Stéphan Clémençon

172 papers A* 19A 18B 15C 6Misc 2Journal 81Unranked 30

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Active Bipartite Ranking with Smooth Posterior Distributions. CoRR James Cheshire, Stéphan Clémençon
2026	A*	`conf`	Best Arm Identification with Biased Contexts. AAAI James Cheshire, Stéphan Clémençon
2026	J	`jnl`	Beyond Kemeny Medians: Consensus Ranking Distributions Definition, Properties and Statistical Learning. CoRR Stéphan Clémençon, Ekhine Irurozki
2026	J	`jnl`	Decentralized Ranking Aggregation: Gossip Algorithms for Borda and Copeland Consensus. CoRR Anna Van Elst, Kerrian Le Caillec, Igor Colin, Stéphan Clémençon
2026	J	`jnl`	On Gossip Algorithms for Machine Learning with Pairwise Objectives. CoRR Igor Colin, Aurélien Bellet, Stéphan Clémençon, Joseph Salmon
2026	J	`jnl`	On Gossip Algorithms for Machine Learning with Pairwise Objectives. Trans. Mach. Learn. Res. Igor Colin, Aurélien Bellet, Stéphan Clémençon, Joseph Salmon
2026	J	`jnl`	Robust Distributed Learning under Resource Constraints: Decentralized Quantile Estimation via (Asynchronous) ADMM. CoRR Anna Van Elst, Igor Colin, Stéphan Clémençon
2026	J	`jnl`	TimeSAE: Sparse Decoding for Faithful Explanations of Black-Box Time Series Models. CoRR Khalid Oublal, Quentin Bouniot, Qi Gan, Stéphan Clémençon, Zeynep Akata
2025	A	`conf`	Active Bipartite Ranking with Smooth Posterior Distributions. AISTATS James Cheshire, Stéphan Clémençon
2025	J	`jnl`	Asynchronous Gossip Algorithms for Rank-Based Statistical Methods. CoRR Anna Van Elst, Igor Colin, Stéphan Clémençon
2025	J	`jnl`	Feature Impact Analysis on Top Long-Jump Performances with Quantile Random Forest and Explainable AI Techniques. CoRR Qi Gan, Stéphan Clémençon, Mounîm A. El-Yacoubi, Sao Mai Nguyen, Eric Fenaux, Ons Jelassi
2025	J	`jnl`	Mitigating Bias in Facial Recognition Systems: Centroid Fairness Loss Optimization. CoRR Jean-Rémy Conti, Stéphan Clémençon
2025	B	`conf`	Numerically Efficient Parametric Inference for Learning Space-Time Hawkes Processes. DSAA Emilia Siviero, Guillaume Staerman, Stéphan Clémençon, Thomas Moreau
2025	—	`conf`	Polar Coordinate-Based 2D Pose Prior with Neural Distance Field. CVPR Workshops Qi Gan, Sao Mai Nguyen, Eric Fenaux, Stéphan Clémençon, Mounim A. El-Yacoubi
2025	J	`jnl`	Polar Coordinate-Based 2D Pose Prior with Neural Distance Field. CoRR Qi Gan, Sao Mai Nguyen, Eric Fenaux, Stéphan Clémençon, Mounim A. El-Yacoubi
2025	J	`jnl`	Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means. CoRR Anna Van Elst, Igor Colin, Stéphan Clémençon
2024	J	`jnl`	A Pseudo-Metric between Probability Distributions based on Depth-Trimmed Regions. Trans. Mach. Learn. Res. Guillaume Staerman, Pavlo Mozharovskyi, Pierre Colombo, Stéphan Clémençon, Florence d'Alché-Buc
2024	A*	`conf`	Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition. ICLR Jean-Rémy Conti, Stéphan Clémençon
2024	J	`jnl`	Flexible Parametric Inference for Space-Time Hawkes Processes. CoRR Emilia Siviero, Guillaume Staerman, Stéphan Clémençon, Thomas Moreau
2024	C	`conf`	Human Pose Estimation Based Biomechanical Feature Extraction for Long Jumps. HSI Qi Gan, Sao Mai Nguyen, Mounîm A. El-Yacoubi, Eric Fenaux, Stéphan Clémençon
2024	J	`jnl`	Learning to rank anomalies: scalar performance criteria and maximization of rank statistics. Mach. Learn. Myrto Limnios, Nathan Noiry, Stéphan Clémençon
2024	—	`conf`	Machine Learning-Driven Low-Complexity Optical Power Optimization for Point-to-Point Links. OFC Isaia Andrenacci, Matteo Lonardi, Petros Ramantanis, Elie Awwad, Ekhiñe Irurozki, Stéphan Clémençon, Paolo Serena, Chiara Lasagni, Sébastien Bigo, Patricia Layec
