Stéphan Clémençon

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 93

Top Venues

Publications

Myrto Limnios, Stéphan Clémençon
On Ranking-based Tests of Independence. AISTATS (2024)
Jean-Rémy Conti, Stéphan Clémençon
Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition. ICLR (2024)
Qi Gan, Sao Mai Nguyen, Mounîm A. El-Yacoubi, Eric Fenaux, Stéphan Clémençon
Human Pose Estimation Based Biomechanical Feature Extraction for Long Jumps. HSI (2024)
Emilia Siviero, Guillaume Staerman, Stéphan Clémençon, Thomas Moreau
Flexible Parametric Inference for Space-Time Hawkes Processes. CoRR (2024)
Isaia Andrenacci, Matteo Lonardi, Petros Ramantanis, Elie Awwad, Ekhiñe Irurozki, Stéphan Clémençon, Paolo Serena, Chiara Lasagni, Sébastien Bigo, Patricia Layec
Machine Learning-Driven Low-Complexity Optical Power Optimization for Point-to-Point Links. OFC (2024)
Guillaume Staerman, Pavlo Mozharovskyi, Pierre Colombo, Stéphan Clémençon, Florence d'Alché-Buc
A Pseudo-Metric between Probability Distributions based on Depth-Trimmed Regions. Trans. Mach. Learn. Res. 2024 (2024)
Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stéphan Clémençon
Functional anomaly detection: a benchmark study. Int. J. Data Sci. Anal. 16 (1) (2023)
James Cheshire, Vincent Laurent, Stéphan Clémençon
Active Bipartite Ranking. NeurIPS (2023)
Anas Himmi, Ekhine Irurozki, Nathan Noiry, Stéphan Clémençon, Pierre Colombo
Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks. CoRR (2023)
Morgane Goibert, Clément Calauzènes, Ekhine Irurozki, Stéphan Clémençon
Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues. ICML (2023)
Morgane Goibert, Clément Calauzènes, Ekhine Irurozki, Stéphan Clémençon
Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues. CoRR (2023)
Nathan Huet, Stéphan Clémençon, Anne Sabourin
On Regression in Extreme Regions. CoRR (2023)
Isaia Andrenacci, Matteo Lonardi, Petros Ramantanis, Elie Awwad, Ekhiñe Irurozki, Stéphan Clémençon
Fast and accurate nonlinear interference in-band spectrum prediction for sparse channel allocation. ONDM (2023)
Laurence Likforman-Sulem, Anna Esposito, Marcos Faúndez-Zanuy, Stéphan Clémençon, Gennaro Cordasco
EMOTHAW: A novel database for emotional state recognition from handwriting. CoRR (2022)
Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stéphan Clémençon
What are the best Systems? New Perspectives on NLP Benchmarking. NeurIPS (2022)
Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stéphan Clémençon
Functional Anomaly Detection: a Benchmark Study. CoRR (2022)
Jean-Rémy Conti, Nathan Noiry, Stéphan Clémençon, Vincent Despiegel, Stéphane Gentric
Mitigating Gender Bias in Face Recognition using the von Mises-Fisher Mixture Model. ICML (2022)
Emilia Siviero, Emilie Chautru, Stéphan Clémençon
A Statistical Learning View of Simple Kriging. CoRR (2022)
Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stéphan Clémençon
What are the best systems? New perspectives on NLP Benchmarking. CoRR (2022)
Morgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi
Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications. CoRR (2022)
Jean-Rémy Conti, Stéphan Clémençon
Assessing Performance and Fairness Metrics in Face Recognition - Bootstrap Methods. CoRR (2022)
Jean-Rémy Conti, Nathan Noiry, Vincent Despiegel, Stéphane Gentric, Stéphan Clémençon
Mitigating Gender Bias in Face Recognition Using the von Mises-Fisher Mixture Model. CoRR (2022)
Mathieu Chambefort, Raphaël Butez, Emilie Chautru, Stéphan Clémençon
Improving the quality control of seismic data through active learning. CoRR (2022)
Morgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi
Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications. AISTATS (2022)
Guillaume Ausset, Stéphan Clémençon, François Portier
Empirical Risk Minimization under Random Censorship. J. Mach. Learn. Res. 23 (2022)
Pierre Laforgue, Stéphan Clémençon, Patrice Bertail
On Medians of (Randomized) Pairwise Means. CoRR (2022)
Corentin Larroche, Johan Mazel, Stéphan Clémençon
Anomalous Cluster Detection in Large Networks with Diffusion-Percolation Testing. ESANN (2021)
Safa Boudabous, Stéphan Clémençon, Houda Labiod, Julian Garbiso
Dynamic Graph Convolutional LSTM application for traffic flow estimation from error-prone measurements: results and transferability analysis. DSAA (2021)
Guillaume Ausset, Stéphan Clémençon, François Portier
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications. AISTATS (2021)
Guillaume Ausset, Tom Ciffreo, François Portier, Stéphan Clémençon, Timothée Papin
Individual Survival Curves with Conditional Normalizing Flows. DSAA (2021)
