Michèle Sebag

Q: What Schools Are Affiliated With Michèle Sebag

Michèle Sebag is affiliated with the following schools: Paris-Saclay University, Polytechnic Institute of Paris

Michèle Sebag's AcademicInfluence.com Rankings

Michèle Sebag

Computer Science

#2172

World Rank

#2260

Historical Rank

Data Mining

#47

World Rank

#47

Historical Rank

Machine Learning

#458

World Rank

#464

Historical Rank

Database

#7580

World Rank

#7867

Historical Rank

computer-science Degrees

Download Badge

Computer Science

Michèle Sebag's Degrees

PhD Computer Science Paris-Saclay University
Masters Computer Science Paris-Saclay University
Bachelors Mathematics Paris-Saclay University

Similar Degrees You Can Earn

Why Is Michèle Sebag Influential?

(Suggest an Edit or Addition)

According to Wikipedia, Martine-Michèle Sebag is a French computer scientist, primarily focused on machine learning. She has over 6,000 citations. Biography Sebag studied mathematics at the Ecole Normale Supérieure, and later worked in the computer science industry, starting at Thomson Corporation, where she was introduced to artificial intelligence. She then moved into the research field, at the Laboratoire de Mécanique des Solides at Ecole Polytechnique.

(See a Problem?)

