Michèle Sebag

Affiliations:
  • University of Paris-Sud, Laboratory for Computer Science (LRI), France


According to our database1, Michèle Sebag authored at least 211 papers between 1990 and 2023.

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Bibliography

2023
GAN-based data augmentation for transcriptomics: survey and comparative assessment.
Bioinform., 2023

Toward Job Recommendation for All.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

RECTO : REcommandation diminuant la Congestion par Transport Optimal.
Proceedings of the 9ème Conférence Nationale sur les Applications Pratiques de l'Intelligence Artificielle, 2023

Fairness in job recommendations: estimating, explaining, and reducing gender gaps.
Proceedings of the 1st Workshop on Fairness and Bias in AI co-located with 26th European Conference on Artificial Intelligence (ECAI 2023), 2023

2022
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs.
J. Mach. Learn. Res., 2022

High-Dimensional Causal Discovery: Learning from Inverse Covariance via Independence-based Decomposition.
CoRR, 2022

From Graphs to DAGs: A Low-Complexity Model and a Scalable Algorithm.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Learning meta-features for AutoML.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Frugal Machine Learning.
CoRR, 2021

Boltzmann Tuning of Generative Models.
CoRR, 2021

Cartolabe: A Web-Based Scalable Visualization of Large Document Collections.
IEEE Computer Graphics and Applications, 2021

On the Identifiability of Hierarchical Decision Models.
Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021

Iterative Learning for Model Reactive Control: Application to Autonomous Multi-agent Control.
Proceedings of the 7th International Conference on Automation, Robotics and Applications, 2021

I2SL: Learn How to Swarm Autonomous Quadrotors Using Iterative Imitation Supervised Learning.
Proceedings of the Progress in Artificial Intelligence, 2021

Important Topics in Causal Analysis: Summary of the CAWS 2021 Round Table Discussion.
Proceedings of the Causal Analysis Workshop Series, 2021

Towards causal modeling of nutritional outcomes.
Proceedings of the Causal Analysis Workshop Series, 2021

2020
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities.
Frontiers Big Data, 2020

Distribution-Based Invariant Deep Networks for Learning Meta-Features.
CoRR, 2020

Variational Auto-Encoder: not all failures are equal.
CoRR, 2020

Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Dynamic Time Lag Regression: Predicting What & When.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Towards AutoML in the presence of Drift: first results.
CoRR, 2019

Automated Machine Learning with Monte-Carlo Tree Search (Extended Version).
CoRR, 2019

Agnostic Feature Selection.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

From Abstract Items to Latent Spaces to Observed Data and Back: Compositional Variational Auto-Encoder.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Automated Machine Learning with Monte-Carlo Tree Search.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Multi-Domain Adversarial Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Discriminant Learning Machines.
Proceedings of the Cause Effect Pairs in Machine Learning, 2019

Analysis of the AutoML Challenge Series 2015-2018.
Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

Learning Bivariate Functional Causal Models.
Proceedings of the Cause Effect Pairs in Machine Learning, 2019

2018
ActivMetal: Algorithm Recommendation with Active Meta Learning.
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning (ECML 2018) and Principles and Practice of Knowledge Discovery in Databases (PKDD 2018), 2018

2017
Nonstandard Criteria in Evolutionary Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Phase Transitions in Machine Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Grammatical Inference.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations.
Signal Process., 2017

Stochastic Gradient Descent: Going As Fast As Possible But Not Faster.
CoRR, 2017

Toward Optimal Run Racing: Application to Deep Learning Calibration.
CoRR, 2017

Alors: An algorithm recommender system.
Artif. Intell., 2017

ASAP.V2 and ASAP.V3: Sequential optimization of an Algorithm Selector and a Scheduler.
Proceedings of the Open Algorithm Selection Challenge 2017, 2017

Language Modelling for Collaborative Filtering: Application to Job Applicant Matching.
Proceedings of the 29th IEEE International Conference on Tools with Artificial Intelligence, 2017

