:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Even, Mathieu, Berenfeld, Clément, Bleistein, Linus, Cebere, Tudor, Josse, Julie, Bellet, Aurélien
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2602.02819
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Privacy Auditing with Zero (0) Training Run
by: Cebere, Tudor, et al.
Published: (2026)

Optimal Transport with Heterogeneously Missing Data
by: Bleistein, Linus, et al.
Published: (2025)

Model Agnostic Differentially Private Causal Inference
by: Lebeda, Christian Janos, et al.
Published: (2025)

Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model
by: Cebere, Tudor, et al.
Published: (2024)

Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis
by: Khellaf, Rémi, et al.
Published: (2024)

Optimal Transport under Group Fairness Constraints
by: Bleistein, Linus, et al.
Published: (2026)

Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees
by: Lebeda, Christian Janos, et al.
Published: (2026)

Private Rate-Constrained Optimization with Applications to Fair Learning
by: Yaghini, Mohammad, et al.
Published: (2025)

Principled Federated Random Forests for Heterogeneous Data
by: Khellaf, Rémi, et al.
Published: (2026)

Federated Causal Inference from Multi-Site Observational Data via Propensity Score Aggregation
by: Khellaf, Rémi, et al.
Published: (2025)

Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging
by: Cyffers, Edwige, et al.
Published: (2022)

Preference-based Conditional Treatment Effects and Policy Learning
by: Parnas, Dovid, et al.
Published: (2026)

On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
by: Bleistein, Linus, et al.
Published: (2023)

Rethinking the Win Ratio: A Causal Framework for Hierarchical Outcome Analysis
by: Even, Mathieu, et al.
Published: (2025)

A Unified Framework for the Transportability of Population-Level Causal Measures
by: Boughdiri, Ahmed, et al.
Published: (2025)

Causal Meta-Analysis: Rethinking the Foundations of Evidence-Based Medicine
by: Berenfeld, Clément, et al.
Published: (2025)

Privacy in Theory, Bugs in Practice: Grey-Box Auditing of Differential Privacy Libraries
by: Cebere, Tudor, et al.
Published: (2026)

Privacy Attacks in Decentralized Learning
by: Mrini, Abdellah El, et al.
Published: (2024)

Set-Valued Policy Learning
by: Fuentes-Vicente, Laura, et al.
Published: (2026)

Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration
by: Pierquin, Clément, et al.
Published: (2023)

Privacy Amplification Through Synthetic Data: Insights from Linear Regression
by: Pierquin, Clément, et al.
Published: (2025)

Treatment Effect Estimation in Causal Survival Analysis: Practical Recommendations
by: Voinot, Charlotte, et al.
Published: (2025)

MMD-based Variable Importance for Distributional Random Forest
by: Bénard, Clément, et al.
Published: (2023)

Dynamical Survival Analysis with Controlled Latent States
by: Bleistein, Linus, et al.
Published: (2024)

Privacy Amplification Persists under Unlimited Synthetic Data Release
by: Pierquin, Clément, et al.
Published: (2026)

Range Membership Inference Attacks
by: Tao, Jiashu, et al.
Published: (2024)

Loss Gap Parity for Fairness in Heterogeneous Federated Learning
by: Erraji, Brahim, et al.
Published: (2026)

Imitative Membership Inference Attack
by: Du, Yuntao, et al.
Published: (2025)

Differentially Private Decentralized Learning with Random Walks
by: Cyffers, Edwige, et al.
Published: (2024)

Learning with Hidden Factorial Structure
by: Arnal, Charles, et al.
Published: (2024)

Sequential Membership Inference Attacks
by: Michel, Thomas, et al.
Published: (2026)

Evaluating Membership Inference Attacks in heterogeneous-data setups
by: van Dartel, Bram, et al.
Published: (2025)

The Relative Gaussian Mechanism and its Application to Private Gradient Descent
by: Hendrikx, Hadrien, et al.
Published: (2023)

Membership Inference Attacks on Sequence Models
by: Rossi, Lorenzo, et al.
Published: (2025)

Membership Inference Attacks for Unseen Classes
by: Thaker, Pratiksha, et al.
Published: (2025)

Membership Inference Attacks Beyond Overfitting
by: Khalil, Mona, et al.
Published: (2025)

Cascading and Proxy Membership Inference Attacks
by: Du, Yuntao, et al.
Published: (2025)

On Gossip Algorithms for Machine Learning with Pairwise Objectives
by: Colin, Igor, et al.
Published: (2026)

Differentially Private and Federated Structure Learning in Bayesian Networks
by: Fehri, Ghita Fassy El, et al.
Published: (2025)

Meta-learning of shared linear representations beyond well-specified linear regression
by: Even, Mathieu, et al.
Published: (2025)