Michèle Sebag's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Collaborative hyperparameter tuning (2013) (292)
Extending Population-Based Incremental Learning to Continuous Search Spaces (1998) (259)
TreeFinder: a first step towards XML data mining (2002) (218)
The grand challenge of computer Go (2012) (179)
Adaptive operator selection with dynamic multi-armed bandits (2008) (160)
Analyzing bandit-based adaptive operator selection mechanisms (2010) (150)
Machine Learning and Knowledge Discovery in Databases (2015) (138)
BenchNN: On the broad potential application scope of hardware neural network accelerators (2012) (116)
APRIL: Active Preference-learning based Reinforcement Learning (2012) (110)
Extreme Value Based Adaptive Operator Selection (2008) (110)
Feature Selection as a One-Player Game (2010) (105)
Analysis of the AutoML Challenge Series 2015-2018 (2019) (104)
Preference-Based Policy Learning (2011) (102)
Tractable Induction and Classification in First Order Logic Via Stochastic Matching (1997) (101)
Multi-armed Bandit, Dynamic Environments and Meta-Bandits (2006) (101)
Exploration vs Exploitation vs Safety: Risk-Aware Multi-Armed Bandits (2013) (100)
Data Stream Clustering With Affinity Propagation (2014) (91)
Data Streaming with Affinity Propagation (2008) (88)
Distance Induction in First Order Logic (1997) (87)
A mono surrogate for multiobjective optimization (2010) (85)
Dryade: a new approach for discovering closed frequent trees in heterogeneous tree databases (2004) (84)
Compact Unstructured Representations for Evolutionary Design (2002) (84)
Self-adaptive surrogate-assisted covariance matrix adaptation evolution strategy (2012) (82)
A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention (2016) (76)
Scalability and efficiency in multi-relational data mining (2003) (76)
Delaying the Choice of Bias: A Disjunctive Version Space Approach (1996) (75)
Comparison-Based Optimizers Need Comparison-Based Surrogates (2010) (75)
Graph inference datasets. Replication Data for: "Learning Functional Causal Models with Generative Neural Networks" (2017) (75)
Feature selection in proteomic pattern data with support vector machines (2004) (72)
Extreme compass and Dynamic Multi-Armed Bandits for Adaptive Operator Selection (2009) (69)
Ensemble Feature Ranking (2004) (65)
Fast Theta-Subsumption with Constraint Satisfaction Algorithms (2004) (63)
Dynamic Multi-Armed Bandits and Extreme Value-Based Rewards for Adaptive Operator Selection in Evolutionary Algorithms (2009) (61)
Alors: An algorithm recommender system (2017) (59)
Multi-objective Monte-Carlo Tree Search (2012) (58)
K-AP: Generating Specified K Clusters by Efficient Affinity Propagation (2010) (58)
Change Point Detection and Meta-Bandits for Online Learning in Dynamic Environments (2007) (58)
Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery (2000) (57)
DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm (2008) (57)
Controlling Crossover through Inductive Learning (1994) (56)
Toward comparison-based adaptive operator selection (2010) (56)
Adaptive coordinate descent (2011) (54)
Bi-population CMA-ES agorithms with surrogate models and line searches (2013) (53)
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs (2018) (51)
Relational Learning as Search in a Critical Region (2003) (51)
Analysis of adaptive operator selection techniques on the royal road and long k-path problems (2009) (50)
Programming by Feedback (2014) (50)
Evolutionary identification of macro-mechanical models (1996) (49)
Multi-Domain Adversarial Learning (2019) (46)
The Grand Challenge of Computer Go: Monte Carlo Tree Search and Extensions (2015) (46)
A Distributed Resource Evolutionary Algorithm Machine (DREAM) (2000) (46)
ROC-Based Evolutionary Learning: Application to Medical Data Mining (2003) (46)
Alternative Restart Strategies for CMA-ES (2012) (43)
Hypervolume indicator and dominance reward based multi-objective Monte-Carlo Tree Search (2013) (43)
Resource-bounded Relational Reasoning: Induction and Deduction Through Stochastic Matching (2004) (42)
Toward Civilized Evolution: Developing Inhibitions (1997) (42)
Causal Generative Neural Networks (2017) (41)
A Rule-Based Similarity Measure (1993) (41)
Intensive surrogate model exploitation in self-adaptive surrogate-assisted cma-es (saacm-es) (2013) (40)
Avoiding the Bloat with Stochastic Grammar-Based Genetic Programming (2001) (39)
Ensemble learning for free with evolutionary algorithms? (2007) (37)
Xyleme, a dynamic warehouse for XML data of the Web (2001) (37)
Bandit-Based Search for Constraint Programming (2013) (36)
The Grid Observatory (2009) (35)
