| 2009 | ||
|---|---|---|
| 94 | Philippe Rolet, Michèle Sebag, Olivier Teytaud: Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm. ECML/PKDD (2) 2009: 302-317 | |
| 93 | Philippe Rolet, Michèle Sebag, Olivier Teytaud: Optimal robust expensive optimization is tractable. GECCO 2009: 1951-1956 | |
| 92 | Álvaro Fialho, Marc Schoenauer, Michèle Sebag: Analysis of adaptive operator selection techniques on the royal road and long k-path problems. GECCO 2009: 779-786 | |
| 91 | Álvaro Fialho, Luís Da Costa, Marc Schoenauer, Michèle Sebag: Extreme: dynamic multi-armed bandits for adaptive operator selection. GECCO (Companion) 2009: 2213-2216 | |
| 90 | Xiangliang Zhang, Cyril Furtlehner, Julien Perez, Cécile Germain-Renaud, Michèle Sebag: Toward autonomic grids: analyzing the job flow with affinity streaming. KDD 2009: 987-996 | |
| 89 | Cyril Furtlehner, Michèle Sebag, Xiangliang Zhang: Scaling Analysis of Affinity Propagation CoRR abs/0910.1800: (2009) | |
| 2008 | ||
| 88 | Xiangliang Zhang, Cyril Furtlehner, Michèle Sebag: Data Streaming with Affinity Propagation. ECML/PKDD (2) 2008: 628-643 | |
| 87 | Luís Da Costa, Álvaro Fialho, Marc Schoenauer, Michèle Sebag: Adaptive operator selection with dynamic multi-armed bandits. GECCO 2008: 913-920 | |
| 86 | Álvaro 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 | |
| 84 | Alexandre 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) | |
| 83 | Antoine 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 | ||
| 82 | Christian Gagné, Michèle Sebag, Marc Schoenauer, Marco Tomassini: Ensemble learning for free with evolutionary algorithms? GECCO 2007: 1782-1789 | |
| 81 | Xiangliang Zhang, Michèle Sebag, Cécile Germain: Toward Behavioral Modeling of a Grid System: Mining the Logging and Bookkeeping Files. ICDM Workshops 2007: 581-588 | |
| 80 | Nicolas Baskiotis, Michèle Sebag, Marie-Claude Gaudel, Sandrine-Dominique Gouraud: A Machine Learning Approach for Statistical Software Testing. IJCAI 2007: 2274-2279 | |
| 79 | Romaric Gaudel, Michèle Sebag, Antoine Cornuéjols: A Phase Transition-Based Perspective on Multiple Instance Kernels. ILP 2007: 112-121 | |
| 78 | Nicolas Baskiotis, Michèle Sebag: Structural Statistical Software Testing with Active Learning in a Graph. ILP 2007: 49-62 | |
| 77 | Nicolas Baskiotis, Michèle Sebag: Structural Sampling for Statistical Software Testing. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007 | |
| 76 | Christian Gagné, Michèle Sebag, Marc Schoenauer, Marco Tomassini: Ensemble Learning for Free with Evolutionary Algorithms ? CoRR abs/0704.3905: (2007) | |
| 75 | Nicolas Godzik, Marc Schoenauer, Michèle Sebag: Evolving Symbolic Controllers CoRR abs/0705.1244: (2007) | |
| 2006 | ||
| 74 | Christian Gagné, Marc Schoenauer, Michèle Sebag, Marco Tomassini: Genetic Programming for Kernel-Based Learning with Co-evolving Subsets Selection. PPSN 2006: 1008-1017 | |
| 73 | Vojtech Krmicek, Michèle Sebag: Functional Brain Imaging with Multi-objective Multi-modal Evolutionary Optimization. PPSN 2006: 382-391 | |
| 72 | Marc Schoenauer, Michèle Sebag: Using Domain Knowledge in Evolutionary System Identification CoRR abs/cs/0602021: (2006) | |
| 71 | Alain Ratle, Michèle Sebag: Avoiding the Bloat with Stochastic Grammar-based Genetic Programming CoRR abs/cs/0602022: (2006) | |
| 70 | Christian Gagné, Marc Schoenauer, Michèle Sebag, Marco Tomassini: Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection CoRR abs/cs/0611135: (2006) | |
| 69 | Vojtech 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 | |
| 64 | Elena Marchiori, Michèle Sebag: Bayesian Learning with Local Support Vector Machines for Cancer Classification with Gene Expression Data. EvoWorkshops 2005: 74-83 | |
| 63 | Alexandre Termier, Marie-Christine Rousset, Michèle Sebag, Kouzou Ohara, Takashi Washio, Hiroshi Motoda: Efficient Mining of High Branching Factor Attribute Trees. ICDM 2005: 785-788 | |
| 62 | Nicolas Pernot, Antoine Cornuéjols, Michèle Sebag: Phase Transitions within Grammatical Inference. IJCAI 2005: 811-816 | |
