5 papers · 1 filter
Nonparametric Instrumental Variable Regression with Observed Covariates
Zikai Shen, Zonghao Chen, Dimitri Meunier +3
We study the problem of nonparametric instrumental variable regression with observed covariates, which we refer to as NPIV-O. Compared with standard nonparametric instrumental vari…
Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression
Juno Kim, Dimitri Meunier, Arthur Gretton +2
We provide a convergence analysis of deep feature instrumental variable (DFIV) regression (Xu et al., 2021), a nonparametric approach to IV regression using data-adaptive features…
Nonparametric Instrumental Regression via Kernel Methods is Minimax Optimal
Dimitri Meunier, Zhu Li, Tim Christensen +1
We study the kernel instrumental variable (KIV) algorithm, a kernel-based two-stage least-squares method for nonparametric instrumental variable regression. We provide a convergenc…
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms
Dimitri Meunier, Zikai Shen, Mattes Mollenhauer +2
We study theoretical properties of a broad class of regularized algorithms with vector-valued output. These spectral algorithms include kernel ridge regression, kernel principal co…
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm
Zhu Li, Dimitri Meunier, Mattes Mollenhauer +1
We present the first optimal rates for infinite-dimensional vector-valued ridge regression on a continuous scale of norms that interpolate between and the hypothesis space, w…