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Michèle Sebag Vis

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*2009
94EEPhilippe Rolet, Michèle Sebag, Olivier Teytaud: Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm. ECML/PKDD (2) 2009: 302-317
93EEPhilippe Rolet, Michèle Sebag, Olivier Teytaud: Optimal robust expensive optimization is tractable. GECCO 2009: 1951-1956
92EEÁlvaro Fialho, Marc Schoenauer, Michèle Sebag: Analysis of adaptive operator selection techniques on the royal road and long k-path problems. GECCO 2009: 779-786
91EEÁlvaro Fialho, Luís Da Costa, Marc Schoenauer, Michèle Sebag: Extreme: dynamic multi-armed bandits for adaptive operator selection. GECCO (Companion) 2009: 2213-2216
90EEXiangliang Zhang, Cyril Furtlehner, Julien Perez, Cécile Germain-Renaud, Michèle Sebag: Toward autonomic grids: analyzing the job flow with affinity streaming. KDD 2009: 987-996
89EECyril Furtlehner, Michèle Sebag, Xiangliang Zhang: Scaling Analysis of Affinity Propagation CoRR abs/0910.1800: (2009)
2008
88EEXiangliang Zhang, Cyril Furtlehner, Michèle Sebag: Data Streaming with Affinity Propagation. ECML/PKDD (2) 2008: 628-643
87EELuís Da Costa, Álvaro Fialho, Marc Schoenauer, Michèle Sebag: Adaptive operator selection with dynamic multi-armed bandits. GECCO 2008: 913-920
86EEÁlvaro Fialho, Luís Da Costa, Marc Schoenauer, Michèle Sebag: Extreme Value Based Adaptive Operator Selection. PPSN 2008: 175-184
85 Xiangliang Zhang, Cyril Furtlehner, Michèle Sebag: Distributed and Incremental Clustering Based on Weighted Affinity Propagation. STAIRS 2008: 199-210
84EEAlexandre Termier, Marie-Christine Rousset, Michèle Sebag, Kouzou Ohara, Takashi Washio, Hiroshi Motoda: DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm. IEEE Trans. Knowl. Data Eng. 20(3): 300-320 (2008)
83EEAntoine Cornuéjols, Michèle Sebag: A note on phase transitions and computational pitfalls of learning from sequences. J. Intell. Inf. Syst. 31(2): 177-189 (2008)
2007
82EEChristian Gagné, Michèle Sebag, Marc Schoenauer, Marco Tomassini: Ensemble learning for free with evolutionary algorithms? GECCO 2007: 1782-1789
81EEXiangliang Zhang, Michèle Sebag, Cécile Germain: Toward Behavioral Modeling of a Grid System: Mining the Logging and Bookkeeping Files. ICDM Workshops 2007: 581-588
80EENicolas Baskiotis, Michèle Sebag, Marie-Claude Gaudel, Sandrine-Dominique Gouraud: A Machine Learning Approach for Statistical Software Testing. IJCAI 2007: 2274-2279
79EERomaric Gaudel, Michèle Sebag, Antoine Cornuéjols: A Phase Transition-Based Perspective on Multiple Instance Kernels. ILP 2007: 112-121
78EENicolas Baskiotis, Michèle Sebag: Structural Statistical Software Testing with Active Learning in a Graph. ILP 2007: 49-62
77EENicolas Baskiotis, Michèle Sebag: Structural Sampling for Statistical Software Testing. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007
76EEChristian Gagné, Michèle Sebag, Marc Schoenauer, Marco Tomassini: Ensemble Learning for Free with Evolutionary Algorithms ? CoRR abs/0704.3905: (2007)
75EENicolas Godzik, Marc Schoenauer, Michèle Sebag: Evolving Symbolic Controllers CoRR abs/0705.1244: (2007)
2006
74EEChristian Gagné, Marc Schoenauer, Michèle Sebag, Marco Tomassini: Genetic Programming for Kernel-Based Learning with Co-evolving Subsets Selection. PPSN 2006: 1008-1017
