Toward a route detection method base on detail call records. - Hadrien Hendrikx; Miguel Núñez del Prado Cortez (LA-CCI, 2016)

Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning. - El Mahdi El Mhamdi; Rachid Guerraoui; Hadrien Hendrikx; Alexandre Maurer (NIPS, 2017)

Can AIs learn to avoid human interruption? - El Mahdi El Mhamdi; Rachid Guerraoui; Hadrien Hendrikx; Alexandre Maurer (CoRR, 2017)

Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives. - Hadrien Hendrikx; Francis R. Bach; Laurent Massoulié (AISTATS, 2019)

An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums. - Hadrien Hendrikx; Francis R. Bach; Laurent Massoulié (NeurIPS, 2019)

Asynchronous Accelerated Proximal Stochastic Gradient for Strongly Convex Distributed Finite Sums. - Hadrien Hendrikx; Francis R. Bach; Laurent Massoulié (CoRR, 2019)

Who started this rumor? Quantifying the natural differential privacy guarantees of gossip protocols. - Aurélien Bellet; Rachid Guerraoui; Hadrien Hendrikx (CoRR, 2019)

Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization. - Hadrien Hendrikx; Lin Xiao; Sébastien Bubeck; Francis R. Bach; Laurent Massoulié (ICML, 2020)

Dual-Free Stochastic Decentralized Optimization with Variance Reduction. - Hadrien Hendrikx; Francis R. Bach; Laurent Massoulié (NeurIPS, 2020)

Who Started This Rumor? Quantifying the Natural Differential Privacy of Gossip Protocols. - Aurélien Bellet; Rachid Guerraoui; Hadrien Hendrikx (DISC, 2020)

Asynchrony and Acceleration in Gossip Algorithms. - Mathieu Even; Hadrien Hendrikx; Laurent Massoulié (CoRR, 2020)

Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction. - Radu-Alexandru Dragomir; Mathieu Even; Hadrien Hendrikx (ICML, 2021)

Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms. - Mathieu Even; Raphaël Berthier; Francis R. Bach; Nicolas Flammarion; Hadrien Hendrikx; Pierre Gaillard; Laurent Massoulié; Adrien B. Taylor (NeurIPS, 2021)

Decentralized Optimization with Heterogeneous Delays: a Continuous-Time Approach. - Mathieu Even; Hadrien Hendrikx; Laurent Massoulié (CoRR, 2021)

A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip. - Mathieu Even; Raphaël Berthier; Francis R. Bach; Nicolas Flammarion; Pierre Gaillard; Hadrien Hendrikx; Laurent Massoulié; Adrien B. Taylor (CoRR, 2021)

An Optimal Algorithm for Decentralized Finite-Sum Optimization. - Hadrien Hendrikx; Francis R. Bach; Laurent Massoulié (SIAM J. Optim., 2021)

Accelerated Methods for Distributed Optimization. (Méthodes Accélérées pour l'Optimisation Distribuée). - Hadrien Hendrikx (2021)

A principled framework for the design and analysis of token algorithms. - Hadrien Hendrikx (AISTATS, 2023)

Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees. - Anastasia Koloskova; Hadrien Hendrikx; Sebastian U. Stich (ICML, 2023)

Beyond spectral gap (extended): The role of the topology in decentralized learning. - Thijs Vogels; Hadrien Hendrikx; Martin Jaggi (CoRR, 2023)

Beyond Spectral Gap: The Role of the Topology in Decentralized Learning. - Thijs Vogels; Hadrien Hendrikx; Martin Jaggi (J. Mach. Learn. Res., 2023)

The Relative Gaussian Mechanism and its Application to Private Gradient Descent. - Hadrien Hendrikx; Paul Mangold; Aurélien Bellet (AISTATS, 2024)

Byzantine-Robust Gossip: Insights from a Dual Approach. - Renaud Gaucher; Hadrien Hendrikx; Aymeric Dieuleveut (CoRR, 2024)

Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits. - Daniel Morales-Brotons; Thijs Vogels; Hadrien Hendrikx (Trans. Mach. Learn. Res., 2024)

Asynchronous Speedup in Decentralized Optimization. - Mathieu Even; Hadrien Hendrikx; Laurent Massoulié (IEEE Trans. Autom. Control., 2025)