Stéphan Clémençon

According to our database1, Stéphan Clémençon authored at least 92 papers between 2005 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2020
A multivariate extreme value theory approach to anomaly clustering and visualization.
Comput. Stat., 2020

Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications.
CoRR, 2020

How Robust is the Median-of-Means? Concentration Bounds in Presence of Outliers.
CoRR, 2020

Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach.
CoRR, 2020

Learning Fair Scoring Functions: Fairness Definitions, Algorithms and Generalization Bounds for Bipartite Ranking.
CoRR, 2020

Weighted Empirical Risk Minimization: Sample Selection Bias Correction based on Importance Sampling.
CoRR, 2020

Statistical learning based on Markovian data maximal deviation inequalities and learning rates.
Ann. Math. Artif. Intell., 2020

Percolation-Based Detection of Anomalous Subgraphs in Complex Networks.
Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

Distributed online Data Anomaly Detection for connected vehicles.
Proceedings of the 2020 International Conference on Artificial Intelligence in Information and Communication, 2020

Identifying the "right" level of explanation in a given situation.
Proceedings of the First International Workshop on New Foundations for Human-Centered AI (NeHuAI) co-located with 24th European Conference on Artificial Intelligence (ECAI 2020), 2020

A Multiclass Classification Approach to Label Ranking.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth measure.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Statistical Learning from Biased Training Samples.
CoRR, 2019

Empirical Risk Minimization under Random Censorship: Theory and Practice.
CoRR, 2019

Traffic Analysis Based on Bluetooth Passive Scanning.
Proceedings of the 89th IEEE Vehicular Technology Conference, 2019

A LSTM Approach to Detection of Autonomous Vehicle Hijacking.
Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems, 2019

Trade-Offs in Large-Scale Distributed Tuplewise Estimation And Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

On Tree-Based Methods for Similarity Learning.
Proceedings of the Machine Learning, Optimization, and Data Science, 2019

On Medians of (Randomized) Pairwise Means.
Proceedings of the 36th International Conference on Machine Learning, 2019

Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach.
Proceedings of the Algorithmic Learning Theory, 2019

Autoencoding any Data through Kernel Autoencoders.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Functional Isolation Forest.
Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018
On Binary Classification in Extreme Regions.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Generalization Bounds for Minimum Volume Set Estimation based on Markovian Data.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2018

A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization.
Proceedings of the 35th International Conference on Machine Learning, 2018

On aggregation in ranking median regression.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Ranking Median Regression: Learning to Order through Local Consensus.
Proceedings of the Algorithmic Learning Theory, 2018

Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Profitable Bandits.
Proceedings of The 10th Asian Conference on Machine Learning, 2018

2017
EMOTHAW: A Novel Database for Emotional State Recognition From Handwriting and Drawing.
IEEE Trans. Hum. Mach. Syst., 2017

Sparse representation of multivariate extremes with applications to anomaly detection.
J. Multivar. Anal., 2017

Max K-Armed Bandit: On the ExtremeHunter Algorithm and Beyond.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Ranking Data with Continuous Labels through Oriented Recursive Partitions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

A Learning Theory of Ranking Aggregation.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
An empirical comparison of V-fold penalisation and cross-validation for model selection in distribution-free regression.
Pattern Anal. Appl., 2016

Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics.
J. Mach. Learn. Res., 2016

On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Learning from Survey Training Samples: Rate Bounds for Horvitz-Thompson Risk Minimizers.
Proceedings of The 8th Asian Conference on Machine Learning, 2016

2015
A statistical network analysis of the HIV/AIDS epidemics in Cuba.
Soc. Netw. Anal. Min., 2015

AUC Optimisation and Collaborative Filtering.
CoRR, 2015

SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Extending Gossip Algorithms to Distributed Estimation of U-statistics.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Scalability of Stochastic Gradient Descent based on "Smart" Sampling Techniques.
Proceedings of the INNS Conference on Big Data 2015, 2015

MRA-based Statistical Learning from Incomplete Rankings.
Proceedings of the 32nd International Conference on Machine Learning, 2015