2024	J	`jnl`	Machine-learning-based technique to establish ASE or Kerr impairment dominance in optical transmission. J. Opt. Commun. Netw. Isaia Andrenacci, Matteo Lonardi, Petros Ramantanis, Elie Awwad, Ekhiñe Irurozki, Stéphan Clémençon, Sylvain Almonacil
2024	—	`conf`	Mitigating Bias in Facial Recognition Systems: Centroid Fairness Loss Optimization. ICPR (Workshops and Challenges, 1) Jean-Rémy Conti, Stéphan Clémençon
2024	A	`conf`	On Ranking-based Tests of Independence. AISTATS Myrto Limnios, Stéphan Clémençon
2024	—	`conf`	Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks. EMNLP (Findings) Anas Himmi, Ekhine Irurozki, Nathan Noiry, Stéphan Clémençon, Pierre Colombo
2024	J	`jnl`	Weibull mixture estimation based on censored data with applications to clustering in reliability engineering. Qual. Reliab. Eng. Int. Florian Lamalle, Vincent Feuillard, Anne Sabourin, Stéphan Clémençon
2023	A*	`conf`	Active Bipartite Ranking. NeurIPS James Cheshire, Vincent Laurent, Stéphan Clémençon
2023	—	`conf`	Fast and accurate nonlinear interference in-band spectrum prediction for sparse channel allocation. ONDM Isaia Andrenacci, Matteo Lonardi, Petros Ramantanis, Elie Awwad, Ekhiñe Irurozki, Stéphan Clémençon
2023	J	`jnl`	Functional anomaly detection: a benchmark study. Int. J. Data Sci. Anal. Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stéphan Clémençon
2023	J	`jnl`	On Regression in Extreme Regions. CoRR Nathan Huet, Stéphan Clémençon, Anne Sabourin
2023	A*	`conf`	Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues. ICML Morgane Goibert, Clément Calauzènes, Ekhine Irurozki, Stéphan Clémençon
2023	J	`jnl`	Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues. CoRR Morgane Goibert, Clément Calauzènes, Ekhine Irurozki, Stéphan Clémençon
2023	J	`jnl`	Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks. CoRR Anas Himmi, Ekhine Irurozki, Nathan Noiry, Stéphan Clémençon, Pierre Colombo
2022	J	`jnl`	A Statistical Learning View of Simple Kriging. CoRR Emilia Siviero, Emilie Chautru, Stéphan Clémençon
2022	J	`jnl`	Assessing Performance and Fairness Metrics in Face Recognition - Bootstrap Methods. CoRR Jean-Rémy Conti, Stéphan Clémençon
2022	J	`jnl`	EMOTHAW: A novel database for emotional state recognition from handwriting. CoRR Laurence Likforman-Sulem, Anna Esposito, Marcos Faúndez-Zanuy, Stéphan Clémençon, Gennaro Cordasco
2022	J	`jnl`	Empirical Risk Minimization under Random Censorship. J. Mach. Learn. Res. Guillaume Ausset, Stéphan Clémençon, François Portier
2022	J	`jnl`	Functional Anomaly Detection: a Benchmark Study. CoRR Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi, Vera Hofer, Jayant Sen Gupta, Stéphan Clémençon
2022	J	`jnl`	Improving the quality control of seismic data through active learning. CoRR Mathieu Chambefort, Raphaël Butez, Emilie Chautru, Stéphan Clémençon
2022	J	`jnl`	Mitigating Gender Bias in Face Recognition Using the von Mises-Fisher Mixture Model. CoRR Jean-Rémy Conti, Nathan Noiry, Vincent Despiegel, Stéphane Gentric, Stéphan Clémençon
2022	A*	`conf`	Mitigating Gender Bias in Face Recognition using the von Mises-Fisher Mixture Model. ICML Jean-Rémy Conti, Nathan Noiry, Stéphan Clémençon, Vincent Despiegel, Stéphane Gentric
2022	J	`jnl`	On Medians of (Randomized) Pairwise Means. CoRR Pierre Laforgue, Stéphan Clémençon, Patrice Bertail
2022	A	`conf`	Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications. AISTATS Morgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi
