Pillaud-Vivien, Loucas

15 publications

NeurIPS 2025 Convergence of the Gradient Flow for Shallow ReLU Networks on Weakly Interacting Data Léo Dana, Loucas Pillaud-Vivien, Francis Bach

JMLR 2025 Variational Inference for Uncertainty Quantification: An Analysis of Trade-Offs Charles C. Margossian, Loucas Pillaud-Vivien, Lawrence K. Saul

ICML 2024 Batch and Match: Black-Box Variational Inference with a Score-Based Divergence Diana Cai, Chirag Modi, Loucas Pillaud-Vivien, Charles Margossian, Robert M. Gower, David Blei, Lawrence K. Saul

COLT 2024 Computational-Statistical Gaps in Gaussian Single-Index Models (Extended Abstract) Alex Damian, Loucas Pillaud-Vivien, Jason Lee, Joan Bruna

COLT 2023 Kernelized Diffusion Maps Loucas Pillaud-Vivien, Francis Bach

NeurIPS 2023 On Single-Index Models Beyond Gaussian Data Aaron Zweig, Loucas Pillaud-Vivien, Joan Bruna

NeurIPS 2023 On the Spectral Bias of Two-Layer Linear Networks Aditya Vardhan Varre, Maria-Luiza Vladarean, Loucas Pillaud-Vivien, Nicolas Flammarion

ICML 2023 SGD with Large Step Sizes Learns Sparse Features Maksym Andriushchenko, Aditya Vardhan Varre, Loucas Pillaud-Vivien, Nicolas Flammarion

NeurIPS 2022 Gradient Flow Dynamics of Shallow ReLU Networks for Square Loss and Orthogonal Inputs Etienne Boursier, Loucas Pillaud-Vivien, Nicolas Flammarion

NeurIPS 2021 Implicit Bias of SGD for Diagonal Linear Networks: A Provable Benefit of Stochasticity Scott Pesme, Loucas Pillaud-Vivien, Nicolas Flammarion

NeurIPS 2021 Last Iterate Convergence of SGD for Least-Squares in the Interpolation Regime. Aditya Vardhan Varre, Loucas Pillaud-Vivien, Nicolas Flammarion

NeurIPS 2021 Overcoming the Curse of Dimensionality with Laplacian Regularization in Semi-Supervised Learning Vivien Cabannes, Loucas Pillaud-Vivien, Francis R. Bach, Alessandro Rudi

AISTATS 2020 Statistical Estimation of the Poincaré Constant and Application to Sampling Multimodal Distributions Loucas Pillaud-Vivien, Francis Bach, Tony Lelièvre, Alessandro Rudi, Gabriel Stoltz

COLT 2018 Exponential Convergence of Testing Error for Stochastic Gradient Methods Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach

NeurIPS 2018 Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems Through Multiple Passes Loucas Pillaud-Vivien, Alessandro Rudi, Francis Bach