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*2009
111EEHuma Lodhi, Stephen Muggleton, Michael J. E. Sternberg: Learning Large Margin First Order Decision Lists for Multi-Class Classification. Discovery Science 2009: 168-183
110EEJosé Carlos Almeida Santos, Alireza Tamaddoni-Nezhad, Stephen Muggleton: An ILP System for Learning Head Output Connected Predicates. EPIA 2009: 150-159
109EEHuma Lodhi, Stephen Muggleton, Michael J. E. Sternberg: Multi-class protein fold recognition using large margin logic based divide and conquer learning. KDD Workshop on Statistical and Relational Learning in Bioinformatics 2009: 22-26
2008
108 Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen Muggleton: Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04. - 20.04.2007 Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2008
107 Luc De Raedt, Paolo Frasconi, Kristian Kersting, Stephen Muggleton: Probabilistic Inductive Logic Programming - Theory and Applications Springer 2008
106EEAndreas Fidjeland, Wayne Luk, Stephen Muggleton: A Customisable Multiprocessor for Application-Optimised Inductive Logic Programming. BCS Int. Acad. Conf. 2008: 318-330
105EEStephen Muggleton, José Carlos Almeida Santos, Alireza Tamaddoni-Nezhad: TopLog: ILP Using a Logic Program Declarative Bias. ICLP 2008: 687-692
104EEAlireza Tamaddoni-Nezhad, Stephen Muggleton: A Note on Refinement Operators for IE-Based ILP Systems. ILP 2008: 297-314
103EEJianzhong Chen, Lawrence A. Kelley, Stephen Muggleton, Michael J. E. Sternberg: Protein Fold Discovery Using Stochastic Logic Programs. Probabilistic Inductive Logic Programming 2008: 244-262
102EEStephen Muggleton, Jianzhong Chen: A Behavioral Comparison of Some Probabilistic Logic Models. Probabilistic Inductive Logic Programming 2008: 305-324
101EEStephen Muggleton: Developing Robust Synthetic Biology Designs Using a Microfluidic Robot Scientist. SBIA 2008: 4
100EEStephen Muggleton: From ILP to PILP. SBIA 2008: 7
99EEStephen Muggleton, Ramón P. Otero, Simon Colton: Guest editorial: special issue on Inductive Logic Programming. Machine Learning 70(2-3): 119-120 (2008)
98EEStephen Muggleton, Alireza Tamaddoni-Nezhad: QG/GA: a stochastic search for Progol. Machine Learning 70(2-3): 121-133 (2008)
97EEThomas G. Dietterich, Pedro Domingos, Lise Getoor, Stephen Muggleton, Prasad Tadepalli: Structured machine learning: the next ten years. Machine Learning 73(1): 3-23 (2008)
96EEJianzhong Chen, Stephen Muggleton, José Carlos Almeida Santos: Learning probabilistic logic models from probabilistic examples. Machine Learning 73(1): 55-85 (2008)
2007
95 Stephen Muggleton, Ramón P. Otero, Alireza Tamaddoni-Nezhad: Inductive Logic Programming, 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers Springer 2007
94EEJianzhong Chen, Stephen Muggleton, Jose Santos: Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract). ILP 2007: 22-23
93EEJianzhong Chen, Stephen Muggleton, Jose Santos: Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning. MLG 2007
92EELuc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen Muggleton: 07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007
2006
91 Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton: Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January - 4. February 2005 Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany 2006
90 Stephen Muggleton: Towards Chemical Universal Turing Machines. AAAI 2006
89EEJianzhong Chen, Lawrence A. Kelley, Stephen Muggleton, Michael J. E. Sternberg: Multi-class Prediction Using Stochastic Logic Programs. ILP 2006: 109-124