2022	J	`jnl`	Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and Applications. CoRR Morgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi
2022	A*	`conf`	What are the best Systems? New Perspectives on NLP Benchmarking. NeurIPS Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stéphan Clémençon
2022	J	`jnl`	What are the best systems? New perspectives on NLP Benchmarking. CoRR Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stéphan Clémençon
2021	J	`jnl`	Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis. CoRR Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
2021	B	`conf`	Anomalous Cluster Detection in Large Networks with Diffusion-Percolation Testing. ESANN Corentin Larroche, Johan Mazel, Stéphan Clémençon
2021	J	`jnl`	Depth-based pseudo-metrics between probability distributions. CoRR Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
2021	B	`conf`	Dynamic Graph Convolutional LSTM application for traffic flow estimation from error-prone measurements: results and transferability analysis. DSAA Safa Boudabous, Stéphan Clémençon, Houda Labiod, Julian Garbiso
2021	B	`conf`	Dynamic Graph Convolutional LSTM application for traffic flow estimation from error-prone measurements: results and transferability analysis. DSAA Safa Boudabous, Stéphan Clémençon, Houda Labiod, Julian Garbiso
2021	J	`jnl`	Dynamically Modelling Heterogeneous Higher-Order Interactions for Malicious Behavior Detection in Event Logs. CoRR Corentin Larroche, Johan Mazel, Stéphan Clémençon
2021	A*	`conf`	Generalization Bounds in the Presence of Outliers: a Median-of-Means Study. ICML Pierre Laforgue, Guillaume Staerman, Stéphan Clémençon
2021	B	`conf`	Individual Survival Curves with Conditional Normalizing Flows. DSAA Guillaume Ausset, Tom Ciffreo, François Portier, Stéphan Clémençon, Timothée Papin
2021	J	`jnl`	Individual Survival Curves with Conditional Normalizing Flows. CoRR Guillaume Ausset, Tom Ciffreo, François Portier, Stéphan Clémençon, Timothée Papin
2021	A	`conf`	Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints. AISTATS Robin Vogel, Aurélien Bellet, Stéphan Clémençon
2021	A*	`conf`	Learning from Biased Data: A Semi-Parametric Approach. ICML Patrice Bertail, Stéphan Clémençon, Yannick Guyonvarch, Nathan Noiry
2021	—	`conf`	Learning to Rank Anomalies: Scalar Performance Criteria and Maximization of Two-Sample Rank Statistics. LIDTA@ECML/PKDD Myrto Limnios, Nathan Noiry, Stéphan Clémençon
2021	A	`conf`	Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications. AISTATS Guillaume Ausset, Stéphan Clémençon, François Portier
2021	J	`jnl`	Visual Recognition with Deep Learning from Biased Image Datasets. CoRR Robin Vogel, Stéphan Clémençon, Pierre Laforgue
2020	A	`conf`	A Multiclass Classification Approach to Label Ranking. AISTATS Robin Vogel, Stéphan Clémençon
2020	J	`jnl`	A Multiclass Classification Approach to Label Ranking. CoRR Stéphan Clémençon, Robin Vogel
2020	J	`jnl`	A multivariate extreme value theory approach to anomaly clustering and visualization. Comput. Stat. Maël Chiapino, Stéphan Clémençon, Vincent Feuillard, Anne Sabourin
2020	—	`conf`	Distributed online Data Anomaly Detection for connected vehicles. ICAIIC Naman Singh Negi, Ons Jelassi, Hakima Chaouchi, Stéphan Clémençon
2020	J	`jnl`	Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach. CoRR Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d'Alché-Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh
2020	J	`jnl`	How Robust is the Median-of-Means? Concentration Bounds in Presence of Outliers. CoRR Pierre Laforgue, Guillaume Staerman, Stéphan Clémençon