73EEVojtech Krmicek, Michèle Sebag: Functional Brain Imaging with Multi-objective Multi-modal Evolutionary Optimization. PPSN 2006: 382-391
72EEMarc Schoenauer, Michèle Sebag: Using Domain Knowledge in Evolutionary System Identification CoRR abs/cs/0602021: (2006)
71EEAlain Ratle, Michèle Sebag: Avoiding the Bloat with Stochastic Grammar-based Genetic Programming CoRR abs/cs/0602022: (2006)
70EEChristian Gagné, Marc Schoenauer, Michèle Sebag, Marco Tomassini: Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection CoRR abs/cs/0611135: (2006)
69EEVojtech Krmicek, Michèle Sebag: Functional Brain Imaging with Multi-Objective Multi-Modal Evolutionary Optimization CoRR abs/cs/0611138: (2006)
2005
68 Sylvain Gelly, Nicolas Bredeche, Michèle Sebag: HMM hiérarchiques et factorisés: mécanisme d'inférence et apprentissage à partir de peu de données. CAP 2005: 143-144
67 Nicolas Baskiotis, Michèle Sebag, Olivier Teytaud: Systèmes inductifs-déductifs: une approche statistique. CAP 2005: 145-146
66 Nicolas Tarrisson, Michèle Sebag, Olivier Teytaud, Julien Lefevre, Sylvain Baillet: Multi-objective Multi-modal Optimization for Mining Spatio-temporal Patterns. CAP 2005: 217-230
65 Nicolas Pernot, Antoine Cornuéjols, Michèle Sebag: Phase transitions in grammatical inference. CAP 2005: 49-60
64EEElena Marchiori, Michèle Sebag: Bayesian Learning with Local Support Vector Machines for Cancer Classification with Gene Expression Data. EvoWorkshops 2005: 74-83
63EEAlexandre Termier, Marie-Christine Rousset, Michèle Sebag, Kouzou Ohara, Takashi Washio, Hiroshi Motoda: Efficient Mining of High Branching Factor Attribute Trees. ICDM 2005: 785-788
62EENicolas Pernot, Antoine Cornuéjols, Michèle Sebag: Phase Transitions within Grammatical Inference. IJCAI 2005: 811-816
61EEMichèle Sebag, Nicolas Tarrisson, Olivier Teytaud, Julien Lefevre, Sylvain Baillet: A Multi-Objective Multi-Modal Optimization Approach for Mining Stable Spatio-Temporal Patterns. IJCAI 2005: 859-864
60EESylvain Gelly, Nicolas Bredeche, Michèle Sebag: From Factorial and Hierarchical HMM to Bayesian Network: A Representation Change Algorithm. SARA 2005: 107-120
59EEYann Semet, Sylvain Gelly, Marc Schoenauer, Michèle Sebag: Artificial Agents and Speculative Bubbles CoRR abs/cs/0511093: (2005)
58EEJérôme Azé, Mathieu Roche, Yves Kodratoff, Michèle Sebag: Preference Learning in Terminology Extraction: A ROC-based approach CoRR abs/cs/0512050: (2005)
2004
57EEAlexandre Termier, Marie-Christine Rousset, Michèle Sebag: DRYADE: A New Approach for Discovering Closed Frequent Trees in Heterogeneous Tree Databases. ICDM 2004: 543-546
56EENicolas Baskiotis, Michèle Sebag: C4.5 competence map: a phase transition-inspired approach. ICML 2004
55 Jérôme Azé, Mathieu Roche, Yves Kodratoff, Michèle Sebag: Learning to Order Terms: Supervised Interestingness Measures in Terminology Extraction International Conference on Computational Intelligence 2004: 478-481
54EEKees Jong, Jérémie Mary, Antoine Cornuéjols, Elena Marchiori, Michèle Sebag: Ensemble Feature Ranking. PKDD 2004: 267-278
53EEKees Jong, Elena Marchiori, Michèle Sebag: Ensemble Learning with Evolutionary Computation: Application to Feature Ranking. PPSN 2004: 1133-1142