88EEStephen Muggleton, Niels Pahlavi: The Complexity of Translating BLPs to RMMs. ILP 2006: 351-365
87EEStephen Muggleton, Alireza Tamaddoni-Nezhad: QG/GA: A Stochastic Search for Progol. ILP 2006: 37-39
86EEAlireza Tamaddoni-Nezhad, Raphael Chaleil, Antonis C. Kakas, Stephen Muggleton: Application of abductive ILP to learning metabolic network inhibition from temporal data. Machine Learning 64(1-3): 209-230 (2006)
85EESimon Colton, Stephen Muggleton: Mathematical applications of inductive logic programming. Machine Learning 64(1-3): 25-64 (2006)
2005
84EEStephen Muggleton, Huma Lodhi, Ata Amini, Michael J. E. Sternberg: Support Vector Inductive Logic Programming. Discovery Science 2005: 163-175
83EEStephen Muggleton: Machine Learning for Systems Biology. ILP 2005: 416-423
82EEHiroaki Watanabe, Stephen Muggleton: Learning Stochastic Logical Automaton. JSAI Workshops 2005: 201-211
81EEHuma Lodhi, Stephen Muggleton: Computing Confidence Measures in Stochastic Logic Programs. MICAI 2005: 890-899
80EELuc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton: 05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning 2005
79EELuc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton: 05051 Executive Summary - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning 2005
2004
78EEHuma Lodhi, Stephen Muggleton: Modelling Metabolic Pathways Using Stochastic Logic Programs-Based Ensemble Methods. CMSB 2004: 119-133
77EEAlireza Tamaddoni-Nezhad, Antonis C. Kakas, Stephen Muggleton, Florencio Pazos: Modelling Inhibition in Metabolic Pathways Through Abduction and Induction. ILP 2004: 305-322
2003
76EEStephen Muggleton, Alireza Tamaddoni-Nezhad, Hiroaki Watanabe: Induction of Enzyme Classes from Biological Databases. ILP 2003: 269-280
75EESimon Colton, Stephen Muggleton: ILP for Mathematical Discovery. ILP 2003: 93-111
74 Jung-Wook Bang, Alexandros Pappas, Duncan Fyfe Gillies, Stephen Muggleton: Interpretation of Hidden Node Methodology in Automated Classification of Neural Cell Morphology. METMBS 2003: 527-532
2002
73EEStephen Muggleton: Learning Structure and Parameters of Stochastic Logic Programs. ILP 2002: 198-206
72EEAlireza Tamaddoni-Nezhad, Stephen Muggleton: A Genetic Algorithms Approach to ILP. ILP 2002: 285-300
71EEMarcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg: Generating Protein Three-dimensional Fold Signatures using Inductive Logic Programming. Computers & Chemistry 26(1): 57-64 (2002)
2001
70EEChristopher H. Bryant, Stephen Muggleton, Stephen G. Oliver, Douglas B. Kell, Philip G. K. Reiser, Ross D. King: Combining Inductive Logic Programming, Active Learning and Robotics to Discover the Function of Genes. Electron. Trans. Artif. Intell. 5(B): 1-36 (2001)
69EEPhilip G. K. Reiser, Ross D. King, Douglas B. Kell, Stephen Muggleton, Christopher H. Bryant, Stephen G. Oliver: Developing a Logical Model of Yeast Metabolism. Electron. Trans. Artif. Intell. 5(B): 223-244 (2001)
68EEA. P. Cootes, Stephen Muggleton, R. B. Greaves, Michael J. E. Sternberg: Automatic determination of protein fold signatures from structural superpositions. Electron. Trans. Artif. Intell. 5(B): 245-274 (2001)
67 Stephen Muggleton, Christopher H. Bryant, Ashwin Srinivasan, Alex Whittaker, Simon Topp, Christopher J. Rawlings: Are Grammatical Representations Useful for Learning from Biological Sequence Data? - A Case Study. Journal of Computational Biology 8(5): 493-521 (2001)