2020	—	`conf`	Identifying the "right" level of explanation in a given situation. NeHuAI@ECAI Valérie Beaudouin, Isabelle Bloch, David Bounie, Stéphan Clémençon, Florence d'Alché-Buc, James Eagan, Winston Maxwell, Pavlo Mozharovskyi, Jayneel Parekh
2020	J	`jnl`	Learning Fair Scoring Functions: Fairness Definitions, Algorithms and Generalization Bounds for Bipartite Ranking. CoRR Robin Vogel, Aurélien Bellet, Stéphan Clémençon
2020	J	`jnl`	Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications. CoRR Guillaume Ausset, Stéphan Clémençon, François Portier
2020	B	`conf`	Percolation-Based Detection of Anomalous Subgraphs in Complex Networks. IDA Corentin Larroche, Johan Mazel, Stéphan Clémençon
2020	J	`jnl`	Statistical learning based on Markovian data maximal deviation inequalities and learning rates. Ann. Math. Artif. Intell. Stéphan Clémençon, Patrice Bertail, Gabriela Ciolek
2020	A	`conf`	The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth measure. AISTATS Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
2020	J	`jnl`	Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling. CoRR Robin Vogel, Mastane Achab, Stéphan Clémençon, Charles Tillier
2020	B	`conf`	Weighted Emprirical Risk Minimization: Transfer Learning based on Importance Sampling. ESANN Robin Vogel, Mastane Achab, Stéphan Clémençon, Charles Tillier
2019	C	`conf`	A LSTM Approach to Detection of Autonomous Vehicle Hijacking. VEHITS Naman Singh Negi, Ons Jelassi, Stéphan Clémençon, Sebastian Fischmeister
2019	A	`conf`	Autoencoding any Data through Kernel Autoencoders. AISTATS Pierre Laforgue, Stéphan Clémençon, Florence d'Alché-Buc
2019	B	`conf`	Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach. ALT Mastane Achab, Anna Korba, Stéphan Clémençon
2019	J	`jnl`	Empirical Risk Minimization under Random Censorship: Theory and Practice. CoRR Guillaume Ausset, Stéphan Clémençon, François Portier
2019	C	`conf`	Functional Isolation Forest. ACML Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
2019	J	`jnl`	Functional Isolation Forest. CoRR Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon, Florence d'Alché-Buc
2019	A*	`conf`	On Medians of (Randomized) Pairwise Means. ICML Stéphan Clémençon, Pierre Laforgue, Patrice Bertail
2019	—	`conf`	On Tree-Based Methods for Similarity Learning. LOD Stéphan Clémençon, Robin Vogel
2019	J	`jnl`	On Tree-based Methods for Similarity Learning. CoRR Stéphan Clémençon, Robin Vogel
2019	J	`jnl`	Statistical Learning from Biased Training Samples. CoRR Pierre Laforgue, Stéphan Clémençon
2019	J	`jnl`	The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure. CoRR Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon
2019	—	`conf`	Trade-Offs in Large-Scale Distributed Tuplewise Estimation And Learning. ECML/PKDD (2) Robin Vogel, Aurélien Bellet, Stéphan Clémençon, Ons Jelassi, Guillaume Papa
2019	J	`jnl`	Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning. CoRR Robin Vogel, Aurélien Bellet, Stéphan Clémençon, Ons Jelassi, Guillaume Papa
2019	—	`conf`	Traffic Analysis Based on Bluetooth Passive Scanning. VTC Spring Safa Boudabous, Julian Garbiso, Bertrand Leroy, Stéphan Clémençon, Houda Labiod
2018	A*	`conf`	A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization. ICML Robin Vogel, Aurélien Bellet, Stéphan Clémençon
2018	J	`jnl`	A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization. CoRR Robin Vogel, Aurélien Bellet, Stéphan Clémençon
2018	J	`jnl`	Autoencoding any Data through Kernel Autoencoders. CoRR Pierre Laforgue, Stéphan Clémençon, Florence d'Alché-Buc