| 61 | Michèle 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 | |
| 60 | Sylvain Gelly, Nicolas Bredeche, Michèle Sebag: From Factorial and Hierarchical HMM to Bayesian Network: A Representation Change Algorithm. SARA 2005: 107-120 | |
| 59 | Yann Semet, Sylvain Gelly, Marc Schoenauer, Michèle Sebag: Artificial Agents and Speculative Bubbles CoRR abs/cs/0511093: (2005) | |
| 58 | Jérôme Azé, Mathieu Roche, Yves Kodratoff, Michèle Sebag: Preference Learning in Terminology Extraction: A ROC-based approach CoRR abs/cs/0512050: (2005) | |
| 2004 | ||
| 57 | Alexandre Termier, Marie-Christine Rousset, Michèle Sebag: DRYADE: A New Approach for Discovering Closed Frequent Trees in Heterogeneous Tree Databases. ICDM 2004: 543-546 | |
| 56 | Nicolas 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 | |
| 54 | Kees Jong, Jérémie Mary, Antoine Cornuéjols, Elena Marchiori, Michèle Sebag: Ensemble Feature Ranking. PKDD 2004: 267-278 | |
| 53 | Kees Jong, Elena Marchiori, Michèle Sebag: Ensemble Learning with Evolutionary Computation: Application to Feature Ranking. PPSN 2004: 1133-1142 | |
| 52 | Nicolas 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 | |
| 50 | Jérôme Maloberti, Michèle Sebag: Fast Theta-Subsumption with Constraint Satisfaction Algorithms. Machine Learning 55(2): 137-174 (2004) | |
| 2003 | ||
| 49 | Michèle 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 | |
| 46 | Nicolas Godzik, Marc Schoenauer, Michèle Sebag: Evolving Symbolic Controllers. EvoWorkshops 2003: 638-650 | |
| 45 | Michèle Sebag, Jérôme Azé, Noël Lucas: Impact Studies and Sensitivity Analysis in Medical Data Mining with ROC-based Genetic Learning. ICDM 2003: 637-640 | |
| 44 | Marco Botta, Attilio Giordana, Lorenza Saitta, Michèle Sebag: Relational Learning as Search in a Critical Region. Journal of Machine Learning Research 4: 431-463 (2003) | |
| 43 | Hendrik Blockeel, Michèle Sebag: Scalability and efficiency in multi-relational data mining. SIGKDD Explorations 5(1): 17-30 (2003) | |
| 2002 | ||
| 42 | Alexandre 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 | |
| 40 | Alain 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 | |
| 37 | Alain Ratle, Michèle Sebag: Avoiding the Bloat with Stochastic Grammar-Based Genetic Programming. Artificial Evolution 2001: 255-266 | |
| 36 | Jérôme Maloberti, Michèle Sebag: Theta-Subsumption in a Constraint Satisfaction Perspective. ILP 2001: 164-178 | |
| 35 | Alexandre Termier, Michèle Sebag, Marie-Christine Rousset: Combining Statistics and Semantics for Word and Document Clustering. Workshop on Ontology Learning 2001 | |
| 34 | Alain 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 | |
| 32 | Attilio Giordana, Lorenza Saitta, Michèle Sebag, Marco Botta: Can Relational Learning Scale Up? ISMIS 2000: 31-39 | |
| 31 | Alain 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 | ||
| 29 | Marco Botta, Attilio Giordana, Lorenza Saitta, Michèle Sebag: Relational Learning: Hard Problems and Phase Transitions. AI*IA 1999: 178-189 | |
| 28 | Michèle 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 | |
| 26 | Alejandro 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 | ||
| 25 | Antoine Ducoulombier, Michèle Sebag: Continuous Mimetic Evolution. ECML 1998: 334-345 | |
| 24 | Michèle Sebag: A Stochastic Simple Similarity. ILP 1998: 95-105 | |
| 23 | Michèle 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 | ||
| 20 | Mathieu 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 | |
| 11 | Michèle Sebag, Marc Schoenauer: Mutation by Imitation in Boolean Evolution Strategies. PPSN 1996: 356-365 | |
| 10 | Michèle 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 | |
| 8 | Michèle Sebag, Marc Schoenauer, Caroline Ravise: An Induction-based Control for Genetic Algorithms (Extended Abstract). ECML 1995: 351-355 | |
| 1994 | ||
| 7 | Michèle 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 | |
| 5 | Michèle 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 | |