ML at Aussois : Autumn School on Recent Advances in Machine Learning

16-21 Nov 2025 Aussois (France)

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Program

Week Sun. 16 Mon. 17 Tue. 18 Wed. 19 Thu. 20 Fri. 21 List

Wednesday, November 19, 2025

07:00

08:00

09:00

10:00

11:00

12:00

13:00

14:00

15:00

16:00

17:00

18:00

19:00

20:00

›7:30 (1h)

Breakfast

7:30 - 8:30 (1h)

Breakfast

›8:45 (1h)

The Marauders Map of adversarial examples: State of knowledge on evasion attacks in machine learning (3/3)
Rafael Pinot

› Conference room

8:45 - 9:45 (1h)

The Marauders Map of adversarial examples: State of knowledge on evasion attacks in machine learning (3/3)

Conference room

Rafael Pinot

›9:45 (1h)

Convex Optimization and First-Order Algorithms for Data Science (3/3)
Adrien Taylor

› Conference room

9:45 - 10:45 (1h)

Convex Optimization and First-Order Algorithms for Data Science (3/3)

Conference room

Adrien Taylor

›10:45 (30min)

Coffee break

10:45 - 11:15 (30min)

Coffee break

›11:15 (1h)

Conformal prediction - from a general introduction towards conditional guarantees (1/3)
Aymeric Dieuleveut

› Conference room

11:15 - 12:15 (1h)

Conformal prediction - from a general introduction towards conditional guarantees (1/3)

Conference room

Aymeric Dieuleveut

›12:30 (1h)

Lunch

12:30 - 13:30 (1h)

Lunch

›13:30 (2h)

Free time

13:30 - 15:30 (2h)

Free time

›15:30 (1h15)

CT - Session 3

15:30 - 16:45 (1h15)

CT - Session 3

› Approche bayésienne pour évaluer l'incertitude et la robustesse d'indicateurs de graphes en neurosciences - Alice Chevaux, INRIA 15:30-15:55 (25min)

› Iterated forward scheme to construct proposals for sequential Monte Carlo algorithms - Sylvain Procope-Mamert, Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] 15:55-16:20 (25min)

› PAC-Bayesian Reconstruction Guarantees for Variational Autoencoders for Time Series - Chloé Hashimoto-Cullen, Laboratoire de Probabilités, Statistique et Modélisation 16:20-16:45 (25min)

›17:00 (2h15)

Poster session

17:00 - 19:15 (2h15)

Poster session

› Benign landscape for Burer-Monteiro factorizations of MaxCut-type semidefinite programs - Faniriana Rakoto Endor, CEntre de REcherches en MAthématiques de la DEcision 17:00-19:15 (2h15)

› Validation of Computer Codes via Mixture Model Estimation - Negar Soleimani, AgroParisTech 17:00-19:15 (2h15)

› Variational Inference with Mixture of Isotropic Gaussians - Marguerite Petit Talamon, Centre de Recherche en Économie et Statistique 17:00-19:15 (2h15)

› Statistical and Geometrical properties of regularized Kernel Kullback-Leibler divergence - Clémentine Chazal, Centre de Recherche en Économie et Statistique 17:00-19:15 (2h15)

› Gradient-free variational inference within exponential families using least squares regression with applications on discrete distributions and likelihood-free models - Le Fay Yvan, Centre de Recherche en Économie et Statistique 17:00-19:15 (2h15)

› Understanding the bias induced by Local Differential Privacy - Jean Dufraiche, MAGNET (Machine Learning in Information Networks) 17:00-19:15 (2h15)

› TAMIS: Tailored Membership Inference Attacks on Synthetic Data - Paul Andrey, MAGNET (Machine Learning in Information Networks) 17:00-19:15 (2h15)

› Growing Neural Networks: Spotting Expressivity Bottlenecks and Fixing Them Optimally - Théo Rudkiewicz, TAU team 17:00-19:15 (2h15)

› Joint estimation of bipartite network collections. Application to plant-pollinator networks - Louis LACOSTE, Mathématiques et Informatique Appliquées 17:00-19:15 (2h15)

› Harnessing Mixed Features for Imbalance Data Oversampling: Application to Bank Customers Scoring - Abdoulaye SAKHO, Laboratoire de Probabilités, Statistique et Modélisation, Artefact [Paris] 17:00-19:15 (2h15)

› Hallucinations in statistical inverse problems: discussion, characterization and exploration in PET imaging - Ramy Merabet, Centre Borelli 17:00-19:15 (2h15)

› Streaming Federated Learning with Markovian Data - Tan-Khiem HUYNH, Centre Inria de Lyon 17:00-19:15 (2h15)

› Mask-Conditional Coverage for General Missing Data Mechanisms - Jiarong FAN, Université Paris Saclay 17:00-19:15 (2h15)

› Weakly supervised learning methods for the classification of patients from flow cytometry data - Pierre-André Mikem, Laboratoire de Mathématiques d'Orsay, Metafora biosystems 17:00-19:15 (2h15)

› Group-Specific Thresholding to Preserve Fairness of Stochastic Classifiers - Shreya Venugopal, Machine Learning in Information Networks 17:00-19:15 (2h15)

› Better Capturing Interactions between Products in Retail: Revisited Negative Sampling for Basket Choice Modeling - Vincent Auriau, Mathématiques et Informatique pour la Complexité et les Systèmes, Artefact Research Center 17:00-19:15 (2h15)

› Time Series Motif Discovery: A Comprehensive Evaluation - Valerio Guerrini, CB - Centre Borelli - UMR 9010 17:00-19:15 (2h15)

› Set To Be Fair: Set-Valued Classification Under Fairness Constraints - Eyal Cohen, Laboratoire de Probabilités, Statistique et Modélisation, Mathématiques Appliquées Paris 5, Statistique, Analyse et Modélisation Multidisciplinaire (SAmos-Marin Mersenne) 17:00-19:15 (2h15)

›19:30 (1h)

Dinner

19:30 - 20:30 (1h)

Dinner

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