2016
Anti Imitation-Based Policy Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention.
Proceedings of the 2016 Workshop on Automatic Machine Learning, 2016

Matching Jobs and Resumes: a Deep Collaborative Filtering Task.
Proceedings of the GCAI 2016. 2nd Global Conference on Artificial Intelligence, September 19, 2016

2015
Interactive Metric Learning-Based Visual Data Exploration: Application to the Visualization of a Scientific Social Network.
Proceedings of the Information Search, Integration, and Personalization, 2015

Collaborative Algorithm Platforms.
Proceedings of the DATA 2015, 2015

2014
Learning Sparse Features with an Auto-Associator.
Proceedings of the Growing Adaptive Machines, 2014

Data Stream Clustering With Affinity Propagation.
IEEE Trans. Knowl. Data Eng., 2014

Strategic Choices in Optimization.
J. Inf. Sci. Eng., 2014

Constraints, Optimization and Data (Dagstuhl Seminar 14411).
Dagstuhl Reports, 2014

Exploration vs Exploitation vs Safety: Risk-averse Multi-Armed Bandits.
CoRR, 2014

A tour of machine learning: An AI perspective.
AI Commun., 2014

Coupling Evolution and Information Theory for Autonomous Robotic Exploration.
Proceedings of the Parallel Problem Solving from Nature - PPSN XIII, 2014

Maximum Likelihood-Based Online Adaptation of Hyper-Parameters in CMA-ES.
Proceedings of the Parallel Problem Solving from Nature - PPSN XIII, 2014

Experimental Design in Dynamical System Identification: A Bandit-Based Active Learning Approach.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Combination of One-Class Support Vector Machines for Classification with Reject Option.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Programming by Feedback.
Proceedings of the 31th International Conference on Machine Learning, 2014

A Recommender System for Process Discovery.
Proceedings of the Business Process Management - 12th International Conference, 2014

2013
Hypervolume indicator and dominance reward based multi-objective Monte-Carlo Tree Search.
Mach. Learn., 2013

KL-based Control of the Learning Schedule for Surrogate Black-Box Optimization.
CoRR, 2013

Hybridizing Constraint Programming and Monte-Carlo Tree Search: Application to the Job Shop Problem.
Proceedings of the Learning and Intelligent Optimization - 7th International Conference, 2013

Collaborative hyperparameter tuning.
Proceedings of the 30th International Conference on Machine Learning, 2013

Multi-dimensional sparse structured signal approximation using split bregman iterations.
Proceedings of the IEEE International Conference on Acoustics, 2013

Sustainable cooperative coevolution with a multi-armed bandit.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Bi-population CMA-ES agorithms with surrogate models and line searches.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Intensive surrogate model exploitation in self-adaptive surrogate-assisted cma-es (saacm-es).
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Bandit-Based Search for Constraint Programming.
Proceedings of the Principles and Practice of Constraint Programming, 2013

Fast Adaptive Object Detection towards a Smart Environment by a Mobile Robot.
Proceedings of the Ambient Intelligence - 4th International Joint Conference, 2013

Exploration vs Exploitation vs Safety: Risk-Aware Multi-Armed Bandits.
Proceedings of the Asian Conference on Machine Learning, 2013

2012
Multi-objective Monte-Carlo Tree Search.
Proceedings of the 4th Asian Conference on Machine Learning, 2012

The grand challenge of computer Go: Monte Carlo tree search and extensions.
Commun. ACM, 2012

Alternative Restart Strategies for CMA-ES.
Proceedings of the Parallel Problem Solving from Nature - PPSN XII, 2012

APRIL: Active Preference Learning-Based Reinforcement Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Upper Confidence Tree-Based Consistent Reactive Planning Application to MineSweeper.
Proceedings of the Learning and Intelligent Optimization - 6th International Conference, 2012

Pilot, Rollout and Monte Carlo Tree Search Methods for Job Shop Scheduling.
Proceedings of the Learning and Intelligent Optimization - 6th International Conference, 2012

