Michele Sebag

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

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🗺️ Taxonomy Completionist (42) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Ultra 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird

🌱 Topic Pioneer 🌟 Keyword Trendsetter Combo (3) 🏆 Grand Slam 🧬 Topic Evolution 🏆 Keyword Champion 🧭 Keyword Pioneer 🔥 Unstoppable · Bronze 🚀 Conference Pioneer 🗃️ Keyword Collector (89) 💎 Century Club · Bronze 🌈 Renaissance Researcher (5) 📈 Trend Setter

Venues

IJCAI (5) ICLR (4) ACML (3) ICML (2) JMLR (2) AAAI (1) AutoML (1) NeurIPS (1)

Top co-authors

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

Research topics

Machine Learning (16) Artificial Intelligence (11) Core AI (8) Optimization & Theory (8) Learning Types (7) Core Methods (6) Mathematics & Optimization (4) Application Areas (4) Learning Paradigms (4) Optimization (4) Deep Learning (3) Reinforcement Learning (2) Methods (2) Interdisciplinary (1) Knowledge & Reasoning (1)

Keywords

monte carlo tree search (3) automated machine learning (3) neural network (3) adversarial learning (2) hyperparameter optimization (2) causal inference (2) causal graph (2) causal discovery (2) interactive learning (1) relational learning (1) model selection (1) matrix factorization (1) bayesian inference (1) collaborative filtering (1) concept-based explanation (1) knowledge distillation (1) preference learning (1) domain adaptation (1) bias detection (1) optimal transport (1)

Papers

DCILP: A Distributed Approach for Large-Scale Causal Structure Learning AAAI 2025 Provably Safeguarding a Classifier from OOD and Adversarial Samples ICLR 2025 Cutting the Black Box: Conceptual Interpretation of a Deep Neural Net with Multi-Modal Embeddings and Multi-Criteria Decision Aid IJCAI 2024 Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges IJCAI 2024 Toward Job Recommendation for All IJCAI 2023 Learning meta-features for AutoML ICLR 2022 Structural Agnostic Modeling: Adversarial Learning of Causal Graphs JMLR 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 NeurIPS 2010 Relational Learning as Search in a Critical Region JMLR 2003