Peter A. Flach

	2012
100		Stephen Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan: ILP turns 20 - Biography and future challenges. Machine Learning 86(1): 3-23 (2012)
	2011
99		William Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin: Smooth Receiver Operating Characteristics (smROC) Curves. ECML/PKDD (2) 2011: 193-208
98		José Hernández-Orallo, Peter A. Flach, Cèsar Ferri Ramirez: Brier Curves: a New Cost-Based Visualisation of Classifier Performance. ICML 2011: 585-592
97		Peter A. Flach, José Hernández-Orallo, Cèsar Ferri Ramirez: A Coherent Interpretation of AUC as a Measure of Aggregated Classification Performance. ICML 2011: 657-664
96		José Hernández-Orallo, Peter A. Flach, Cèsar Ferri Ramirez: Technical Note: Towards ROC Curves in Cost Space CoRR abs/1107.5930: (2011)
95		José Hernández-Orallo, Peter A. Flach, César Ferri: Threshold Choice Methods: the Missing Link CoRR abs/1112.2640: (2011)
94		Peter A. Flach: The Machine Learning journal: 25 years young. Machine Learning 82(3): 273-274 (2011)
	2010
93		Sebastian Spiegler, Peter A. Flach: Enhanced Word Decomposition by Calibrating the Decision Threshold of Probabilistic Models and Using a Model Ensemble. ACL 2010: 375-383
92		Sebastian Spiegler, Andrew van der Spuy, Peter A. Flach: Ukwabelana - An open-source morphological Zulu corpus. COLING 2010: 1020-1028
91		Tarek Abudawood, Peter A. Flach: The Advantages of Seed Examples in First-Order Multi-class Subgroup Discovery. ECAI 2010: 1113-1114
90		Tarek Abudawood, Peter A. Flach: Learning Multi-class Theories in ILP. ILP 2010: 6-13
89		Tarek Abudawood, Peter A. Flach: First-Order Multi-class Subgroup Discovery. STAIRS 2010: 1-12
88		Simon Price, Peter A. Flach, Sebastian Spiegler, Christopher Bailey, Nikki Rogers: SubSift Web Services and Workflows for Profiling and Comparing Scientists and Their Published Works. eScience 2010: 182-189
87		Peter A. Flach: First-Order Logic. Encyclopedia of Machine Learning 2010: 410-415
86		Peter A. Flach: ROC Analysis. Encyclopedia of Machine Learning 2010: 869-875
85		Simon Price, Peter A. Flach, Sebastian Spiegler: SubSift: a novel application of the vector space model to support the academic research process. Journal of Machine Learning Research - Proceedings Track 11: 20-27 (2010)
84		Tarek Abudawood, Peter A. Flach: Exploiting the High Predictive Power of Multi-class Subgroups. Journal of Machine Learning Research - Proceedings Track 13: 177-192 (2010)
83		Peter A. Flach: The Machine Learning journal: 250 issues and counting. Machine Learning 81(3): 227-228 (2010)
	2009
82		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
81		Sebastian Spiegler, Bruno Golénia, Peter A. Flach: Unsupervised Word Decomposition with the Promodes Algorithm. CLEF (1) 2009: 625-632
80		Bruno Golénia, Sebastian Spiegler, Peter A. Flach: Unsupervised Morpheme Discovery with Ungrade. CLEF (1) 2009: 633-640
79		William Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin: Cost-Based Sampling of Individual Instances. Canadian Conference on AI 2009: 86-97
78		Tarek Abudawood, Peter A. Flach: Evaluation Measures for Multi-class Subgroup Discovery. ECML/PKDD (1) 2009: 35-50
77		Kseniya B. Shalonova, Bruno Golénia, Peter A. Flach: Towards Learning Morphology for Under-Resourced Fusional and Agglutinating Languages. IEEE Transactions on Audio, Speech & Language Processing 17(5): 956-965 (2009)
76		Antonis C. Kakas, Peter A. Flach: Abduction and Induction in Artificial Intelligence. J. Applied Logic 7(3): 251 (2009)