66 Marcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg: The Effect of Relational Background Knowledge on Learning of Protein Three-Dimensional Fold Signatures. Machine Learning 43(1/2): 81-95 (2001)
2000
65EEStephen Muggleton, Christopher H. Bryant, Ashwin Srinivasan: Measuring Performance when Positives Are Rare: Relative Advantage versus Predictive Accuracy - A Biological Case Study. ECML 2000: 300-312
64 Stephen Muggleton, Christopher H. Bryant, Ashwin Srinivasan: Learning Chomsky-like Grammars for Biological Sequence Families. ICML 2000: 631-638
63EEStephen Muggleton, Christopher H. Bryant: Theory Completion Using Inverse Entailment. ILP 2000: 130-146
62EEAlireza Tamaddoni-Nezhad, Stephen Muggleton: Searching the Subsumption Lattice by a Genetic Algorithm. ILP 2000: 243-252
61EEMarcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg: Use of Inductive Logic Programming to Learn Principles of Protein Structure. Electron. Trans. Artif. Intell. 4(B): 119-124 (2000)
60EEStephen Muggleton: Learning Stochastic Logic Programs. Electron. Trans. Artif. Intell. 4(B): 141-153 (2000)
1999
59 Koichi Furukawa, Donald Michie, Stephen Muggleton: Machine Intelligence 15, Intelligent Agents [St. Catherine's College, Oxford, July 1995] Oxford University Press 1999
58EEStephen Muggleton, Michael Bain: Analogical Prediction. ILP 1999: 234-244
57EERupert Parson, Khalid Khan, Stephen Muggleton: Theory Recovery. ILP 1999: 257-267
56EEStephen Muggleton: Inductive Logic Programming: Issues, Results and the Challenge of Learning Language in Logic. Artif. Intell. 114(1-2): 283-296 (1999)
55EEStephen Muggleton: Scientific Knowledge Discovery Using Inductive Logic Programming. Commun. ACM 42(11): 42-46 (1999)
54 Stephen Muggleton, David Page: Guest Editors' Introduction: Inductive Logic Programming. J. Log. Program. 40(2-3): 125-126 (1999)
1998
53EEStephen Muggleton, Ashwin Srinivasan, Ross D. King, Michael J. E. Sternberg: Biochemical Knowledge Discovery Using Inductive Logic Programming. Discovery Science 1998: 326-341
52EEStephen Muggleton: Knowledge Discovery in Biological and Chemical Domains. Discovery Science 1998: 58-59
51 Stephen Muggleton: Inductive Logic Programming: Issues, Results and the LLL Challenge (abstract). ECAI 1998: 697
50 Khalid Khan, Stephen Muggleton, Rupert Parson: Repeat Learning Using Predicate Invention. ILP 1998: 165-174
49 Stephen Muggleton: Completing Inverse Entailment. ILP 1998: 245-249
48 Saso Dzeroski, Nico Jacobs, Martín Molina, Carlos Moure, Stephen Muggleton, Wim Van Laer: Detecting Traffic Problems with ILP. ILP 1998: 281-290
47 Sam Roberts, Wim Van Laer, Nico Jacobs, Stephen Muggleton, Jeremy Broughton: A Comparison of ILP and Propositional Systems on Propositional Traffic Data. ILP 1998: 291-299
46 Marcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg: Application of Inductive Logic Programming to Discover Rules Governing the Three-Dimensional Topology of Protein Structure. ILP 1998: 53-64
45 Stephen Muggleton: Advances in ILP Theory and Implementations (Abstract). ILP 1998: 9
44 Paul W. Finn, Stephen Muggleton, David Page, Ashwin Srinivasan: Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL. Machine Learning 30(2-3): 241-270 (1998)
1997
43 Stephen Muggleton: Inductive Logic Programming, 6th International Workshop, ILP-96, Stockholm, Sweden, August 26-28, 1996, Selected Papers Springer 1997
42 Ashwin Srinivasan, Ross D. King, Stephen Muggleton, Michael J. E. Sternberg: The Predictive Toxicology Evaluation Challenge. IJCAI (1) 1997: 4-9
41 Stephen Moyle, Stephen Muggleton: Learning Programs in the Event Calculus. ILP 1997: 205-212
