Log. 2(4): 458-494 (2001)
26EEPeter A. Flach: On the state of the art in machine learning: A personal review. Artif. Intell. 131(1-2): 199-222 (2001)
25 Peter A. Flach, Nicolas Lachiche: Confirmation-Guided Discovery of First-Order Rules with Tertius. Machine Learning 42(1/2): 61-95 (2001)
24 Peter A. Flach, Saso Dzeroski: Editorial: Inductive Logic Programming is Coming of Age. Machine Learning 44(3): 207-209 (2001)
23EEPeter A. Flach, Nicolas Lachiche: Decomposing Probability Distributions on Structured Individuals. ILP Work-in-progress reports 2000
22EELjupco Todorovski, Peter A. Flach, Nada Lavrac: Predictive Performance of Weghted Relative Accuracy. PKDD 2000: 255-264
21 Peter A. Flach: The Use of Functional and Logic Languages in Machine Learning. WFLP 2000: 225-237
20EEIztok Savnik, Peter A. Flach: Discovery of multivalued dependencies from relations. Intell. Data Anal. 4(3-4): 195-211 (2000)
19 Saso Dzeroski, Peter A. Flach: Inductive Logic Programming, 9th International Workshop, ILP-99, Bled, Slovenia, June 24-27, 1999, Proceedings Springer 1999
18EEPeter A. Flach: Knowledge Representation for Inductive Learning. ESCQARU 1999: 160-167
17EENada Lavrac, Peter A. Flach, Blaz Zupan: Rule Evaluation Measures: A Unifying View. ILP 1999: 174-185
16EEPeter A. Flach, Nicolas Lachiche: IBC: A First-Order Bayesian Classifier. ILP 1999: 92-103
15 Peter A. Flach, Iztok Savnik: Database Dependency Discovery: A Machine Learning Approach. AI Commun. 12(3): 139-160 (1999)
14 Peter A. Flach, Christophe G. Giraud-Carrier, John W. Lloyd: Strongly Typed Inductive Concept Learning. ILP 1998: 185-194
13 Peter A. Flach: Comparing Consequence Relations. KR 1998: 180-189
12EEPeter A. Flach: From Extensional to Intensional Knowledge: Inductive Logic Programming Techniques and Their Application to Deductive Databases. Transactions and Change in Logic Databases 1998: 356-387
11EEPeter A. Flach, Antonis C. Kakas: Abduction and Induction in AI: Report of the IJCAI'97 Workshop. Logic Journal of the IGPL 6(4): 651-656 (1998)
10EEPeter A. Flach: Inductive Logic Databases: From Extensional to Intensional Knowledge. DOOD 1997: 3
9 Peter A. Flach: Normal Forms for Inductive Logic Programming. ILP 1997: 149-156
8EEPeter A. Flach, Antonis C. Kakas: Abductive and Inductive Reasoning: Report of the ECAI'96 Workshop. Logic Journal of the IGPL 5(5): (1997)
7 Peter A. Flach: Rationality Postulates for Induction. TARK 1996: 267-281
6EEPeter A. Flach: Predicate Invention in Inductive Data Engineering. ECML 1993: 83-94
5 Peter A. Flach: An Analysis of Various Forms of "Jumping to Conclusions". AII 1992: 170-186
4 Peter A. Flach: A Model of Inductive Reasoning. Logic at Work 1992: 41-56
3EEShan-Hwei Nienhuys-Cheng, Peter A. Flach: Consistent Term Mappings, Term Partitions and Inverse Resolution. EWSL 1991: 361-374
2EEPeter A. Flach: Towards a Theory of Inductive Logic Programming. ISMIS 1991: 510-519
1 Peter A. Flach: Second-order Inductive Learning. AII 1989: 202-216

Coauthor Index

1Annalisa Appice [54]
2Pavel Brazdil [38]
3Michelangelo Ceci [54]
4Bojan Cestnik [51]
5Saso Dzeroski [19] [24]
6Kerstin Eder [64]
7John F. Elder IV [75]
8Tom Fawcett [59]
9César Ferri (Cèsar Ferri Ramirez) [36] [45] [48] [55] [57] [70]
10Françoise Fogelman-Soulié [75]
11Johannes Fürnkranz [43] [56] [58]
12Dragan Gamberger [51]
13Thomas Gärtner [28] [32] [35] [46] [50]
14Christophe G. Giraud-Carrier [14]
15Elias Gyftodimos [53] [60] [63]
16David Hardcastle [72]
17José Hernández-Orallo [36] [45] [48] [55] [57]
18Susanne Hoche [66] [72]
19Hsiou-Wen Hsueh [64]
20Nathalie Japkowicz [74]
21Antonis C. Kakas [8] [11] [73]
22Branko Kavsek [37] [52]
23William Klement [74]
24Adam Kowalczyk [35]
25Mark-A. Krogel [41]
26Nicolas Lachiche [16] [23] [25] [34] [42] [48] [49] [57]
27Nada Lavrac [17] [22] [27] [33] [37] [39] [41] [51] [52]
28John W. Lloyd [14] [32] [50]
29Edson Takashi Matsubara [67] [69]
30Stan Matwin [74]
31Dimitrios Mavroeidis [40]
32Shan-Hwei Nienhuys-Cheng [3]
33Andreas Nürnberger [66]
34Yonghong Peng [38]
35Ronaldo C. Prati [61]
36Simon Price [71]
37Luc De Raedt [30]
38Simon Rawles [41] [54]
39Iztok Savnik [15] [20]
40Maja Skrjanc [31]
41Alexander J. Smola (Alex J. Smola) [35]
42Carlos Soares [38]
43Ljupco Todorovski [22] [37] [52]
44Tanja Urbancic [31]
45Stefan Wrobel [41] [46]
46Shaomin Wu [62] [70]
47Mohammed Javeed Zaki (Mohammed J. Zaki) [75]
48Filip Zelezný [33] [41]
49Blaz Zupan [17]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)