75		Peter A. Flach, Sebastian Spiegler, Bruno Golénia, Simon Price, John Guiver, Ralf Herbrich, Thore Graepel, Mohammed J. Zaki: Novel tools to streamline the conference review process: experiences from SIGKDD'09. SIGKDD Explorations 11(2): 63-67 (2009)
	2008
74		Susanne 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
73		Simon Price, Peter A. Flach: Querying and Merging Heterogeneous Data by Approximate Joins on Higher-Order Terms. ILP 2008: 226-243
72		Sebastian Spiegler, Bruno Golénia, Ksenia Shalonova, Peter A. Flach, Roger C. F. Tucker: Learning the morphology of Zulu with different degrees of supervision. SLT 2008: 9-12
	2007
71		Shaomin Wu, Peter A. Flach, Cèsar Ferri Ramirez: An Improved Model Selection Heuristic for AUC. ECML 2007: 478-489
70		Peter A. Flach, Edson Takashi Matsubara: A Simple Lexicographic Ranker and Probability Estimator. ECML 2007: 575-582
69		Peter A. Flach: Putting Things in Order: On the Fundamental Role of Ranking in Classification and Probability Estimation. ECML/PKDD 2007: 2-3
68		Peter A. Flach, Edson Takashi Matsubara: On classification, ranking, and probability estimation. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007
67		Susanne Hoche, Andreas Nürnberger, Peter A. Flach: Network analysis in natural sciences and engineering. AI Commun. 20(4): 229-230 (2007)
	2006
66		Peter A. Flach: Reinventing Machine Learning with ROC Analysis. IBERAMIA-SBIA 2006: 4-5
65		Kerstin Eder, Peter A. Flach, Hsiou-Wen Hsueh: Towards Automating Simulation-Based Design Verification Using ILP. ILP 2006: 154-168
	2005
64		Elias Gyftodimos, Peter A. Flach: Combining Bayesian Networks with Higher-Order Data Representations. IDA 2005: 145-156
63		Peter A. Flach, Shaomin Wu: Repairing Concavities in ROC Curves. IJCAI 2005: 702-707
62		Ronaldo C. Prati, Peter A. Flach: ROCCER: An Algorithm for Rule Learning Based on ROC Analysis. IJCAI 2005: 823-828
61		Elias Gyftodimos, Peter A. Flach: Combining Bayesian Networks with Higher-Order Data Representations. Probabilistic, Logical and Relational Learning 2005
60		Tom 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)
59		Johannes Fürnkranz, Peter A. Flach: ROC 'n' Rule Learning-Towards a Better Understanding of Covering Algorithms. Machine Learning 58(1): 39-77 (2005)
	2004
58		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
57		Johannes Fürnkranz, Peter A. Flach: An Analysis of Stopping and Filtering Criteria for Rule Learning. ECML 2004: 123-133
56		César Ferri, Peter A. Flach, José Hernández-Orallo: Delegating classifiers. ICML 2004
55		Annalisa Appice, Michelangelo Ceci, Simon Rawles, Peter A. Flach: Redundant feature elimination for multi-class problems. ICML 2004
54		Elias Gyftodimos, Peter A. Flach: Hierarchical Bayesian Networks: An Approach to Classification and Learning for Structured Data. SETN 2004: 291-300
53		Nada Lavrac, Branko Kavsek, Peter A. Flach, Ljupco Todorovski: Subgroup Discovery with CN2-SD. Journal of Machine Learning Research 5: 153-188 (2004)
52		Nada 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)
51		Thomas Gärtner, John W. Lloyd, Peter A. Flach: Kernels and Distances for Structured Data. Machine Learning 57(3): 205-232 (2004)
50		Peter A. Flach, Nicolas Lachiche: Naive Bayesian Classification of Structured Data. Machine Learning 57(3): 233-269 (2004)
49		José 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)
48		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)
	2003
47		Thomas Gärtner, Peter A. Flach, Stefan Wrobel: On Graph Kernels: Hardness Results and Efficient Alternatives. COLT 2003: 129-143
46		César Ferri, Peter A. Flach, José Hernández-Orallo: Improving the AUC of Probabilistic Estimation Trees. ECML 2003: 121-132