Genetic Programming for Kernel-Based Learning with Co-evolving Subsets Selection (2006) (35)
Online Heuristic Selection in Constraint Programming (2009) (34)
Dominance-Based Pareto-Surrogate for Multi-Objective Optimization (2010) (34)
SAM: Structural Agnostic Model, Causal Discovery and Penalized Adversarial Learning (2018) (32)
Continuous Search in Constraint Programming (2010) (32)
Inductive Learning of Mutation Step-Size in Evolutionary Parameter Optimization (1997) (30)
A Machine Learning Approach for Statistical Software Testing (2007) (28)
French Roadmap for complex Systems 2008-2009 (2009) (28)
Anytime many-armed bandits (2007) (27)
Grammar-guided genetic programming and dimensional consistency: application to non-parametric identification in mechanics (2001) (27)
Automatic graph drawing and Stochastic Hill Climbing (1999) (27)
A Recommender System for Process Discovery (2014) (27)
An Advanced Evolution Should Not Repeat its Past Errors (1996) (26)
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm (2009) (26)
On Adaptive Self-Organization in Artificial Robot Organisms (2009) (26)
Incremental Learning of Rules and Meta-rules (1990) (25)
Algorithm Selection as a Collaborative Filtering Problem (2013) (25)
Comparison-Based Adaptive Strategy Selection with Bandits in Differential Evolution (2010) (25)
A Multi-Objective Multi-Modal Optimization Approach for Mining Stable Spatio-Temporal Patterns (2005) (25)
Theta-Subsumption in a Constraint Satisfaction Perspective (2001) (24)
Using Constraints to Building Version Spaces (1994) (24)
Toward autonomic grids: analyzing the job flow with affinity streaming (2009) (24)
Memory-enhanced Evolutionary Robotics: The Echo State Network Approach (2009) (22)
Learning Interestingness Measures in Terminology Extraction. A ROC-based approach (2004) (22)
Matching Jobs and Resumes: a Deep Collaborative Filtering Task (2016) (22)
Phase Transitions in Machine Learning (2011) (22)
Combining Statistics and Semantics for Word and Document Clustering (2001) (21)
Pilot, Rollout and Monte Carlo Tree Search Methods for Job Shop Scheduling (2012) (21)
Towards AutoML in the presence of Drift: first results (2018) (21)
Relational Learning: Hard Problems and Phase Transitions (1999) (20)
Continuous Rapid Action Value Estimates (2011) (20)
Impact studies and sensitivity analysis in medical data mining with ROC-based genetic learning (2003) (20)
Adaptive Operator Selection and Management in Evolutionary Algorithms (2012) (19)
Generative Learning (2010) (19)
Analyzing Relational Learning in the Phase Transition Framework (2000) (19)
Bayesian Learning with Local Support Vector Machines for Cancer Classification with Gene Expression Data (2005) (19)
Fitness-AUC bandit adaptive strategy selection vs. the probability matching one within differential evolution: an empirical comparison on the bbob-2010 noiseless testbed (2010) (18)
Agnostic Feature Selection (2019) (18)
Optimal robust expensive optimization is tractable (2009) (18)
Not All Parents Are Equal for MO-CMA-ES (2011) (18)
Black-box optimization benchmarking of IPOP-saACM-ES and BIPOP-saACM-ES on the BBOB-2012 noiseless testbed (2012) (17)
Efficient mining of high branching factor attribute trees (2005) (17)
A tour of machine learning: An AI perspective (2014) (17)
Preference Learning in Terminology Extraction: A ROC-based approach (2005) (15)
Neural Network Architecture (2010) (15)
Twelve Numerical, Symbolic and Hybrid Supervised Classification Methods (1998) (15)
C4.5 competence map: a phase transition-inspired approach (2004) (15)
Open-Ended Evolutionary Robotics: An Information Theoretic Approach (2010) (15)
Maximum Likelihood-Based Online Adaptation of Hyper-Parameters in CMA-ES (2014) (15)
Mutation by Imitation in Boolean Evolution Strategies (1996) (15)
Plan Recognition (2010) (14)
Combination of One-Class Support Vector Machines for Classification with Reject Option (2014) (14)
Ensemble Learning with Evolutionary Computation: Application to Feature Ranking (2004) (14)
Using Domain Knowledge in Evolutionary System Identification (2006) (13)
A distributed resource evolutionary algorithm machine. (2000) (13)
Automated Machine Learning with Monte-Carlo Tree Search (Extended Version) (2019) (13)
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities (2020) (13)
Adaptively detecting changes in Autonomic Grid Computing (2010) (13)
Atherosclerosis Risk Identification and Visual Analysis ( PKDD 2002 Challenge ) (12)
Interactive Robot Education (2013) (12)
Sustainable cooperative coevolution with a multi-armed bandit (2013) (12)
Controlling Evolution by Means of Machine Learning (1996) (11)
Frugal and Online Affinity Propagation (2008) (11)