BenchNN: On the broad potential application scope of hardware neural network accelerators.
Proceedings of the 2012 IEEE International Symposium on Workload Characterization, 2012

Black-box optimization benchmarking of NIPOP-aCMA-ES and NBIPOP-aCMA-ES on the BBOB-2012 noiseless testbed.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Black-box optimization benchmarking of IPOP-saACM-ES on the BBOB-2012 noisy testbed.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Black-box optimization benchmarking of IPOP-saACM-ES and BIPOP-saACM-ES on the BBOB-2012 noiseless testbed.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Self-adaptive surrogate-assisted covariance matrix adaptation evolution strategy.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

Adaptive Operator Selection and Management in Evolutionary Algorithms.
Proceedings of the Autonomous Search, 2012

Continuous Search in Constraint Programming.
Proceedings of the Autonomous Search, 2012

2011
Continuous RAVE.
Proceedings of the 3rd Asian Conference on Machine Learning, 2011

Single trial variability in brain-computer interfaces based on motor imagery: Learning in the presence of labeling noise.
Int. J. Imaging Syst. Technol., 2011

Towards Non-Stationary Grid Models.
J. Grid Comput., 2011

Preference-Based Policy Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Using SVM to Avoid Humans: A Case of a Small Autonomous Mobile Robot in an Office.
Proceedings of the Computer and Information Sciences II, 2011

Characterizing Anomalous Behaviors and Revising Robotic Controllers.
Proceedings of the Data Mining Workshops (ICDMW), 2011

On-Board Evolutionary Algorithm and Off-Line Rule Discovery for Column Formation in Swarm Robotics.
Proceedings of the 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2011

Adaptive coordinate descent.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Not All Parents Are Equal for MO-CMA-ES.
Proceedings of the Evolutionary Multi-Criterion Optimization, 2011

Emergence of temporal and spatial synchronous behaviors in a foraging swarm.
Proceedings of the Advances in Artificial Life: 20th Anniversary Edition, 2011

The Grid Observatory.
Proceedings of the 11th IEEE/ACM International Symposium on Cluster, 2011

2010
Nonstandard Criteria in Evolutionary Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Phase Transitions in Machine Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Grammatical Inference.
Proceedings of the Encyclopedia of Machine Learning, 2010

Special issue for ECML PKDD 2010: Guest editors' introduction.
Mach. Learn., 2010

Guest editors' introduction: special issue of selected papers from ECML PKDD 2010.
Data Min. Knowl. Discov., 2010

Analyzing bandit-based adaptive operator selection mechanisms.
Ann. Math. Artif. Intell., 2010

Dominance-Based Pareto-Surrogate for Multi-Objective Optimization.
Proceedings of the Simulated Evolution and Learning - 8th International Conference, 2010

Comparison-Based Optimizers Need Comparison-Based Surrogates.
Proceedings of the Parallel Problem Solving from Nature, 2010

Comparison-Based Adaptive Strategy Selection with Bandits in Differential Evolution.
Proceedings of the Parallel Problem Solving from Nature, 2010

Open-Ended Evolutionary Robotics: An Information Theoretic Approach.
Proceedings of the Parallel Problem Solving from Nature, 2010

SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Continuous Search in Constraint Programming.
Proceedings of the 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010

Feature Selection as a One-Player Game.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Building Portfolios for the Protein Structure Prediction Problem.
Proceedings of the Workshop on Constraint Based Methods for Bioinformatics, 2010

K-AP: Generating Specified K Clusters by Efficient Affinity Propagation.
Proceedings of the ICDM 2010, 2010

Adaptively detecting changes in Autonomic Grid Computing.
Proceedings of the 2010 11th IEEE/ACM International Conference on Grid Computing, 2010

A pareto-compliant surrogate approach for multiobjective optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

A mono surrogate for multiobjective optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Fitness-AUC bandit adaptive strategy selection vs. the probability matching one within differential evolution: an empirical comparison on the bbob-2010 noiseless testbed.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Toward comparison-based adaptive operator selection.
Proceedings of the Genetic and Evolutionary Computation Conference, 2010

