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Universal aggregation of permutations

 Ekhine Irurozki , Stéphan Clémençon
2022
Proceedings/Recueil des communications hal-03972357v1
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On Binary Classification in Extreme Regions

 Hamid Jalalzai , Stéphan Clémençon , Anne Sabourin
2018
Proceedings/Recueil des communications hal-01932813v1

Bagging Ranking Trees

 Stéphan Clémençon , Marine Depecker , Nicolas Vayatis
IEEE, pp.658-663, 2009, ⟨10.1109/ICMLA.2009.14⟩
Proceedings/Recueil des communications hal-02107271v1
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Learning the dependence structure of rare events: a non-asymptotic study

 Nicolas Goix , Anne Sabourin , Stéphan Clémençon
40, pp.1 - 18, 2015
Proceedings/Recueil des communications hal-02107454v1
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A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization

 Robin Vogel , Aurélien Bellet , Stéphan Clémençon
2018
Proceedings/Recueil des communications hal-01922988v1
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Maximal Deviations of Incomplete U-statistics with Applications to Empirical Risk Sampling

 Stéphan Clémençon , Sylvain Robbiano , Jessica Tressou
2013
Pré-publication, Document de travail hal-00809487v1

Continuous Ranking trough Oriented Recursive Partitions

 Stéphan Clémençon , Mastane Achab
NIPS, Dec 2017, Longbeach, United States
Communication dans un congrès hal-02287581v1

Machine Learning for Survival Analysis: Empirical Risk Minimization for Censored Distribution-Free Regression with Applications.

 Guillaume Ausset , Stéphan Clémençon , François Portier
NIPS, Workshop ML4H, Dec 2018, Montréal, Canada
Communication dans un congrès hal-02287991v1

Learning from Survey Training Samples: Rate Bounds for Horvitz-Thompson Risk Minimizers

 Stéphan Clémençon , P. Bertail , Guillaume Papa
ACML, Dec 2016, Hamilton, New Zealand
Communication dans un congrès hal-02287361v1

Calibrating SVMs with V-fold penalization

 Stéphan Clémençon , Nicolas Baskiotis , Nicolas Usunier
Neural Information Processing Systems workshop on New Frontiers in Model Order Selection, Dec 2011, Sierra Nevada, Spain
Communication dans un congrès hal-01288139v1

On Survey Sampling and Empirical Risk Minimization

 Stéphan Clémençon , P. Bertail , Emilie Chautru
Statistics, 2015
Article dans une revue hal-02286817v1
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On Anomaly Ranking and Excess-Mass Curves

 Nicolas Goix , Anne Sabourin , Stéphan Clémençon
2014
Pré-publication, Document de travail hal-01113521v1

Overlaying Classifiers: A Practical Approach to Optimal Scoring

 Stéphan Clémençon , Nicolas Vayatis
Constructive Approximation, 2010, 32 (3), pp.619-648. ⟨10.1007/s00365-010-9084-9⟩
Article dans une revue istex hal-02107294v1
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Clustering Rankings in the Fourier Domain

 Stéphan Clémençon , Romaric Gaudel , Jérémie Jakubowicz
ECML - European Conference on Machine Learning - 2011, Sep 2011, Athènes, Greece. pp.343-358, ⟨10.1007/978-3-642-23780-5_32⟩
Communication dans un congrès hal-00741210v1

Approximation of the Optimal ROC Curve and a Tree-Based Ranking Algorithm

 Stéphan Clémençon , Nicolas Vayatis
Approximation of the Optimal ROC Curve and a Tree-Based Ranking Algorithm, pp.22-37, 2008, ⟨10.1007/978-3-540-87987-9_7⟩
Chapitre d'ouvrage istex hal-02107171v1
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A Multiresolution Analysis Framework for the Statistical Analysis of Incomplete Rankings

 Eric Sibony , Stéphan Clémençon , Jérémie Jakubowicz
2016
Pré-publication, Document de travail hal-01249862v1

Adaptive estimation of the transition density of a regular Markov chain.

 Stéphan Clémençon
Mathematical Methods of Statistics, 2000, 9, pp.No 4, 323-357
Article dans une revue hal-00111268v1

Regenerative Block-Bootstrap for Markov Chains

 Stéphan Clémençon , Patrice Bertail
Bernoulli, 2006, 12, pp.No 4, 689-712
Article dans une revue hal-00111272v1
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Empirical processes in survey sampling

 Patrice Bertail , Emilie Chautru , Stéphan Clémençon
2013
Pré-publication, Document de travail hal-00989585v1

Regenerative block bootstrap for Markov chains

 Patrice Bertail , Stéphan Clémençon
Bernoulli, 2006, 12 (4), pp.689-712. ⟨10.3150/bj/1155735932⟩
Article dans une revue hal-02107125v1

Integration of time as a description parameter in risk characterisation : application to methyl mercury

 Philippe Verger , Jessica Tressou , Stéphan Clémençon
Regulatory Toxicology and Pharmacology, 2007, 49 (1), pp.25-30. ⟨10.1016/j.yrtph.2007.04.010⟩
Article dans une revue istex hal-01068804v1
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Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications

 Stéphan Clémençon , Guillaume Ausset , François Portier
2021
Proceedings/Recueil des communications hal-03559386v1
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Empirical performance maximization for linear rank statistics

 Stéphan Clémençon , Nicolas Vayatis
2009, Advances in Neural Information Processing Systems 21
Proceedings/Recueil des communications hal-02107196v1
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Ranking Multi-Class Data: Optimality and Pairwise Aggregation

 Stéphan Clémençon , Sylvain Robbiano , Nicolas Vayatis
2011
Pré-publication, Document de travail hal-00630496v1

A Network Analysis of the HIV/AIDS Epidemics in Cuba

 Stéphan Clémençon , H. de Arazoza , Fabrice Rossi , Viet Chi Tran
Social Network Analysis and Mining, 2014
Article dans une revue hal-02286854v1

Max K-Armed Bandit: On the ExtremeHunter Algorithm and Beyond

 Mastane Achab , Stéphan Clémençon , Aurélien Garivier , Anne Sabourin , Claire Vernade
Machine Learning and Knowledge Discovery in Databases ECML PKDD 2017, 2017, pp.389-404
Article dans une revue hal-02023085v1
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What are the best systems? New perspectives on NLP Benchmarking

 Ekhine Irurozki , Pierre Colombo , Nathan Noiry , Stéphan Clémençon
Conference on Neural Information Processing Systems, 2022, New Orleans, United States
Communication dans un congrès hal-04253771v1

Method for providing with a score an object, and decision-support system

 Stéphan Clémençon , N. Vayatis
United States, Patent n° : US9235805B2. SC:TREERANK0. 2012
Brevet hal-02412555v1

Pseudo-regenerative block-bootstrap for hidden Markov chains

 Stéphan Clémençon , A. Garivier , J. Tressou
IEEE, pp.465-468, 2009
Proceedings/Recueil des communications hal-02107248v1
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Comment limiter les biais des algorithmes ?

 Charles-Albert With , Driss Lehalle , Marie Lamrani , David Brière , Winston Bounie , et al.
Les cahiers Louis Bachelier, 2020, The challenges of new technologies in finance, 36
Article dans une revue hal-02878302v1
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