ActivMetal: Algorithm Recommendation with Active Meta Learning (2018) (11)
Induction of Constraint Logic Programs (1996) (11)
Cooperation control in Parallel SAT Solving: a Multi-armed Bandit Approach (2012) (11)
Process-Based Modeling (2010) (10)
Evolving Symbolic Controllers (2003) (10)
Phase Transitions within Grammatical Inference (2005) (10)
Algorithm Selector and Prescheduler in the ICON Challenge (2018) (10)
Parametric and non-parametric identification of macro-mechanical models (1997) (10)
Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations (2016) (9)
Unsupervised Layer-Wise Model Selection in Deep Neural Networks (2010) (9)
Negative Predictive Value (2010) (9)
A Novel Approach to Machine Discovery: Genetic Programming and Stochastic Grammars (2002) (9)
Towards Non-Stationary Grid Models (2011) (9)
Scaling Analysis of Affinity Propagation (2009) (9)
Extreme: dynamic multi-armed bandits for adaptive operator selection (2009) (8)
Black-box optimization benchmarking of NIPOP-aCMA-ES and NBIPOP-aCMA-ES on the BBOB-2012 noiseless testbed (2012) (8)
Constraint-based Learning of Long Relational Concepts (2002) (8)
Constructive Induction: A Version Space-based Approach (1999) (8)
Experimental Design in Dynamical System Identification: A Bandit-Based Active Learning Approach (2014) (8)
Revisiting the Memory of Evolution (1998) (8)
Combining Myopic Optimization and Tree Search: Application to MineSweeper (2012) (8)
Language Modelling for Collaborative Filtering: Application to Job Applicant Matching (2017) (7)
Hybridizing Constraint Programming and Monte-Carlo Tree Search: Application to the Job Shop Problem (2013) (7)
A Stochastic Simple Similarity (1998) (7)
Toward Behavioral Modeling of a Grid System: Mining the Logging and Bookkeeping Files (2007) (7)
A pareto-compliant surrogate approach for multiobjective optimization (2010) (7)
EXIST: Exploitation/Exploration Inference for Statistical Software Testing (2006) (7)
Stochastic Gradient Descent: Going As Fast As Possible But Not Faster (2017) (7)
Dynamic Time Lag Regression: Predicting What & When (2020) (7)
Distributed and Incremental Clustering Based on Weighted Affinity Propagation (2008) (7)
Functional Brain Imaging with Multi-objective Multi-modal Evolutionary Optimization (2006) (7)
Robotics and Multi-agent Systems Robustness in the Long Run: Auto-teaching vs Anticipation in Evolutionary Robotics (2004) (7)
θ-subsumption in a constraint satisfaction perspective (2001) (6)
Any-time Relational Reasoning: Resource-bounded Induction and Deduction Through Stochastic Matching (2000) (6)
Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals (2020) (6)
Discovering Piecewise Linear Models of Grid Workload (2010) (6)
Multi-scale Real-Time Grid Monitoring with Job Stream Mining (2009) (6)
Learning meta-features for AutoML (2022) (6)
Coupling Evolution and Information Theory for Autonomous Robotic Exploration (2014) (6)
Single trial variability in brain–computer interfaces based on motor imagery: Learning in the presence of labeling noise (2011) (5)
Multi-dimensional sparse structured signal approximation using split bregman iterations (2013) (5)
Building Portfolios for the Protein Structure Prediction Problem (2010) (5)
Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III (2010) (5)
Induction-Based Control of Genetic Algorithms (1995) (5)
Lessons learned from the AutoML challenge (2018) (5)
Structural Statistical Software Testing with Active Learning in a Graph (2007) (5)
Polynomial-Time Learning in Logic Programming and Constraint Logic Programming (1996) (5)
Nonparametric Bayesian (2010) (5)
Generalization Performance (2010) (5)
SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system (2010) (5)
Artificial Agents and Speculative Bubbles (2004) (5)
Pride and Prejudice on a Centralized Academic Labor Market (2009) (5)
Black-box optimization benchmarking of IPOP-saACM-ES on the BBOB-2012 noisy testbed (2012) (4)
Mimetic Evolution (1997) (4)
A Constraint-based Induction Algorithm in FOL (1994) (4)
AutoML with Monte Carlo Tree Search (2018) (4)
ASAP.V2 and ASAP.V3: Sequential optimization of an Algorithm Selector and a Scheduler (2017) (4)
Learning Sparse Features with an Auto-Associator (2014) (4)
Modelling a Centralized Academic Labour Market: Efficiency and Fairness (2008) (4)
KL-based Control of the Learning Schedule for Surrogate Black-Box Optimization (2013) (4)
Advances in Intelligent Data Analysis XIV (2015) (3)
Learning to Order Terms: Supervised Interestingness Measures in Terminology Extraction (2007) (3)
Hacia un Enfoque General del Trazado de Grafos (2006) (3)
Frugal Machine Learning (2021) (3)