52EENicolas Godzik, Marc Schoenauer, Michèle Sebag: Robotics and Multi-agent Systems Robustness in the Long Run: Auto-teaching vs Anticipation in Evolutionary Robotics. PPSN 2004: 932-941
51 Mathieu Roche, Jérôme Azé, Yves Kodratoff, Michèle Sebag: Learning Interestingness Measures in Terminology Extraction. A ROC-based approach. ROCAI 2004: 81-88
50EEJérôme Maloberti, Michèle Sebag: Fast Theta-Subsumption with Constraint Satisfaction Algorithms. Machine Learning 55(2): 137-174 (2004)
2003
49EEMichèle Sebag, Jérôme Azé, Noël Lucas: ROC-Based Evolutionary Learning: Application to Medical Data Mining. Artificial Evolution 2003: 384-396
48 Jérôme Azé, Noël Lucas, Michèle Sebag: Fouille de données visuelle et analyse de facteurs de risque médical. EGC 2003: 183-188
47 Sébastien Jouteau, Antoine Cornuéjols, Michèle Sebag, Philippe Tarroux, Jean-Sylvain Liénard: Nouveaux résultats en classification à l'aide d'un codage par motifs fréquents. EGC 2003: 521-532
46EENicolas Godzik, Marc Schoenauer, Michèle Sebag: Evolving Symbolic Controllers. EvoWorkshops 2003: 638-650
45EEMichèle Sebag, Jérôme Azé, Noël Lucas: Impact Studies and Sensitivity Analysis in Medical Data Mining with ROC-based Genetic Learning. ICDM 2003: 637-640
44EEMarco Botta, Attilio Giordana, Lorenza Saitta, Michèle Sebag: Relational Learning as Search in a Critical Region. Journal of Machine Learning Research 4: 431-463 (2003)
43EEHendrik Blockeel, Michèle Sebag: Scalability and efficiency in multi-relational data mining. SIGKDD Explorations 5(1): 17-30 (2003)
2002
42EEAlexandre Termier, Marie-Christine Rousset, Michèle Sebag: TreeFinder: a First Step towards XML Data Mining. ICDM 2002: 450-457
41 Jacques Ales Bianchetti, Céline Rouveirol, Michèle Sebag: Constraint-based Learning of Long Relational Concepts. ICML 2002: 35-42
40EEAlain Ratle, Michèle Sebag: A Novel Approach to Machine Discovery: Genetic Programming and Stochastic Grammars. ILP 2002: 207-222
39 Hatem Hamda, François Jouve, Evelyne Lutton, Marc Schoenauer, Michèle Sebag: Compact Unstructured Representations for Evolutionary Design. Appl. Intell. 16(2): 139-155 (2002)
2001
38 Céline Rouveirol, Michèle Sebag: Inductive Logic Programming, 11th International Conference, ILP 2001, Strasbourg, France, September 9-11, 2001, Proceedings Springer 2001
37EEAlain Ratle, Michèle Sebag: Avoiding the Bloat with Stochastic Grammar-Based Genetic Programming. Artificial Evolution 2001: 255-266
36EEJérôme Maloberti, Michèle Sebag: Theta-Subsumption in a Constraint Satisfaction Perspective. ILP 2001: 164-178
35EEAlexandre Termier, Michèle Sebag, Marie-Christine Rousset: Combining Statistics and Semantics for Word and Document Clustering. Workshop on Ontology Learning 2001
34EEAlain Ratle, Michèle Sebag: Grammar-guided genetic programming and dimensional consistency: application to non-parametric identification in mechanics. Appl. Soft Comput. 1(1): 105-118 (2001)
2000
33 Attilio Giordana, Lorenza Saitta, Michèle Sebag, Marco Botta: Analyzing Relational Learning in the Phase Transition Framework. ICML 2000: 311-318
32EEAttilio Giordana, Lorenza Saitta, Michèle Sebag, Marco Botta: Can Relational Learning Scale Up? ISMIS 2000: 31-39