Pierre Laforgue, Guillaume Staerman, Stéphan Clémençon
Generalization Bounds in the Presence of Outliers: a Median-of-Means Study. ICML (2021)
Corentin Larroche, Johan Mazel, Stéphan Clémençon
Dynamically Modelling Heterogeneous Higher-Order Interactions for Malicious Behavior Detection in Event Logs. CoRR (2021)
Safa Boudabous, Stéphan Clémençon, Houda Labiod, Julian Garbiso
Dynamic Graph Convolutional LSTM application for traffic flow estimation from error-prone measurements: results and transferability analysis. DSAA (2021)
Guillaume Ausset, Tom Ciffreo, François Portier, Stéphan Clémençon, Timothée Papin
Individual Survival Curves with Conditional Normalizing Flows. CoRR (2021)
Robin Vogel, Stéphan Clémençon, Pierre Laforgue
Visual Recognition with Deep Learning from Biased Image Datasets. CoRR (2021)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon
Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints. AISTATS (2021)
Myrto Limnios, Nathan Noiry, Stéphan Clémençon
Learning to Rank Anomalies: Scalar Performance Criteria and Maximization of Two-Sample Rank Statistics. LIDTA@ECML/PKDD (2021)
Patrice Bertail, Stéphan Clémençon, Yannick Guyonvarch, Nathan Noiry
Learning from Biased Data: A Semi-Parametric Approach. ICML (2021)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
Depth-based pseudo-metrics between probability distributions. CoRR (2021)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis. CoRR (2021)
Corentin Larroche, Johan Mazel, Stéphan Clémençon
Percolation-Based Detection of Anomalous Subgraphs in Complex Networks. IDA (2020)
Robin Vogel, Stéphan Clémençon
A Multiclass Classification Approach to Label Ranking. AISTATS (2020)
Stéphan Clémençon, Robin Vogel
A Multiclass Classification Approach to Label Ranking. CoRR (2020)
Naman Singh Negi, Ons Jelassi, Hakima Chaouchi, Stéphan Clémençon
Distributed online Data Anomaly Detection for connected vehicles. ICAIIC (2020)
Pierre Laforgue, Guillaume Staerman, Stéphan Clémençon
How Robust is the Median-of-Means? Concentration Bounds in Presence of Outliers. CoRR (2020)
Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d'Alché-Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh
Identifying the "right" level of explanation in a given situation. NeHuAI@ECAI (2020)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth measure. AISTATS (2020)
Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d'Alché-Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh
Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach. CoRR (2020)
Stéphan Clémençon, Patrice Bertail, Gabriela Ciolek
Statistical learning based on Markovian data maximal deviation inequalities and learning rates. Ann. Math. Artif. Intell. 88 (7) (2020)
Robin Vogel, Mastane Achab, Stéphan Clémençon, Charles Tillier
Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling. CoRR (2020)
Guillaume Ausset, Stéphan Clémençon, François Portier
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications. CoRR (2020)
Maël Chiapino, Stéphan Clémençon, Vincent Feuillard, Anne Sabourin
A multivariate extreme value theory approach to anomaly clustering and visualization. Comput. Stat. 35 (2) (2020)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon
Learning Fair Scoring Functions: Fairness Definitions, Algorithms and Generalization Bounds for Bipartite Ranking. CoRR (2020)
Robin Vogel, Mastane Achab, Stéphan Clémençon, Charles Tillier
Weighted Emprirical Risk Minimization: Transfer Learning based on Importance Sampling. ESANN (2020)
Stéphan Clémençon, Robin Vogel
On Tree-Based Methods for Similarity Learning. LOD (2019)
Mastane Achab, Anna Korba, Stéphan Clémençon
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach. ALT (2019)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure. CoRR (2019)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon, Ons Jelassi, Guillaume Papa
Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning. CoRR (2019)
Pierre Laforgue, Stéphan Clémençon
Statistical Learning from Biased Training Samples. CoRR (2019)
Safa Boudabous, Julian Garbiso, Bertrand Leroy, Stéphan Clémençon, Houda Labiod
Traffic Analysis Based on Bluetooth Passive Scanning. VTC Spring (2019)
Guillaume Ausset, Stéphan Clémençon, François Portier
Empirical Risk Minimization under Random Censorship: Theory and Practice. CoRR (2019)
Naman Singh Negi, Ons Jelassi, Stéphan Clémençon, Sebastian Fischmeister
A LSTM Approach to Detection of Autonomous Vehicle Hijacking. VEHITS (2019)
Stéphan Clémençon, Pierre Laforgue, Patrice Bertail
On Medians of (Randomized) Pairwise Means. ICML (2019)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