40 Ashwin Srinivasan, Ross D. King, Stephen Muggleton, Michael J. E. Sternberg: Carcinogenesis Predictions Using ILP. ILP 1997: 273-287
39EEStephen Muggleton, Donald Michie: Machine Intelligibility and the Duality Principle. Software Agents and Soft Computing 1997: 276-292
38 Stephen Muggleton, David Page: Guest Editors' Introduction. Machine Learning 26(2-3): 97-98 (1997)
1996
37 Stephen Muggleton, David Page, Ashwin Srinivasan: An Initial Experiment into Stereochemistry-Based Drug Design Using Inductive Logic Programming. Inductive Logic Programming Workshop 1996: 25-40
36 Stephen Muggleton: Learning from Positive Data. Inductive Logic Programming Workshop 1996: 358-376
35EEAshwin Srinivasan, Stephen Muggleton, Michael J. E. Sternberg, Ross D. King: Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction. Artif. Intell. 85(1-2): 277-299 (1996)
1995
34 Koichi Furukawa, Donald Michie, Stephen Muggleton: Machine Intelligence 14, Proceedings of the Fourteenth Machine Intelligence Workshop, held at Hitachi Advanced Research Laboratories, Tokyo, Japan, November 1993 Oxford University Press 1995
33 Stephen Muggleton: Inductive Logic Programming: Inverse Resolution and Beyond. IJCAI (1) 1995: 997
32 Rupert Parson, Stephen Muggleton: An Experiment with Browsers that Learn. Machine Intelligence 15 1995: 176-184
31 Stephen Muggleton, David Page: A Learnability Model for Universal Representations and Its Application to Top-down Induction of Decision Trees. Machine Intelligence 15 1995: 248-267
30 Michael J. E. Sternberg, Ross D. King, Ashwin Srinivasan, Stephen Muggleton: Drug Design by Machine Learning. Machine Intelligence 15 1995: 328-338
29 Ivan Bratko, Stephen Muggleton: Applications of Inductive Logic Programming. Commun. ACM 38(11): 65-70 (1995)
28 Stephen Muggleton, Fumio Mizoguchi, Koichi Furukawa: Special Issue on Inductive Logic Programming. New Generation Comput. 13(3&4): 243-244 (1995)
27 Stephen Muggleton: Inverse Entailment and Progol. New Generation Comput. 13(3&4): 245-286 (1995)
1994
26EEStephen Muggleton: Bayesian Inductive Logic Programming. COLT 1994: 3-11
25 Stephen Muggleton: Bayesian Inductive Logic Programming. ICML 1994: 371-379
24 Michael J. E. Sternberg, R. A. Lewis, Ross D. King, Stephen Muggleton: Machine Learning and biomolecular modelling. Machine Intelligence 13 1994: 193-212
23 Michael Bain, Stephen Muggleton: Learning optimal chess strategies. Machine Intelligence 13 1994: 291-309
22 Stephen Muggleton: Logic and Learning: Turing's legacy. Machine Intelligence 13 1994: 37-56
21 Ashwin Srinivasan, Stephen Muggleton, Michael Bain: The Justification of Logical Theories based on Data Compression. Machine Intelligence 13 1994: 87-121
20 Stephen Muggleton, Luc De Raedt: Inductive Logic Programming: Theory and Methods. J. Log. Program. 19/20: 629-679 (1994)
19 Stephen Muggleton: Inductive Logic Programming: Derivations, Successes and Shortcomings. SIGART Bulletin 5(1): 5-11 (1994)
1993
18 Stephen Muggleton: Optimal Layered Learning: A PAC Approach to Incremental Sampling. ALT 1993: 37-44
17EEStephen Muggleton: Inductive Logic Programming: Derivations, Successes and Shortcomings. ECML 1993: 21-37
16EESaso Dzeroski, Stephen Muggleton, Stuart J. Russell: Learnability of Constrained Logic Programs. ECML 1993: 342-347
15 Stephen Muggleton: Inverting Entailment and Progol. Machine Intelligence 14 1993: 135-190
1992
14EESaso Dzeroski, Stephen Muggleton, Stuart J. Russell: PAC-Learnability of Determinate Logic Programs. COLT 1992: 128-135