Unsupervised Layer-Wise Model Selection in Deep Neural Networks.
Proceedings of the ECAI 2010, 2010

Discovering Piecewise Linear Models of Grid Workload.
Proceedings of the 10th IEEE/ACM International Conference on Cluster, 2010

2009
Scaling Analysis of Affinity Propagation
CoRR, 2009

Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Dynamic Multi-Armed Bandits and Extreme Value-Based Rewards for Adaptive Operator Selection in Evolutionary Algorithms.
Proceedings of the Learning and Intelligent Optimization, Third International Conference, 2009

Toward autonomic grids: analyzing the job flow with affinity streaming.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Optimal robust expensive optimization is tractable.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

Analysis of adaptive operator selection techniques on the royal road and long k-path problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

Extreme: dynamic multi-armed bandits for adaptive operator selection.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

Extreme compass and Dynamic Multi-Armed Bandits for Adaptive Operator Selection.
Proceedings of the IEEE Congress on Evolutionary Computation, 2009

Memory-enhanced Evolutionary Robotics: The Echo State Network Approach.
Proceedings of the IEEE Congress on Evolutionary Computation, 2009

Multi-scale Real-Time Grid Monitoring with Job Stream Mining.
Proceedings of the 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, 2009

2008
DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm.
IEEE Trans. Knowl. Data Eng., 2008

A note on phase transitions and computational pitfalls of learning from sequences.
J. Intell. Inf. Syst., 2008

Distributed and Incremental Clustering Based on Weighted Affinity Propagation.
Proceedings of the STAIRS 2008, 2008

Extreme Value Based Adaptive Operator Selection.
Proceedings of the Parallel Problem Solving from Nature, 2008

Data Streaming with Affinity Propagation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Adaptive operator selection with dynamic multi-armed bandits.
Proceedings of the Genetic and Evolutionary Computation Conference, 2008

SoftwareTesting with Active Learning in a Graph.
Proceedings of the Evolutionary Test Generation, 24.08. - 29.08.2008, 2008

2007
A Phase Transition-Based Perspective on Multiple Instance Kernels.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

Structural Statistical Software Testing with Active Learning in a Graph.
Proceedings of the Inductive Logic Programming, 17th International Conference, 2007

A Machine Learning Approach for Statistical Software Testing.
Proceedings of the IJCAI 2007, 2007

Toward Behavioral Modeling of a Grid System: Mining the Logging and Bookkeeping Files.
Proceedings of the Workshops Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

Ensemble learning for free with evolutionary algorithms?
Proceedings of the Genetic and Evolutionary Computation Conference, 2007

Structural Sampling for Statistical Software Testing.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

2006
Using Domain Knowledge in Evolutionary System Identification
CoRR, 2006

Functional Brain Imaging with Multi-objective Multi-modal Evolutionary Optimization.
Proceedings of the Parallel Problem Solving from Nature, 2006

Genetic Programming for Kernel-Based Learning with Co-evolving Subsets Selection.
Proceedings of the Parallel Problem Solving from Nature, 2006

2005
Preference Learning in Terminology Extraction: A ROC-based approach
CoRR, 2005

Artificial Agents and Speculative Bubbles
CoRR, 2005

From Factorial and Hierarchical HMM to Bayesian Network: A Representation Change Algorithm.
Proceedings of the Abstraction, 2005

A Multi-Objective Multi-Modal Optimization Approach for Mining Stable Spatio-Temporal Patterns.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Phase Transitions within Grammatical Inference.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Efficient Mining of High Branching Factor Attribute Trees.
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

Inférence dans les HMM hiérarchiques et factorisés : changement de représentation vers le formalisme des Réseaux Bayésiens.
Proceedings of the Extraction des connaissances : Etat et perspectives (Ateliers de la conférence EGC'2005), 2005