Strategic Choices in Optimization (2014) (3)
Learning to Control Inconsistent Knowledge (1992) (3)
From Factorial and Hierarchical HMM to Bayesian Network: A Representation Change Algorithm (2005) (3)
Fast Adaptive Object Detection towards a Smart Environment by a Mobile Robot (2013) (3)
SABIN: A Resampling-Based Learning Algorithm for Idle State Identification in Asynchronous Brain-Computer Interfaces (2010) (3)
Ensemble learning for brain computer-interface using uncooperative democratic echo state communities (2010) (3)
Upper Confidence Tree-Based Consistent Reactive Planning Application to MineSweeper (2012) (3)
From graphs to DAGs: a low-complexity model and a scalable algorithm (2022) (3)
Learning Bivariate Functional Causal Models (2019) (2)
Upper Conﬁdence Trees and Billiards for Optimal Active Learning (2009) (2)
Towards a Data Science Collaboratory (2015) (2)
Multi-objective Multi-modal Optimization for Mining Spatio-temporal Patterns (2005) (2)
Achieving optimization invariance w.r.t. monotonous transformations of the objective function and orthogonal transformations of the representation (2012) (2)
Using SVM to Avoid Humans: A Case of a Small Autonomous Mobile Robot in an Office (2011) (2)
Economy-Driven Shaping of Social Networks and Emerging Class Behaviors (2007) (2)
Can Relational Learning Scale Up? (2000) (2)
Emergence of temporal and spatial synchronous behaviors in a foraging swarm (2011) (2)
Interactive Metric Learning-Based Visual Data Exploration: Application to the Visualization of a Scientific Social Network (2015) (2)
Variational Auto-Encoder: not all failures are equal (2020) (2)
Genetic Grouping (2010) (2)
Convergence proofs, convergence rates and stopping criterions for multi-modal or multi-objective evolutionary algorithms (2004) (2)
Continuous Mimetic Evolution (1998) (2)
Genetic Clustering (2010) (2)
Discriminant Learning Machines (2019) (2)
A Phase Transition-Based Perspective on Multiple Instance Kernels (2007) (2)
Positive Semidefinite (2010) (2)
Distribution-Based Invariant Deep Networks for Learning Meta-Features (2020) (1)
Statistical Learning for BCIs (2016) (1)
Generic Methods for Evolutionary Ensemble Learning (2007) (1)
Learning 2-additive Hierarchical Choquet Integrals with non-monotonic utilities (2020) (1)
An Induction-based Control for Genetic Algorithms (Extended Abstract) (1995) (1)
Ensem ble Feature R anking (2017) (1)
Direct Value Learning: a Preference-based Approach to Reinforcement Learning (2012) (1)
Relational learning: Hard problems and Phase transition (2022) (1)
Machine Learning and Knowledge Discovery in Databases (2009) (1)
Fault Detection and Diagnosis from the Logging and Bookkeping Data (2007) (1)
Bellmanian Bandit Network (2014) (1)
Negative Correlation Learning (2010) (1)
Proceedings of the 11th International Conference on Inductive Logic Programming (2001) (1)
On the Identifiability of Hierarchical Decision Models (2021) (1)
Predicate Invention (2010) (1)
Positive Definite (2010) (1)
Iterative Learning for Model Reactive Control: Application to Autonomous Multi-agent Control (2021) (1)
Toward Optimal Run Racing: Application to Deep Learning Calibration (2017) (1)
SoftwareTesting with Active Learning in a Graph (2008) (1)
PAC Identification (2010) (1)
Direct Value Learning: a Rank-Invariant Approach to Reinforcement Learning (2014) (1)
From first order logic to Nd: a data driven reformulation (1999) (1)
BESS: Bandit Ensemble for parallel SAT Solving (2012) (1)
On-Board Evolutionary Algorithm and Off-Line Rule Discovery for Column Formation in Swarm Robotics (2011) (1)
Passive Learning (2010) (1)
Growth Function (2010) (1)
Cartolabe: A Web-Based Scalable Visualization of Large Document Collections (2020) (1)
A note on phase transitions and computational pitfalls of learning from sequences (2008) (1)
Anti Imitation-Based Policy Learning (2016) (1)
DRYADEPARENT: Efficient mining of high branching factor attribute trees (特集「Web Intelligence」および一般) (2005) (0)
Feature selection based on support sector machines for proteomic pattern data (2004) (0)
Scaling Analysis of the Affinity Propagation Algorithm (2009) (0)
PAC-MDP Learning (2010) (0)
New Losses for Generative Adversarial Learning (2018) (0)
Nonstandard Criteria in Evolutionary Learning (2010) (0)
Positive Predictive Value (2010) (0)
Guest editors’ introduction: special issue of selected papers from ECML PKDD 2010 (2010) (0)
Nogood Learning (2010) (0)
Ensemble Learning for Non-Invasive Brain Computer-Interfaces Using Uncooperative Democratic Echo State Communities (2011) (0)
Inductive-deductive systems: a mathematical logic and statistical learning perspective (2007) (0)