45		Peter A. Flach: The Geometry of ROC Space: Understanding Machine Learning Metrics through ROC Isometrics. ICML 2003: 194-201
44		Johannes Fürnkranz, Peter A. Flach: An Analysis of Rule Evaluation Metrics. ICML 2003: 202-209
43		Nicolas Lachiche, Peter A. Flach: Improving Accuracy and Cost of Two-class and Multi-class Probabilistic Classifiers Using ROC Curves. ICML 2003: 416-423
42		Mark-A. Krogel, Simon Rawles, Filip Zelezný, Peter A. Flach, Nada Lavrac, Stefan Wrobel: Comparative Evaluation of Approaches to Propositionalization. ILP 2003: 197-214
41		Dimitrios Mavroeidis, Peter A. Flach: Improved Distances for Structured Data. ILP 2003: 251-268
	2002
40		Peter A. Flach, Nada Lavrac: Learning in Clausal Logic: A Perspective on Inductive Logic Programming. Computational Logic: Logic Programming and Beyond 2002: 437-471
39		Yonghong Peng, Peter A. Flach, Carlos Soares, Pavel Brazdil: Improved Dataset Characterisation for Meta-learning. Discovery Science 2002: 141-152
38		Nada Lavrac, Peter A. Flach, Branko Kavsek, Ljupco Todorovski: Adapting classification rule induction to subgroup discovery. ICDM 2002: 266-273
37		César Ferri, Peter A. Flach, José Hernández-Orallo: Learning Decision Trees Using the Area Under the ROC Curve. ICML 2002: 139-146
36		Thomas Gärtner, Peter A. Flach, Adam Kowalczyk, Alex J. Smola: Multi-Instance Kernels. ICML 2002: 179-186
35		Nicolas Lachiche, Peter A. Flach: 1BC2: A True First-Order Bayesian Classifier. ILP 2002: 133-148
34		Nada Lavrac, Filip Zelezný, Peter A. Flach: RSD: Relational Subgroup Discovery through First-Order Feature Construction. ILP 2002: 149-165
33		Thomas Gärtner, John W. Lloyd, Peter A. Flach: Kernels for Structured Data. ILP 2002: 66-83
32		Tanja Urbancic, Maja Skrjanc, Peter A. Flach: Web-based analysis of data mining and decision support education. AI Commun. 15(4): 199-204 (2002)
	2001
31		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
30		Peter A. Flach: Multi-relational Data Mining: a perspective. EPIA 2001: 3-4
29		Thomas Gärtner, Peter A. Flach: WBCsvm: Weighted Bayesian Classification based on Support Vector Machines. ICML 2001: 154-161
28		Nada Lavrac, Peter A. Flach: An extended transformation approach to inductive logic programming. ACM Trans. Comput. Log. 2(4): 458-494 (2001)
27		Peter A. Flach: On the state of the art in machine learning: A personal review. Artif. Intell. 131(1-2): 199-222 (2001)
26		Peter A. Flach, Nicolas Lachiche: Confirmation-Guided Discovery of First-Order Rules with Tertius. Machine Learning 42(1/2): 61-95 (2001)
25		Peter A. Flach, Saso Dzeroski: Editorial: Inductive Logic Programming is Coming of Age. Machine Learning 44(3): 207-209 (2001)
	2000
24		Peter A. Flach, Nicolas Lachiche: Decomposing Probability Distributions on Structured Individuals. ILP Work-in-progress reports 2000
23		Ljupco Todorovski, Peter A. Flach, Nada Lavrac: Predictive Performance of Weghted Relative Accuracy. PKDD 2000: 255-264
22		Peter A. Flach: The Use of Functional and Logic Languages in Machine Learning. WFLP 2000: 225-237
21		Iztok Savnik, Peter A. Flach: Discovery of multivalued dependencies from relations. Intell. Data Anal. 4(3-4): 195-211 (2000)
	1999
20		Saso Dzeroski, Peter A. Flach: Inductive Logic Programming, 9th International Workshop, ILP-99, Bled, Slovenia, June 24-27, 1999, Proceedings Springer 1999
19		Peter A. Flach: Knowledge Representation for Inductive Learning. ESCQARU 1999: 160-167
18		Nada Lavrac, Peter A. Flach, Blaz Zupan: Rule Evaluation Measures: A Unifying View. ILP 1999: 174-185
17		Peter A. Flach, Nicolas Lachiche: IBC: A First-Order Bayesian Classifier. ILP 1999: 92-103
