Dimitri Meunier

22 papers A* 4A 1Journal 17

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Demystifying Spectral Feature Learning for Instrumental Variable Regression. CoRR Dimitri Meunier, Antoine Moulin, Jakub Wornbard, Vladimir R. Kostic, Arthur Gretton
2025	J	`jnl`	Density Ratio-Free Doubly Robust Proxy Causal Learning. CoRR Bariscan Bozkurt, Houssam Zenati, Dimitri Meunier, Liyuan Xu, Arthur Gretton
2025	A	`conf`	Density Ratio-based Proxy Causal Learning Without Density Ratios. AISTATS Bariscan Bozkurt, Ben Deaner, Dimitri Meunier, Liyuan Xu, Arthur Gretton
2025	J	`jnl`	Density Ratio-based Proxy Causal Learning Without Density Ratios. CoRR Bariscan Bozkurt, Ben Deaner, Dimitri Meunier, Liyuan Xu, Arthur Gretton
2025	J	`jnl`	Nonlinear Meta-learning Can Guarantee Faster Rates. SIAM J. Math. Data Sci. Dimitri Meunier, Zhu Li, Arthur Gretton, Samory Kpotufe
2025	J	`jnl`	Nonparametric Instrumental Variable Regression with Observed Covariates. CoRR Zikai Shen, Zonghao Chen, Dimitri Meunier, Ingo Steinwart, Arthur Gretton, Zhu Li
2025	A*	`conf`	Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression. ICLR Juno Kim, Dimitri Meunier, Arthur Gretton, Taiji Suzuki, Zhu Li
2025	J	`jnl`	Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression. CoRR Juno Kim, Dimitri Meunier, Arthur Gretton, Taiji Suzuki, Zhu Li
2025	J	`jnl`	Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression. CoRR Dimitri Meunier, Jakub Wornbard, Vladimir R. Kostic, Antoine Moulin, Alek Fröhlich, Karim Lounici, Massimiliano Pontil, Arthur Gretton
2025	J	`jnl`	Regularized least squares learning with heavy-tailed noise is minimax optimal. CoRR Mattes Mollenhauer, Nicole Mücke, Dimitri Meunier, Arthur Gretton
2024	J	`jnl`	Nonparametric Instrumental Regression via Kernel Methods is Minimax Optimal. CoRR Dimitri Meunier, Zhu Li, Tim Christensen, Arthur Gretton
2024	A*	`conf`	Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms. NeurIPS Dimitri Meunier, Zikai Shen, Mattes Mollenhauer, Arthur Gretton, Zhu Li
2024	J	`jnl`	Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms. CoRR Dimitri Meunier, Zikai Shen, Mattes Mollenhauer, Arthur Gretton, Zhu Li
2024	J	`jnl`	Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm. J. Mach. Learn. Res. Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton
2023	J	`jnl`	Nonlinear Meta-Learning Can Guarantee Faster Rates. CoRR Dimitri Meunier, Zhu Li, Arthur Gretton, Samory Kpotufe
2023	J	`jnl`	Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm. CoRR Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton
2022	A*	`conf`	Distribution Regression with Sliced Wasserstein Kernels. ICML Dimitri Meunier, Massimiliano Pontil, Carlo Ciliberto
2022	J	`jnl`	Distribution Regression with Sliced Wasserstein Kernels. CoRR Dimitri Meunier, Massimiliano Pontil, Carlo Ciliberto
2022	A*	`conf`	Optimal Rates for Regularized Conditional Mean Embedding Learning. NeurIPS Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton
2022	J	`jnl`	Optimal Rates for Regularized Conditional Mean Embedding Learning. CoRR Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton
2021	J	`jnl`	Meta-Strategy for Learning Tuning Parameters with Guarantees. Entropy Dimitri Meunier, Pierre Alquier
2021	J	`jnl`	Meta-strategy for Learning Tuning Parameters with Guarantees. CoRR Dimitri Meunier, Pierre Alquier