Bayesian Learning with Local Support Vector Machines for Cancer Classification with Gene Expression Data.
Proceedings of the Applications of Evolutionary Computing, 2005

Multi-objective Multi-modal Optimization for Mining Spatio-temporal Patterns.
Proceedings of the Actes de CAP 05, Conférence francophone sur l'apprentissage automatique, 2005

Phase transitions in grammatical inference.
Proceedings of the Actes de CAP 05, Conférence francophone sur l'apprentissage automatique, 2005

HMM hiérarchiques et factorisés: mécanisme d'inférence et apprentissage à partir de peu de données.
Proceedings of the Actes de CAP 05, Conférence francophone sur l'apprentissage automatique, 2005

Systèmes inductifs-déductifs: une approche statistique.
Proceedings of the Actes de CAP 05, Conférence francophone sur l'apprentissage automatique, 2005

2004
Fast Theta-Subsumption with Constraint Satisfaction Algorithms.
Mach. Learn., 2004

Learning Interestingness Measures in Terminology Extraction. A ROC-based approach.
Proceedings of the ROC Analysis in Artificial Intelligence, 1st International Workshop, 2004

Ensemble Learning with Evolutionary Computation: Application to Feature Ranking.
Proceedings of the Parallel Problem Solving from Nature, 2004

Robotics and Multi-agent Systems Robustness in the Long Run: Auto-teaching vs Anticipation in Evolutionary Robotics.
Proceedings of the Parallel Problem Solving from Nature, 2004

Ensemble Feature Ranking.
Proceedings of the Knowledge Discovery in Databases: PKDD 2004, 2004

Learning to Order Terms: Supervised Interestingness Measures in Terminology Extraction
Proceedings of the International Conference on Computational Intelligence, 2004

C4.5 competence map: a phase transition-inspired approach.
Proceedings of the Machine Learning, 2004

DRYADE: A New Approach for Discovering Closed Frequent Trees in Heterogeneous Tree Databases.
Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 2004

Feature selection in proteomic pattern data with support vector machines.
Proceedings of the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2004

2003
Scalability and efficiency in multi-relational data mining.
SIGKDD Explor., 2003

Relational Learning as Search in a Critical Region.
J. Mach. Learn. Res., 2003

Impact Studies and Sensitivity Analysis in Medical Data Mining with ROC-based Genetic Learning.
Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003

Nouveaux résultats en classification à l'aide d'un codage par motifs fréquents.
Proceedings of the Extraction et gestion des connaissances (EGC'2003), 2003

Fouille de données visuelle et analyse de facteurs de risque médical.
Proceedings of the Extraction et gestion des connaissances (EGC'2003), 2003

Evolving Symbolic Controllers.
Proceedings of the Applications of Evolutionary Computing, 2003

ROC-Based Evolutionary Learning: Application to Medical Data Mining.
Proceedings of the Artificial Evolution, 2003

2002
Compact Unstructured Representations for Evolutionary Design.
Appl. Intell., 2002

A Novel Approach to Machine Discovery: Genetic Programming and Stochastic Grammars.
Proceedings of the Inductive Logic Programming, 12th International Conference, 2002

Constraint-based Learning of Long Relational Concepts.
Proceedings of the Machine Learning, 2002

TreeFinder: a First Step towards XML Data Mining.
Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM 2002), 2002

2001
Grammar-guided genetic programming and dimensional consistency: application to non-parametric identification in mechanics.
Appl. Soft Comput., 2001

Theta-Subsumption in a Constraint Satisfaction Perspective.
Proceedings of the Inductive Logic Programming, 11th International Conference, 2001

Combining Statistics and Semantics for Word and Document Clustering.
Proceedings of the IJCAI'2001 Workshop on Ontology Learning, 2001

Avoiding the Bloat with Stochastic Grammar-Based Genetic Programming.
Proceedings of the Artificial Evolution, 2001

2000
Any-time Relational Reasoning: Resource-bounded Induction and Deduction Through Stochastic Matching.
Mach. Learn., 2000

Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery.
Proceedings of the Parallel Problem Solving from Nature, 2000

Can Relational Learning Scale Up?
Proceedings of the Foundations of Intelligent Systems, 12th International Symposium, 2000

Analyzing Relational Learning in the Phase Transition Framework.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

A Distributed Resource Evolutionary Algorithm Machine (DREAM).
Proceedings of the 2000 Congress on Evolutionary Computation, 2000

1999
Hacia un Enfoque General del Trazado de Grafos.
Inteligencia Artif., 1999

Constructive Induction: A Version Space-based Approach.
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

From first order logic to Nd: a data driven reformulation.
Proceedings of the 7th European Symposium on Artificial Neural Networks, 1999

Relational Learning: Hard Problems and Phase Transitions.
Proceedings of the AI*IA 99:Advances in Artificial Intelligence, 1999

1998
Twelve Numerical, Symbolic and Hybrid Supervised Classification Methods.
Int. J. Pattern Recognit. Artif. Intell., 1998

Revisiting the Memory of Evolution.
Fundam. Informaticae, 1998

Extending Population-Based Incremental Learning to Continuous Search Spaces.
Proceedings of the Parallel Problem Solving from Nature, 1998

A Stochastic Simple Similarity.
Proceedings of the Inductive Logic Programming, 8th International Workshop, 1998

Continuous Mimetic Evolution.
Proceedings of the Machine Learning: ECML-98, 1998

1997
Distance Induction in First Order Logic.
Proceedings of the Inductive Logic Programming, 7th International Workshop, 1997

Tractable Induction and Classification in First Order Logic Via Stochastic Matching.
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

Toward Civilized Evolution: Developing Inhibitions.
Proceedings of the 7th International Conference on Genetic Algorithms, 1997

Inductive Learning of Mutation Step-Size in Evolutionary Parameter Optimization.
Proceedings of the Evolutionary Programming VI, 6th International Conference, 1997

Mimetic Evolution.
Proceedings of the Artificial Evolution, Third European Conference, 1997

1996
Induction of Constraint Logic Programs.
Proceedings of the Learning and Reasoning with Complex Representations, 1996

Mutation by Imitation in Boolean Evolution Strategies.
Proceedings of the Parallel Problem Solving from Nature, 1996

Polynomial-Time Learning in Logic Programming and Constraint Logic Programming.
Proceedings of the Inductive Logic Programming, 6th International Workshop, 1996

Delaying the Choice of Bias: A Disjunctive Version Space Approach.
Proceedings of the Machine Learning, 1996

An Advanced Evolution Should Not Repeat its Past Errors.
Proceedings of the Machine Learning, 1996

Controlling Evolution by Means of Machine Learning.
Proceedings of the Fifth Annual Conference on Evolutionary Programming, 1996

1995
A numerical strategy to defectuous knowledge using.
Ann. Oper. Res., 1995

An Induction-based Control for Genetic Algorithms (Extended Abstract).
Proceedings of the Machine Learning: ECML-95, 1995

Induction-Based Control of Genetic Algorithms.
Proceedings of the Artificial Evolution, European Conference, 1995

1994
Controlling Crossover through Inductive Learning.
Proceedings of the Parallel Problem Solving from Nature, 1994

A Constraint-based Induction Algorithm in FOL.
Proceedings of the Machine Learning, 1994

Using Constraints to Building Version Spaces.
Proceedings of the Machine Learning: ECML-94, 1994

1993
A Rule-Based Similarity Measure.
Proceedings of the Topics in Case-Based Reasoning, First European Workshop, 1993

1992
Learning to Control Inconsistent Knowledge.
Proceedings of the 10th European Conference on Artificial Intelligence, 1992

1991
Using Examples to Refine a Redundant Knowledge Base.
Proceedings of the European Workshop on the Verification and Validation of Knowledge-Based Systems, 1991

1990
Incremental Learning of Rules and Meta-rules.
Proceedings of the Machine Learning, 1990


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