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← Authors

Michele Sebag

19 papers · 2003–2025 · 8 conferences · across top CS/AI conferences

Achievements

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+13 more ↓ 🧭 Keyword Pioneer 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (17) 🌍 Conference Polyglot (8)
πŸ—ΊοΈ Taxonomy Completionist (17) 🌈 Renaissance Researcher (6) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (4) πŸ† Grand Slam 🌱 Topic Pioneer πŸ† Keyword Champion (2) 🧬 Topic Evolution πŸš€ Conference Pioneer πŸ’Ž Century Club (19) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (72) πŸ”₯ Unstoppable (5)

Conferences

IJCAI (5) ICLR (4) ACML (3) ICML (2) JMLR (2) AAAI (1) AUTOML (1) NIPS (1)

Top co-authors

Marc Schoenauer (5) Johanne Cohen (3) Christophe Labreuche (3) Nicolas Atienza (2) MΓ‘tyΓ‘s Brendel (2) Isabelle Guyon (2) Olivier Teytaud (2) Philippe Caillou (2) Herilalaina Rakotoarison (2) Roman Bresson (2)

Research topics

Reinforcement Learning (1)

Keywords

neural network (3) causal discovery (2) causal inference (2) monte-carlo tree search (2) hyperparameter optimization (2) automated machine learning (2) causal graph (2) transfer learning (1) interactive learning (1) adversarial learning (1) collaborative filtering (1) sequential decision making (1) preference learning (1) knowledge distillation (1) markov decision process (1) model selection (1) model interpretability (1) causal structure learning (1) relational learning (1) distributed learning (1)

Papers

Provably Safeguarding a Classifier from OOD and Adversarial Samples ICLR 2025 DCILP: A Distributed Approach for Large-Scale Causal Structure Learning AAAI 2025 Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges IJCAI 2024 Cutting the Black Box: Conceptual Interpretation of a Deep Neural Net with Multi-Modal Embeddings and Multi-Criteria Decision Aid IJCAI 2024 Toward Job Recommendation for All IJCAI 2023 Structural Agnostic Modeling: Adversarial Learning of Causal Graphs JMLR 2022 Learning meta-features for AutoML ICLR 2022 Dynamic Time Lag Regression: Predicting What & When ICLR 2020 Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals IJCAI 2020 Automated Machine Learning with Monte-Carlo Tree Search IJCAI 2019 Multi-Domain Adversarial Learning ICLR 2019 A Brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning Without Human Intervention AUTOML 2016 Programming by Feedback ICML 2014 Collaborative hyperparameter tuning ICML 2013 Exploration vs Exploitation vs Safety: Risk-Aware Multi-Armed Bandits ACML 2013 Multi-objective Monte-Carlo Tree Search ACML 2012 Continuous Rapid Action Value Estimates ACML 2011 SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system NIPS 2010 Relational Learning as Search in a Critical Region JMLR 2003