31EEAlain Ratle, Michèle Sebag: Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery. PPSN 2000: 211-220
30 Michèle Sebag, Céline Rouveirol: Any-time Relational Reasoning: Resource-bounded Induction and Deduction Through Stochastic Matching. Machine Learning 38(1-2): 41-62 (2000)
1999
29EEMarco Botta, Attilio Giordana, Lorenza Saitta, Michèle Sebag: Relational Learning: Hard Problems and Phase Transitions. AI*IA 1999: 178-189
28EEMichèle Sebag: From first order logic to Nd: a data driven reformulation. ESANN 1999: 231-236
27 Michèle Sebag: Constructive Induction: A Version Space-based Approach. IJCAI 1999: 708-713
26EEAlejandro Rosete-Suárez, Alberto Nogueira-Keeling, Alberto Ochoa-Rodríguez, Michèle Sebag: Hacia un Enfoque General del Trazado de Grafos. Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 8: 18-26 (1999)
1998
25EEAntoine Ducoulombier, Michèle Sebag: Continuous Mimetic Evolution. ECML 1998: 334-345
24 Michèle Sebag: A Stochastic Simple Similarity. ILP 1998: 95-105
23EEMichèle Sebag, Antoine Ducoulombier: Extending Population-Based Incremental Learning to Continuous Search Spaces. PPSN 1998: 418-427
22 Michèle Sebag, Marc Schoenauer, Mathieu Peyral: Revisiting the Memory of Evolution. Fundam. Inform. 35(1-4): 125-162 (1998)
21 Olivier Gascuel, Bernadette Bouchon-Meunier, Gilles Caraux, Patrick Gallinari, Alain Guénoche, Yann Guermeur, Yves Lechevallier, Christophe Marsala, Laurent Miclet, Jacques Nicolas, Richard Nock, Mohammed Ramdani, Michèle Sebag, Basavanneppa Tallur, Gilles Venturini, Patrick Vitte: Twelve Numerical, Symbolic and Hybrid Supervised Classification Methods. IJPRAI 12(4): 517-571 (1998)
1997
20EEMathieu Peyral, Antoine Ducoulombier, Caroline Ravise, Marc Schoenauer, Michèle Sebag: Mimetic Evolution. Artificial Evolution 1997: 81-94
19 Michèle Sebag, Marc Schoenauer, Caroline Ravise: Inductive Learning of Mutation Step-Size in Evolutionary Parameter Optimization. Evolutionary Programming 1997: 247-261
18 Michèle Sebag, Marc Schoenauer, Caroline Ravise: Toward Civilized Evolution: Developing Inhibitions. ICGA 1997: 291-298
17 Michèle Sebag, Céline Rouveirol: Tractable Induction and Classification in First Order Logic Via Stochastic Matching. IJCAI (2) 1997: 888-893
16 Michèle Sebag: Distance Induction in First Order Logic. ILP 1997: 264-272
1996
15 Michèle Sebag, Caroline Ravise, Marc Schoenauer: Controlling Evolution by Means of Machine Learning. Evolutionary Programming 1996: 57-66
14 Caroline Ravise, Michèle Sebag: An Advanced Evolution Should Not Repeat its Past Errors. ICML 1996: 400-408
13 Michèle Sebag: Delaying the Choice of Bias: A Disjunctive Version Space Approach. ICML 1996: 444-452
12 Michèle Sebag, Céline Rouveirol: Polynomial-Time Learning in Logic Programming and Constraint Logic Programming. Inductive Logic Programming Workshop 1996: 105-126
11EEMichèle Sebag, Marc Schoenauer: Mutation by Imitation in Boolean Evolution Strategies. PPSN 1996: 356-365
10EEMichèle Sebag, Céline Rouveirol, Jean-Francois Puget: Induction of Constraint Logic Programs. PRICAI Workshops 1996: 148-167
1995
9 Caroline Ravise, Michèle Sebag, Marc Schoenauer: Induction-Based Control of Genetic Algorithms. Artificial Evolution 1995: 100-119