2018	A	`conf`	Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods. AISTATS Stéphan Clémençon, François Portier
2018	J	`jnl`	Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach. CoRR Mastane Achab, Anna Korba, Stéphan Clémençon
2018	Misc	`conf`	Generalization Bounds for Minimum Volume Set Estimation based on Markovian Data. ISAIM Patrice Bertail, Gabriela Ciolek, Stéphan Clémençon
2018	A*	`conf`	On Binary Classification in Extreme Regions. NeurIPS Hamid Jalalzai, Stéphan Clémençon, Anne Sabourin
2018	B	`conf`	On aggregation in ranking median regression. ESANN Stéphan Clémençon, Anna Korba
2018	C	`conf`	Profitable Bandits. ACML Mastane Achab, Stéphan Clémençon, Aurélien Garivier
2018	J	`jnl`	Profitable Bandits. CoRR Mastane Achab, Stéphan Clémençon, Aurélien Garivier
2018	B	`conf`	Ranking Median Regression: Learning to Order through Local Consensus. ALT Stéphan Clémençon, Anna Korba, Eric Sibony
2017	A	`conf`	A Learning Theory of Ranking Aggregation. AISTATS Anna Korba, Stéphan Clémençon, Eric Sibony
2017	A	`conf`	Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere. AISTATS Albert Thomas, Stéphan Clémençon, Alexandre Gramfort, Anne Sabourin
2017	J	`jnl`	EMOTHAW: A Novel Database for Emotional State Recognition From Handwriting and Drawing. IEEE Trans. Hum. Mach. Syst. Laurence Likforman-Sulem, Anna Esposito, Marcos Faúndez-Zanuy, Stéphan Clémençon, Gennaro Cordasco
2017	—	`conf`	Max K-Armed Bandit: On the ExtremeHunter Algorithm and Beyond. ECML/PKDD (2) Mastane Achab, Stéphan Clémençon, Aurélien Garivier, Anne Sabourin, Claire Vernade
2017	J	`jnl`	Max K-armed bandit: On the ExtremeHunter algorithm and beyond. CoRR Mastane Achab, Stéphan Clémençon, Aurélien Garivier, Anne Sabourin, Claire Vernade
2017	—	`conf`	Ranking Data with Continuous Labels through Oriented Recursive Partitions. NIPS Stéphan Clémençon, Mastane Achab
2017	J	`jnl`	Sparse representation of multivariate extremes with applications to anomaly detection. J. Multivar. Anal. Nicolas Goix, Anne Sabourin, Stéphan Clémençon
2016	J	`jnl`	An empirical comparison of V-fold penalisation and cross-validation for model selection in distribution-free regression. Pattern Anal. Appl. Charanpal Dhanjal, Nicolas Baskiotis, Stéphan Clémençon, Nicolas Usunier
2016	A*	`conf`	Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. ICML Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
2016	J	`jnl`	Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. CoRR Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
2016	C	`conf`	Learning from Survey Training Samples: Rate Bounds for Horvitz-Thompson Risk Minimizers. ACML Stéphan Clémençon, Patrice Bertail, Guillaume Papa
2016	—	`conf`	On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability. NIPS Guillaume Papa, Aurélien Bellet, Stéphan Clémençon
2016	J	`jnl`	Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics. J. Mach. Learn. Res. Stéphan Clémençon, Igor Colin, Aurélien Bellet
2016	A	`conf`	Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking. AISTATS Nicolas Goix, Anne Sabourin, Stéphan Clémençon
2015	J	`jnl`	A statistical network analysis of the HIV/AIDS epidemics in Cuba. Soc. Netw. Anal. Min. Stéphan Clémençon, Héctor de Arazoza, Fabrice Rossi, Viet-Chi Tran
2015	J	`jnl`	AUC Optimisation and Collaborative Filtering. CoRR Charanpal Dhanjal, Romaric Gaudel, Stéphan Clémençon
2015	B	`conf`	Adaptive Sampling for Incremental Optimization Using Stochastic Gradient Descent. ALT Guillaume Papa, Pascal Bianchi, Stéphan Clémençon
2015	B	`conf`	An Ensemble Learning Technique for Multipartite Ranking. ESANN Stéphan Clémençon, Sylvain Robbiano