16		Peter A. Flach, Iztok Savnik: Database Dependency Discovery: A Machine Learning Approach. AI Commun. 12(3): 139-160 (1999)
	1998
15		Peter A. Flach, Christophe G. Giraud-Carrier, John W. Lloyd: Strongly Typed Inductive Concept Learning. ILP 1998: 185-194
14		Peter A. Flach: Comparing Consequence Relations. KR 1998: 180-189
13		Peter 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
12		Peter 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)
	1997
11		Peter A. Flach: Inductive Logic Databases: From Extensional to Intensional Knowledge. DOOD 1997: 3
10		Peter A. Flach: Normal Forms for Inductive Logic Programming. ILP 1997: 149-156
9		Peter A. Flach, Antonis C. Kakas: Abductive and Inductive Reasoning: Report of the ECAI'96 Workshop. Logic Journal of the IGPL 5(5): 773-778 (1997)
	1996
8		Peter A. Flach: Rationality Postulates for Induction. TARK 1996: 267-281
	1994
7		Peter A. Flach: Simply logical - intelligent reasoning by example. Wiley 1994: I-XV, 1-240
	1993
6		Peter A. Flach: Predicate Invention in Inductive Data Engineering. ECML 1993: 83-94
	1992
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
	1991
3		Shan-Hwei Nienhuys-Cheng, Peter A. Flach: Consistent Term Mappings, Term Partitions and Inverse Resolution. EWSL 1991: 361-374
2		Peter A. Flach: Towards a Theory of Inductive Logic Programming. ISMIS 1991: 510-519
	1989
1		Peter A. Flach: Second-order Inductive Learning. AII 1989: 202-216

Coauthor Index

1	Tarek Abudawood	[78] [84] [89] [90] [91]
2	Annalisa Appice	[55]
3	Christopher Bailey	[88]
4	Ivan Bratko	[100]
5	Pavel Brazdil	[39]
6	Michelangelo Ceci	[55]
7	Bojan Cestnik	[52]
8	Saso Dzeroski	[20] [25]
9	Kerstin Eder	[65]
10	John F. Elder IV	[82]
11	Tom Fawcett	[60]
12	César Ferri (Cèsar Ferri Ramirez)	[37] [46] [49] [56] [58] [71] [95] [96] [97] [98]
13	Françoise Fogelman-Soulié	[82]
14	Johannes Fürnkranz	[44] [57] [59]
15	Dragan Gamberger	[52]
16	Thomas Gärtner	[29] [33] [36] [47] [51]
17	Christophe G. Giraud-Carrier	[15]
18	Bruno Golénia	[72] [75] [77] [80] [81]
19	Thore Graepel	[75]
20	John Guiver	[75]
21	Elias Gyftodimos	[54] [61] [64]
22	David Hardcastle	[74]
23	Ralf Herbrich	[75]
24	José Hernández-Orallo	[37] [46] [49] [56] [58] [95] [96] [97] [98]
25	Susanne Hoche	[67] [74]
26	Hsiou-Wen Hsueh	[65]
27	Katsumi Inoue	[100]
28	Nathalie Japkowicz	[79] [99]
29	Antonis C. Kakas	[9] [12] [76]
30	Branko Kavsek	[38] [53]
31	William Klement	[79] [99]
32	Adam Kowalczyk	[36]
33	Mark-A. Krogel	[42]
34	Nicolas Lachiche	[17] [24] [26] [35] [43] [49] [50] [58]
35	Nada Lavrac	[18] [23] [28] [34] [38] [40] [42] [52] [53]
36	John W. Lloyd	[15] [33] [51]
37	Edson Takashi Matsubara	[68] [70]
38	Stan Matwin	[79] [99]
39	Dimitrios Mavroeidis	[41]
40	Stephen Muggleton	[100]
41	Shan-Hwei Nienhuys-Cheng	[3]
42	Andreas Nürnberger	[67]
43	Yonghong Peng	[39]
44	David Poole	[100]
45	Ronaldo C. Prati (Ronaldo Cristiano Prati)	[62]
46	Simon Price	[73] [75] [85] [88]
47	Luc De Raedt	[31] [100]
48	Simon Rawles	[42] [55]
49	Nikki Rogers	[88]
50	Iztok Savnik	[16] [21]
51	Kseniya B. Shalonova (Ksenia Shalonova)	[72] [77]
52	Maja Skrjanc	[32]
53	Alexander J. Smola (Alex J. Smola)	[36]
54	Carlos Soares	[39]
55	Sebastian Spiegler	[72] [75] [80] [81] [85] [88] [92] [93]
56	Andrew van der Spuy	[92]
57	Ashwin Srinivasan	[100]
58	Ljupco Todorovski	[23] [38] [53]
59	Roger C. F. Tucker	[72]
60	Tanja Urbancic	[32]
61	Stefan Wrobel	[42] [47]
62	Shaomin Wu	[63] [71]
63	Mohammed Javeed Zaki (Mohammed J. Zaki)	[75] [82]
64	Filip Zelezný	[34] [42]
65	Blaz Zupan	[18]

Colors in the list of coauthors

Last update Wed May 30 22:34:44 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page