Chapter 9 Continuous Search in Constraint Programming (0)
General-to-Specific Search (2010) (0)
New Results - Machine Learning for Stochastic Optimisation (2007) (0)
Negotiation protocols and dynamic social networks (2007) (0)
Acknowledgments to Reviewers (1998) (0)
Postsynaptic Neuron (2010) (0)
Nonstationary Kernels (2010) (0)
Piecewise Linear Models (2010) (0)
Pruning Set (2010) (0)
New Results - Fundamentals of Machine Learning, Knowledge Extraction and Data Mining (2004) (0)
New Results - Crossing the Chasm (2009) (0)
Constraints, Optimization and Data (Dagstuhl Seminar 14411) (2014) (0)
Important Topics in Causal Analysis: Summary of the CAWS 2021 Round Table Discussion (2021) (0)
A numerical strategy to defectuous knowledge using (1995) (0)
From abstract items to latent spaces to observed data and back: Compositional Variational Auto-Encoder (2019) (0)
Piecewise Constant Models (2010) (0)
Networks with Kernel Functions (2010) (0)
New Results - Optimal Decision Making under Uncertainty (2013) (0)
New Results - Complex Systems (2011) (0)
New Results - Reservoir Computing (2008) (0)
Chair of the Nectar track at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD 2013), Prague, Czech Republic (2013) (0)
Direct Value Learning: Reinforcement Learning and Anti-Imitation (2015) (0)
New Results - Autonomous Computing (2011) (0)
Locally Linear Unsupervised Feature Selection (2018) (0)
Genetic Attribute Construction (2010) (0)
Collaborative Algorithm Platforms (2015) (0)
Boltzmann Tuning of Generative Models (2021) (0)
Ensemble feuture ranking (2004) (0)
Special issue for ECML PKDD 2010: Guest editors’ introduction (2010) (0)
New Results - Other applications (2005) (0)
Phase transitions in grammatical inference (2005) (0)
New Results - Optimal Decision Making (2011) (0)
Predicate Calculus (2010) (0)
Growing Set (2010) (0)
I2SL: Learn How to Swarm Autonomous Quadrotors Using Iterative Imitation Supervised Learning (2021) (0)
Inductive Logic Programming: 11th International Conference, ILP 2001, Strasbourg, France, September 9-11, 2001. Proceedings (2001) (0)
Autonomous learning of parameters in differential equations (2015) (0)
L EARNING META - FEATURES FOR A UTO ML (2022) (0)
Genetics-Based Machine Learning (2010) (0)
New Results - Applications to E-science (2014) (0)
Genetic Feature Selection (2010) (0)
The Game of Go the Tree of Possible Moves Optimizing the Power of the Algorithm (0)
Towards causal modeling of nutritional outcomes (2021) (0)
New Results - Inverse problems (2004) (0)
Generalized Delta Rule (2010) (0)
Programming from Traces (2010) (0)
New Results - Designing Criteria (2013) (0)
Grammar Learning (2010) (0)
Characterizing Anomalous Behaviors and Revising Robotic Controllers (2011) (0)
Parallel Corpus (2010) (0)
Proposition D'ARC INRIA MaBI : Machine Learning for Brain Computer Interfaces (2009) (0)
Managing a Large network of excellence: Case Study of the PASCAL Network (2007) (0)
New Results - Applications (2007) (0)
Hypervolume indicator and dominance reward based multi-objective Monte-Carlo Tree Search (2013) (0)
Bayesian learning w ith local support vector m achines for cancer classification w ith gene expression data (2017) (0)
Generality And Logic (2010) (0)
New Results - Large and Deep Networks (2011) (0)
Using Examples to Refine a Redundant Knowledge Base (1991) (0)
New Results - Continuous Optimization (2013) (0)
2 State of the Art and Goal of the Study (2007) (0)
Proposal for a common research project INRIA-LRI as part of UR Futurs TAO-Thèmes Apprentissage et Optimisation Machine Learning , Data Mining and Evolutionary Optimization (0)
Program Synthesis From Examples (2010) (0)
Genetic Neural Networks (2010) (0)
New Results - Stochastic Optimisation for ML and DM (2007) (0)
Grammatical Inference (2010) (0)
High-Dimensional Causal Discovery: Learning from Inverse Covariance via Independence-based Decomposition (2022) (0)
Inductive Logic Programming (2001) (0)
Structural Sampling for Statistical Software Testing (2007) (0)
Learning to O rder T erms : Supervised Interestingness Measures in T erminology E xtraction (2012) (0)

This paper list is powered by the following services:

Other Resources About Michèle Sebag

What Schools Are Affiliated With Michèle Sebag?

Michèle Sebag is affiliated with the following schools:

Michèle Sebag's Academic­Influence.com Rankings

Michèle Sebag's Degrees

Similar Degrees You Can Earn

Why Is Michèle Sebag Influential?

Michèle Sebag's Published Works

Published Works

Other Resources About Michèle Sebag

What Schools Are Affiliated With Michèle Sebag?

Michèle Sebag's AcademicInfluence.com Rankings