2015	A*	`conf`	Collaborative Filtering with Localised Ranking. AAAI Charanpal Dhanjal, Romaric Gaudel, Stéphan Clémençon
2015	J	`jnl`	Extending Gossip Algorithms to Distributed Estimation of U-Statistics. CoRR Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
2015	—	`conf`	Extending Gossip Algorithms to Distributed Estimation of U-statistics. NIPS Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
2015	—	`ch.`	Extracting Style and Emotion from Handwriting. Advances in Neural Networks Laurence Likforman-Sulem, Anna Esposito, Marcos Faúndez-Zanuy, Stéphan Clémençon
2015	A*	`conf`	Learning the dependence structure of rare events: a non-asymptotic study. COLT Nicolas Goix, Anne Sabourin, Stéphan Clémençon
2015	A*	`conf`	MRA-based Statistical Learning from Incomplete Rankings. ICML Eric Sibony, Stéphan Clémençon, Jérémie Jakubowicz
2015	A	`conf`	On Anomaly Ranking and Excess-Mass Curves. AISTATS Nicolas Goix, Anne Sabourin, Stéphan Clémençon
2015	—	`conf`	SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk. NIPS Guillaume Papa, Stéphan Clémençon, Aurélien Bellet
2015	—	`conf`	Scalability of Stochastic Gradient Descent based on "Smart" Sampling Techniques. INNS Conference on Big Data Stéphan Clémençon, Aurélien Bellet, Ons Jelassi, Guillaume Papa
2015	J	`jnl`	Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics. CoRR Stéphan Clémençon, Aurélien Bellet, Igor Colin
2014	J	`jnl`	A statistical network analysis of the HIV/AIDS epidemics in Cuba. CoRR Stéphan Clémençon, Héctor de Arazoza, Fabrice Rossi, Viet-Chi Tran
2014	J	`jnl`	A statistical view of clustering performance through the theory of U-processes. J. Multivar. Anal. Stéphan Clémençon
2014	A*	`conf`	Anomaly Ranking as Supervised Bipartite Ranking. ICML Stéphan Clémençon, Sylvain Robbiano
2014	J	`jnl`	Building confidence regions for the ROC surface. Pattern Recognit. Lett. Stéphan Clémençon, Sylvain Robbiano
2014	J	`jnl`	Efficient eigen-updating for spectral graph clustering. Neurocomputing Charanpal Dhanjal, Romaric Gaudel, Stéphan Clémençon
2014	Misc	`conf`	Learning reputation in an authorship network. SAC Charanpal Dhanjal, Stéphan Clémençon
2014	—	`conf`	Multiresolution analysis of incomplete rankings with applications to prediction. IEEE BigData Eric Sibony, Stéphan Clémençon, Jérémie Jakubowicz
2014	A	`conf`	Online Matrix Completion Through Nuclear Norm Regularisation. SDM Charanpal Dhanjal, Romaric Gaudel, Stéphan Clémençon
2014	—	`conf`	Scaling up M-estimation via sampling designs: The Horvitz-Thompson stochastic gradient descent. IEEE BigData Stéphan Clémençon, Patrice Bertail, Emilie Chautru
2013	J	`jnl`	An empirical comparison of learning algorithms for nonparametric scoring: the TreeRank algorithm and other methods. Pattern Anal. Appl. Stéphan Clémençon, Marine Depecker, Nicolas Vayatis
2013	J	`jnl`	Learning Reputation in an Authorship Network. CoRR Charanpal Dhanjal, Stéphan Clémençon
2013	A	`conf`	Maximal Deviations of Incomplete U-statistics with Applications to Empirical Risk Sampling. SDM Stéphan Clémençon, Sylvain Robbiano, Jessica Tressou
2013	—	`conf`	On-line learning gossip algorithm in multi-agent systems with local decision rules. IEEE BigData Pascal Bianchi, Stéphan Clémençon, Gemma Morral, Jérémie Jakubowicz
2013	J	`jnl`	Ranking data with ordinal labels: optimality and pairwise aggregation. Mach. Learn. Stéphan Clémençon, Sylvain Robbiano, Nicolas Vayatis
2013	J	`jnl`	Ranking forests. J. Mach. Learn. Res. Stéphan Clémençon, Marine Depecker, Nicolas Vayatis