8EEMichèle Sebag, Marc Schoenauer, Caroline Ravise: An Induction-based Control for Genetic Algorithms (Extended Abstract). ECML 1995: 351-355
1994
7EEMichèle Sebag: Using Constraints to Building Version Spaces. ECML 1994: 257-271
6 Michèle Sebag: A Constraint-based Induction Algorithm in FOL. ICML 1994: 275-283
5EEMichèle Sebag, Marc Schoenauer: Controlling Crossover through Inductive Learning. PPSN 1994: 209-218
1993
4 Michèle Sebag, Marc Schoenauer: A Rule-Based Similarity Measure. EWCBR 1993: 119-131
1992
3 Michèle Sebag, Marc Schoenauer: Learning to Control Inconsistent Knowledge. ECAI 1992: 479-483
1991
2 Michèle Sebag, Marc Schoenauer: Using Examples to Refine a Redundant Knowledge Base. EUROVAV 1991: 227-236
1990
1 Marc Schoenauer, Michèle Sebag: Incremental Learning of Rules and Meta-rules. ML 1990: 49-57

Coauthor Index

1Jérôme Azé [45] [48] [49] [51] [55] [58]
2Sylvain Baillet [61] [66]
3Nicolas Baskiotis [56] [67] [77] [78] [80]
4Jacques Ales Bianchetti [41]
5Hendrik Blockeel [43]
6Marco Botta [29] [32] [33] [44]
7Bernadette Bouchon-Meunier (Bernadette Bouchon) [21]
8Nicolas Bredeche [60] [68]
9Gilles Caraux [21]
10Antoine Cornuéjols [47] [54] [62] [65] [79] [83]
11Luís Da Costa [86] [87] [91]
12Antoine Ducoulombier [20] [23] [25]
13Álvaro Fialho [86] [87] [91] [92]
14Cyril Furtlehner [85] [88] [89] [90]
15Christian Gagné [70] [74] [76] [82]
16Patrick Gallinari [21]
17Olivier Gascuel [21]
18Marie-Claude Gaudel [80]
19Romaric Gaudel [79]
20Sylvain Gelly [59] [60] [68]
21Cécile Germain-Renaud (Cécile Germain) [81] [90]
22Attilio Giordana [29] [32] [33] [44]
23Nicolas Godzik [46] [52] [75]
24Sandrine-Dominique Gouraud [80]
25Alain Guénoche (A. Guénoche) [21]
26Yann Guermeur [21]
27Hatem Hamda [39]
28Kees Jong [53] [54]
29Sébastien Jouteau [47]
30François Jouve [39]
31Yves Kodratoff [51] [55] [58]
32Vojtech Krmicek [69] [73]
33Yves Lechevallier [21]
34Julien Lefevre [61] [66]
35Jean-Sylvain Liénard [47]
36Noël Lucas [45] [48] [49]
37Evelyne Lutton [39]
38Jérôme Maloberti [36] [50]
39Elena Marchiori [53] [54] [64]
40Christophe Marsala [21]
41Jérémie Mary [54]
42Laurent Miclet [21]
43Hiroshi Motoda [63] [84]
44Jacques Nicolas [21]
45Richard Nock [21]
46Alberto Nogueira-Keeling [26]
47Alberto Ochoa-Rodríguez [26]
48Kouzou Ohara [63] [84]
49Julien Perez [90]
50Nicolas Pernot [62] [65]
51Mathieu Peyral [20] [22]
52Jean-François Puget (Jean-Francois Puget) [10]
53Mohammed Ramdani [21]
54Alain Ratle [31] [34] [37] [40] [71]
55Caroline Ravise [8] [9] [14] [15] [18] [19] [20]
56Mathieu Roche [51] [55] [58]
57Philippe Rolet [93] [94]
58Alejandro Rosete-Suárez [26]
59Marie-Christine Rousset [35] [42] [57] [63] [84]
60Céline Rouveirol [10] [12] [17] [30] [38] [41]
61Lorenza Saitta [29] [32] [33] [44]
62Marc Schoenauer [1] [2] [3] [4] [5] [8] [9] [11] [15] [18] [19] [20] [22] [39] [46] [52] [59] [70] [72] [74] [75] [76] [82] [86] [87] [91] [92]
63Yann Semet [59]
64Basavanneppa Tallur [21]
65Nicolas Tarrisson [61] [66]
66Philippe Tarroux [47]
67Alexandre Termier [35] [42] [57] [63] [84]
68Olivier Teytaud [61] [66] [67] [93] [94]
69Marco Tomassini [70] [74] [76] [82]
70Gilles Venturini [21]
71Patrick Vitte [21]
72Takashi Washio [63] [84]
73Xiangliang Zhang [81] [85] [88] [89] [90]

Colors in the list of coauthors

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