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hal-02496048v2  Reports
Rachid Guennouni Hassani, Alexis Gilles, Emmanuel Lassalle, Arthur Dénouveaux. Predicting Stock Returns with Batched AROW
[Research Report] Machina Capital. 2020
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hal-02382232v1  Conference papers
Tanguy Levent, Philippe Preux, Erwan Le Pennec, Jordi Badosa, Gonzague Henri et al.  Energy Management for Microgrids: a Reinforcement Learning Approach
ISGT-Europe 2019 - IEEE PES Innovative Smart Grid Technologies Europe, Sep 2019, Bucharest, France. pp.1-5, ⟨10.1109/ISGTEurope.2019.8905538⟩
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hal-02446200v1  Preprints, Working Papers, ...
Nicolas Aussel, Sophie Chabridon, Yohan Petetin. Combining federated and active learning for communication-efficient distributed failure prediction in aeronautics
2019
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hal-02282219v1  Conference papers
Nicolas Aussel, Fabian Dubourvieux, Yohan Petetin. Spatio-temporal convolutional neural networks for failure prediction
GRETSI 2019: XXVIIème colloque francophone de traitement du signal et des images, Aug 2019, Lille, France. pp.1-5
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tel-03046826v1  Theses
Stratis Limnios. Etude de Dégénérescence de Graph appliqué à l'Apprentissage Automatique Avancé et Résultats Théoriques relatifs
Artificial Intelligence [cs.AI]. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAX038⟩
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tel-03485159v1  Theses
Anas Barakat. Contributions to non-convex stochastic optimization and reinforcement learning
Machine Learning [stat.ML]. Institut Polytechnique de Paris, 2021. English. ⟨NNT : 2021IPPAT030⟩
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tel-03485328v1  Theses
Louis Faury. Variance-sensitive confidence intervals for parametric and offline bandits
Statistics [math.ST]. Institut Polytechnique de Paris, 2021. English. ⟨NNT : 2021IPPAT046⟩
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tel-03650864v1  Theses
Guillaume Staerman. Functional anomaly detection and robust estimation
Machine Learning [stat.ML]. Institut Polytechnique de Paris, 2022. English. ⟨NNT : 2022IPPAT021⟩
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hal-02423445v1  Journal articles
Geneviève Robin, Olga Klopp, Julie Josse, Éric Moulines, Robert Tibshirani. Main effects and interactions in mixed and incomplete data frames
Journal of the American Statistical Association, Taylor & Francis, 2019, ⟨10.1080/01621459.2019.1623041⟩
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hal-03559386v1  Conference papers
Stéphan Clémençon, Guillaume Ausset, François Portier. Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications
24th International Conference on Artificial Intelligence and Statistics ( AISTATS2021), 2021, Virtual, France
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hal-03559387v1  Conference papers
Stéphan Clémençon, Robin Vogel, Mastane Achab, Charles Tillier. Weighted Empirical Risk Minimization: Transfer Learning based on Importance Sampling
28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning ( ESANN 2020), 2020, Bruges (on line), Belgium
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hal-03559370v1  Conference papers
Stéphan Clémençon, Patrice Bertail, Yannick Guyonvarch, Nathan Noiry. Learning from Biased Data: A Semi-Parametric Approach
38th International Conference on Machine Learning (ICML 2021), 2021, Bilbao, Spain
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hal-03559365v1  Journal articles
Guillaume Ausset, Stéphan Clémençon, François Portier. Empirical Risk Minimization under Random Censorship
Journal of Machine Learning Research, Microtome Publishing, 2022
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tel-02379295v1  Theses
Rémi Besson. Decision making strategy for antenatal echographic screening of foetal abnormalities using statistical learning
Applications [stat.AP]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLX037⟩
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hal-02185060v1  Preprints, Working Papers, ...
Maël Chiapino, Stéphan Clémençon, Vincent Feuillard, Anne Sabourin. A Multivariate Extreme Value Theory Approach to Anomaly Clustering and Visualization
2019
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hal-02532344v1  Preprints, Working Papers, ...
Michel Deudon. Sur notre alimentation, nos biais et nos saisons: Vers des recettes durables et responsables
2020
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tel-03544727v1  Theses
Jules Depersin. Statistical and Computational Complexities of Robust and High-Dimensional Estimation Problems
Statistics [math.ST]. Institut Polytechnique de Paris, 2021. English. ⟨NNT : 2021IPPAG009⟩
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hal-03001057v1  Conference papers
Nicolas Donati, Abhishek Sharma, Maks Ovsjanikov. Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence
CVPR, Jun 2020, Seattle (virtual), United States
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tel-03380450v1  Theses
Laura Tinsi. Modeling and optimal strategies in short-term energy markets
Optimization and Control [math.OC]. Institut Polytechnique de Paris, 2021. English. ⟨NNT : 2021IPPAG005⟩
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tel-02430579v2  Theses
Nicolas Brosse. Autour de l'algorithme du Langevin : extensions et applications
Machine Learning [stat.ML]. Université Paris Saclay (COmUE), 2019. Français. ⟨NNT : 2019SACLX014⟩
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hal-03333516v3  Conference papers
Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Geneviève Robin. Federated Expectation Maximization with heterogeneity mitigation and variance reduction
NeurIPS 2021 - 35th Conference on Neural Information Processing Systems, Dec 2021, Sydney, Australia
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hal-03021394v2  Conference papers
Gersende Fort, Eric Moulines, Hoi-To Wai. Geom-SPIDER-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization
2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2021, Toronto, Canada
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hal-02509621v2  Preprints, Working Papers, ...
Gersende Fort, Eric Moulines, Pierre Gach. Fast incremental expectation-maximization algorithm: √N iterations for an epsilon-stationary point ?
2021
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hal-03029700v1  Conference papers
Gersende Fort, Eric Moulines, Hoi-To Wai. A Stochastic Path-Integrated Differential EstimatoR Expectation Maximization Algorithm
NeurIPS 2020 - 34th Conference on Neural Information Processing Systems, Dec 2020, Vancouver / Virtuel, Canada
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hal-03183775v2  Conference papers
Gersende Fort, E Moulines. The perturbed prox-preconditioned spider algorithm: non-asymptotic convergence bounds
SSP 2021 - IEEE Statistical Signal Processing Workshop, Jul 2021, Rio de Janeiro, Brazil
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hal-03183774v2  Conference papers
Gersende Fort, Eric Moulines. The Perturbed Prox-Preconditioned SPIDER algorithm for EM-based large scale learning
SSP 2021 - IEEE Statistical Signal Processing Workshop, Jul 2021, Rio de Janeiro, Brazil
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tel-03084452v1  Theses
Boris Muzellec. Leveraging regularization, projections and elliptical distributions in optimal transport
Optimization and Control [math.OC]. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAG009⟩
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tel-03015285v1  Theses
Gautier Appert. Information k-means, fragmentation and syntax analysis. A new approach to unsupervised machine learning
Machine Learning [stat.ML]. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAG011⟩
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tel-02913708v1  Theses
Mamadou Dione. Prévision court terme de la production éolienne par Machine learning
Statistiques [math.ST]. Institut Polytechnique de Paris, 2020. Français. ⟨NNT : 2020IPPAG004⟩
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tel-02893465v1  Theses
Badr-Eddine Cherief-Abdellatif. Contributions to the theoretical study of variational inference and robustness
Statistics [math.ST]. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAG001⟩