2013	A	`conf`	Scoring anomalies: a M-estimation formulation. AISTATS Stéphan Clémençon, Jérémie Jakubowicz
2012	J	`jnl`	Dissemination of Health Information within Social Networks CoRR Charanpal Dhanjal, Sandrine Blanchemanche, Stéphan Clémençon, Ákos Róna-Tas, Fabrice Rossi
2012	J	`jnl`	Hierarchical clustering for graph visualization CoRR Stéphan Clémençon, Héctor de Arazoza, Fabrice Rossi, Viet-Chi Tran
2012	J	`jnl`	Visual Mining of Epidemic Networks CoRR Stéphan Clémençon, Héctor de Arazoza, Fabrice Rossi, Viet-Chi Tran
2011	—	`conf`	A Data-Mining Approach to Travel Price Forecasting. ICMLA (1) Till Wohlfarth, Stéphan Clémençon, François Roueff, Xavier Casellato
2011	J	`jnl`	Adaptive partitioning schemes for bipartite ranking - How to grow and prune a ranking tree. Mach. Learn. Stéphan Clémençon, Marine Depecker, Nicolas Vayatis
2011	J	`jnl`	Avancées récentes dans le domaine de l'apprentissage d'ordonnancements. Rev. d'Intelligence Artif. Stéphan Clémençon, Marine Depecker, Nicolas Vayatis
2011	—	`conf`	Clustering Rankings in the Fourier Domain. ECML/PKDD (1) Stéphan Clémençon, Romaric Gaudel, Jérémie Jakubowicz
2011	B	`conf`	Hierarchical clustering for graph visualization. ESANN Stéphan Clémençon, Héctor de Arazoza, Fabrice Rossi, Viet-Chi Tran
2011	A	`conf`	Maximising the Quality of Influence. SDM Charanpal Dhanjal, Stéphan Clémençon
2011	A*	`conf`	Minimax Learning Rates for Bipartite Ranking and Plug-in Rules. ICML Sylvain Robbiano, Stéphan Clémençon
2011	—	`conf`	On U-processes and clustering performance. NIPS Stéphan Clémençon
2011	J	`jnl`	The Evolution of the Cuban HIV/AIDS Network CoRR Charanpal Dhanjal, Stéphan Clémençon, Héctor de Arazoza, Fabrice Rossi, Viet-Chi Tran
2011	—	`conf`	Visual Mining of Epidemic Networks. IWANN (2) Stéphan Clémençon, Héctor de Arazoza, Fabrice Rossi, Viet-Chi Tran
2010	—	`conf`	Kantorovich Distances between Rankings with Applications to Rank Aggregation. ECML/PKDD (1) Stéphan Clémençon, Jérémie Jakubowicz
2009	—	`conf`	AUC optimization and the two-sample problem. NIPS Stéphan Clémençon, Nicolas Vayatis, Marine Depecker
2009	B	`conf`	Adaptive Estimation of the Optimal ROC Curve and a Bipartite Ranking Algorithm. ALT Stéphan Clémençon, Nicolas Vayatis
2009	C	`conf`	Bagging Ranking Trees. ICMLA Stéphan Clémençon, Marine Depecker, Nicolas Vayatis
2009	A*	`conf`	Nonparametric estimation of the precision-recall curve. ICML Stéphan Clémençon, Nicolas Vayatis
2009	A	`conf`	On Partitioning Rules for Bipartite Ranking. AISTATS Stéphan Clémençon, Nicolas Vayatis
2009	J	`jnl`	Tree-based ranking methods. IEEE Trans. Inf. Theory Stéphan Clémençon, Nicolas Vayatis
2008	J	`jnl`	Approximate regenerative-block bootstrap for Markov chains. Comput. Stat. Data Anal. Patrice Bertail, Stéphan Clémençon
2008	B	`conf`	Approximation of the Optimal ROC Curve and a Tree-Based Ranking Algorithm. ALT Stéphan Clémençon, Nicolas Vayatis
2008	—	`conf`	Empirical performance maximization for linear rank statistics. NIPS Stéphan Clémençon, Nicolas Vayatis
2008	—	`conf`	On Bootstrapping the ROC Curve. NIPS Patrice Bertail, Stéphan Clémençon, Nicolas Vayatis
2008	—	`conf`	Overlaying classifiers: a practical approach for optimal ranking. NIPS Stéphan Clémençon, Nicolas Vayatis
2007	J	`jnl`	Ranking the Best Instances. J. Mach. Learn. Res. Stéphan Clémençon, Nicolas Vayatis
2005	—	`conf`	From Ranking to Classification: A Statistical View. GfKl Stéphan Clémençon, Gábor Lugosi, Nicolas Vayatis
2005	A*	`conf`	Ranking and Scoring Using Empirical Risk Minimization. COLT Stéphan Clémençon, Gábor Lugosi, Nicolas Vayatis