An Ensemble Learning Technique for Multipartite Ranking.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Learning the dependence structure of rare events: a non-asymptotic study.
Proceedings of The 28th Conference on Learning Theory, 2015

Adaptive Sampling for Incremental Optimization Using Stochastic Gradient Descent.
Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

On Anomaly Ranking and Excess-Mass Curves.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Collaborative Filtering with Localised Ranking.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Building confidence regions for the ROC surface.
Pattern Recognit. Lett., 2014

A statistical view of clustering performance through the theory of U-processes.
J. Multivar. Anal., 2014

Efficient eigen-updating for spectral graph clustering.
Neurocomputing, 2014

Online Matrix Completion Through Nuclear Norm Regularisation.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Learning reputation in an authorship network.
Proceedings of the Symposium on Applied Computing, 2014

Anomaly Ranking as Supervised Bipartite Ranking.
Proceedings of the 31th International Conference on Machine Learning, 2014

Multiresolution analysis of incomplete rankings with applications to prediction.
Proceedings of the 2014 IEEE International Conference on Big Data, 2014

Scaling up M-estimation via sampling designs: The Horvitz-Thompson stochastic gradient descent.
Proceedings of the 2014 IEEE International Conference on Big Data, 2014

2013
An empirical comparison of learning algorithms for nonparametric scoring: the TreeRank algorithm and other methods.
Pattern Anal. Appl., 2013

Ranking data with ordinal labels: optimality and pairwise aggregation.
Mach. Learn., 2013

Ranking forests.
J. Mach. Learn. Res., 2013

Maximal Deviations of Incomplete U-statistics with Applications to Empirical Risk Sampling.
Proceedings of the 13th SIAM International Conference on Data Mining, 2013

On-line learning gossip algorithm in multi-agent systems with local decision rules.
Proceedings of the 2013 IEEE International Conference on Big Data, 2013

Scoring anomalies: a M-estimation formulation.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Dissemination of Health Information within Social Networks
CoRR, 2012

2011
Avancées récentes dans le domaine de l'apprentissage d'ordonnancements.
Rev. d'Intelligence Artif., 2011

Adaptive partitioning schemes for bipartite ranking - How to grow and prune a ranking tree.
Mach. Learn., 2011

The Evolution of the Cuban HIV/AIDS Network
CoRR, 2011

Maximising the Quality of Influence.
Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Clustering Rankings in the Fourier Domain.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

On U-processes and clustering performance.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Visual Mining of Epidemic Networks.
Proceedings of the Advances in Computational Intelligence, 2011

A Data-Mining Approach to Travel Price Forecasting.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

Minimax Learning Rates for Bipartite Ranking and Plug-in Rules.
Proceedings of the 28th International Conference on Machine Learning, 2011

Hierarchical clustering for graph visualization.
Proceedings of the ESANN 2011, 2011

2010
Kantorovich Distances between Rankings with Applications to Rank Aggregation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009
Tree-based ranking methods.
IEEE Trans. Inf. Theory, 2009

On Partitioning Rules for Bipartite Ranking.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

AUC optimization and the two-sample problem.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Bagging Ranking Trees.
Proceedings of the International Conference on Machine Learning and Applications, 2009

Nonparametric estimation of the precision-recall curve.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Adaptive Estimation of the Optimal ROC Curve and a Bipartite Ranking Algorithm.
Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009

2008
Approximate regenerative-block bootstrap for Markov chains.
Comput. Stat. Data Anal., 2008

Overlaying classifiers: a practical approach for optimal ranking.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Empirical performance maximization for linear rank statistics.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

On Bootstrapping the ROC Curve.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Approximation of the Optimal ROC Curve and a Tree-Based Ranking Algorithm.
Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

2007
Ranking the Best Instances.
J. Mach. Learn. Res., 2007

2005
From Ranking to Classification: A Statistical View.
Proceedings of the From Data and Information Analysis to Knowledge Engineering, 2005

Ranking and Scoring Using Empirical Risk Minimization.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005


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