Functional Isolation Forest. ACML (2019)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon, Ons Jelassi, Guillaume Papa
Trade-Offs in Large-Scale Distributed Tuplewise Estimation And Learning. ECML/PKDD (2) (2019)
Pierre Laforgue, Stéphan Clémençon, Florence d'Alché-Buc
Autoencoding any Data through Kernel Autoencoders. AISTATS (2019)
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
Functional Isolation Forest. CoRR (2019)
Stéphan Clémençon, Robin Vogel
On Tree-based Methods for Similarity Learning. CoRR (2019)
Stéphan Clémençon, François Portier
Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods. AISTATS (2018)
Mastane Achab, Stéphan Clémençon, Aurélien Garivier
Profitable Bandits. CoRR (2018)
Mastane Achab, Stéphan Clémençon, Aurélien Garivier
Profitable Bandits. ACML (2018)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization. CoRR (2018)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization. ICML (2018)
Hamid Jalalzai, Stéphan Clémençon, Anne Sabourin
On Binary Classification in Extreme Regions. NeurIPS (2018)
Stéphan Clémençon, Anna Korba
On aggregation in ranking median regression. ESANN (2018)
Patrice Bertail, Gabriela Ciolek, Stéphan Clémençon
Generalization Bounds for Minimum Volume Set Estimation based on Markovian Data. ISAIM (2018)
Stéphan Clémençon, Anna Korba, Eric Sibony
Ranking Median Regression: Learning to Order through Local Consensus. ALT (2018)
Pierre Laforgue, Stéphan Clémençon, Florence d'Alché-Buc
Autoencoding any Data through Kernel Autoencoders. CoRR (2018)
Mastane Achab, Anna Korba, Stéphan Clémençon
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach. CoRR (2018)
Mastane Achab, Stéphan Clémençon, Aurélien Garivier, Anne Sabourin, Claire Vernade
Max K-Armed Bandit: On the ExtremeHunter Algorithm and Beyond. ECML/PKDD (2) (2017)
Stéphan Clémençon, Mastane Achab
Ranking Data with Continuous Labels through Oriented Recursive Partitions. NIPS (2017)
Anna Korba, Stéphan Clémençon, Eric Sibony
A Learning Theory of Ranking Aggregation. AISTATS (2017)
Laurence Likforman-Sulem, Anna Esposito, Marcos Faúndez-Zanuy, Stéphan Clémençon, Gennaro Cordasco
EMOTHAW: A Novel Database for Emotional State Recognition From Handwriting and Drawing. IEEE Trans. Hum. Mach. Syst. 47 (2) (2017)
Nicolas Goix, Anne Sabourin, Stéphan Clémençon
Sparse representation of multivariate extremes with applications to anomaly detection. J. Multivar. Anal. 161 (2017)
Albert Thomas, Stéphan Clémençon, Alexandre Gramfort, Anne Sabourin
Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere. AISTATS (2017)
Mastane Achab, Stéphan Clémençon, Aurélien Garivier, Anne Sabourin, Claire Vernade
Max K-armed bandit: On the ExtremeHunter algorithm and beyond. CoRR (2017)
Nicolas Goix, Anne Sabourin, Stéphan Clémençon
Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking. AISTATS (2016)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. ICML (2016)
Stéphan Clémençon, Patrice Bertail, Guillaume Papa
Learning from Survey Training Samples: Rate Bounds for Horvitz-Thompson Risk Minimizers. ACML (2016)
Guillaume Papa, Aurélien Bellet, Stéphan Clémençon
On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability. NIPS (2016)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. CoRR (2016)
Stéphan Clémençon, Igor Colin, Aurélien Bellet
Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics. J. Mach. Learn. Res. 17 (2016)
Charanpal Dhanjal, Nicolas Baskiotis, Stéphan Clémençon, Nicolas Usunier
An empirical comparison of V-fold penalisation and cross-validation for model selection in distribution-free regression. Pattern Anal. Appl. 19 (1) (2016)
Eric Sibony, Stéphan Clémençon, Jérémie Jakubowicz
MRA-based Statistical Learning from Incomplete Rankings. ICML (2015)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Extending Gossip Algorithms to Distributed Estimation of U-statistics. NIPS (2015)
Charanpal Dhanjal, Romaric Gaudel, Stéphan Clémençon
Collaborative Filtering with Localised Ranking. AAAI (2015)
Guillaume Papa, Pascal Bianchi, Stéphan Clémençon
Adaptive Sampling for Incremental Optimization Using Stochastic Gradient Descent. ALT (2015)
Nicolas Goix, Anne Sabourin, Stéphan Clémençon
Learning the dependence structure of rare events: a non-asymptotic study. COLT (2015)
Stéphan Clémençon, Sylvain Robbiano
An Ensemble Learning Technique for Multipartite Ranking. ESANN (2015)
Stéphan Clémençon, Héctor de Arazoza, Fabrice Rossi, Viet-Chi Tran
A statistical network analysis of the HIV/AIDS epidemics in Cuba. Soc. Netw. Anal. Min. 5 (1) (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Stéphan Clémençon