13 Stephen Muggleton: Developments in Inductive Logic Programming, Panel Position Paper. FGCS 1992: 1071-1073
12 Cao Feng, Stephen Muggleton: Towards Inductive Generalization in Higher Order Logic. ML 1992: 154-162
11 Stephen Muggleton, Ashwin Srinivasan, Michael Bain: Compression, Significance, and Accuracy. ML 1992: 338-347
1991
10EEPavel Brazdil, Stephen Muggleton: Learning to Relate Terms in a Multiple Agent Environment. EWSL 1991: 424-439
9 Ivan Bratko, Stephen Muggleton, Alen Varsek: Learning Qualitative Models of Dynamic Systems. ML 1991: 385-388
8 Stephen Muggleton: Inductive Logic Programming. New Generation Comput. 8(4): 295- (1991)
1990
7 Stephen Muggleton, Cao Feng: Efficient Induction of Logic Programs. ALT 1990: 368-381
6 Stephen Muggleton: Inductive Logic Programming. ALT 1990: 42-62
1989
5 Stephen Muggleton, Michael Bain, Jean Hayes Michie, Donald Michie: An Experimental Comparison of Human and Machine Learning Formalisms. ML 1989: 113-118
1988
4 Stephen Muggleton: A Strategy for Constructing New Predicates in First-Order Logic. EWSL 1988: 123-130
3 Stephen Muggleton, Wray L. Buntine: Machine Invention of First Order Predicates by Inverting Resolution. ML 1988: 339-352
1987
2 Stephen Muggleton: Structuring Knowledge by Asking Questions. EWSL 1987: 218-229
1 Stephen Muggleton: Duce, An Oracle-based Approach to Constructive Induction. IJCAI 1987: 287-292

Coauthor Index

1Ata Amini [84]
2Michael Bain [5] [11] [21] [23] [58]
3Jung-Wook Bang [74]
4Ivan Bratko [9] [29]
5Pavel Brazdil [10]
6Jeremy Broughton [47]
7Christopher H. Bryant [63] [64] [65] [67] [69] [70]
8Wray L. Buntine [3]
9Raphael Chaleil [86]
10Jianzhong Chen [89] [93] [94] [96] [102] [103]
11Simon Colton [75] [85] [99]
12A. P. Cootes [68]
13Thomas G. Dietterich [79] [80] [91] [92] [97] [108]
14Pedro Domingos [97]
15Saso Dzeroski [14] [16] [48]
16Cao Feng [7] [12]
17Andreas Fidjeland [106]
18Paul W. Finn [44]
19Paolo Frasconi [107]
20Koichi Furukawa [28] [34] [59]
21Lise Getoor [79] [80] [91] [92] [97] [108]
22Duncan Fyfe Gillies [74]
23R. B. Greaves [68]
24Nico Jacobs [47] [48]
25Antonis C. Kakas [77] [86]
26Douglas B. Kell [69] [70]
27Lawrence A. Kelley [89] [103]
28Kristian Kersting [92] [107] [108]
29Khalid Khan [50] [57]
30Ross D. King [24] [30] [35] [40] [42] [53] [69] [70]
31Wim Van Laer [47] [48]
32R. A. Lewis [24]
33Huma Lodhi [78] [81] [84] [109] [111]
34Wayne Luk [106]
35Donald Michie [5] [34] [39] [59]
36Jean Hayes Michie [5]
37Fumio Mizoguchi [28]
38Martín Molina [48]
39Carlos Moure [48]
40Stephen Moyle [41]
41Stephen G. Oliver [69] [70]
42Ramón P. Otero [95] [99]
43C. David Page Jr. (David Page) [31] [37] [38] [44] [54]
44Niels Pahlavi [88]
45Alexandros Pappas [74]
46Rupert Parson [32] [50] [57]
47Florencio Pazos [77]
48Luc De Raedt [20] [79] [80] [91] [92] [107] [108]
49Christopher J. Rawlings [67]
50Philip G. K. Reiser [69] [70]
51Sam Roberts [47]
52Stuart J. Russell [14] [16]
53Jose Santos (José Carlos Almeida Santos) [93] [94] [96] [105] [110]
54Ashwin Srinivasan [11] [21] [30] [35] [37] [40] [42] [44] [53] [64] [65] [67]
55Michael J. E. Sternberg [24] [30] [35] [40] [42] [46] [53] [61] [66] [68] [71] [84] [89] [103] [109] [111]
56Prasad Tadepalli [97]
57Alireza Tamaddoni-Nezhad [62] [72] [76] [77] [86] [87] [95] [98] [104] [105] [110]
58Simon Topp [67]
59Marcel Turcotte [46] [61] [66] [71]
60Alen Varsek [9]
61Hiroaki Watanabe [76] [82]
62Alex Whittaker [67]

Colors in the list of coauthors

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