Cover Image

Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Singh, Rahul
Format:	Preprint
Published:	2021
Subjects:	Machine Learning Econometrics Statistics Theory 62G15, 62D20, 46E22 G.3; J.4
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Automatic Debiased Machine Learning via Riesz Regression
by: Chernozhukov, Victor, et al.
Published: (2021)

Likelihood Ratio Tests by Kernel Gaussian Embedding
by: Santoro, Leonardo V., et al.
Published: (2025)

A Necessary and Sufficient Condition for Size Controllability of Heteroskedasticity Robust Test Statistics
by: Pötscher, Benedikt M., et al.
Published: (2024)

Kernel-Based Nonparametric Tests For Shape Constraints
by: Sen, Rohan
Published: (2025)

Valid Heteroskedasticity Robust Testing
by: Pötscher, Benedikt M., et al.
Published: (2021)

Can we have it all? Non-asymptotically valid and asymptotically exact confidence intervals for expectations and linear regressions
by: Derumigny, Alexis, et al.
Published: (2025)

Local Fr'echet Regression via RKHS embedding and Its Applications to Data Analysis on Manifolds
by: Iida, Yuki, et al.
Published: (2025)

SAGA: A Sequence-Adaptive Generative Architecture for Multi-Horizon Probabilistic Forecasting with Adaptive Temporal Conformal Prediction
by: Lundström-Imanov, Gustav Olaf Yunus Laitinen-Fredriksson, et al.
Published: (2026)

Adaptive Nonparametric Estimation via Kernel Transport on Group Orbits: Oracle Inequalities and Minimax Rates
by: Nembe, Jocelyn
Published: (2025)

Yurinskii's Coupling for Martingales
by: Cattaneo, Matias D., et al.
Published: (2022)

Correcting Mode Proportion Bias in Generalized Bayesian Inference via a Weighted Kernel Stein Discrepancy
by: Afzali, Elham, et al.
Published: (2025)

Kernel Embeddings and the Separation of Measure Phenomenon
by: Santoro, Leonardo V., et al.
Published: (2025)

Joint Estimation of Conditional Mean and Covariance for Unbalanced Panels
by: Filipovic, Damir, et al.
Published: (2024)

Spectral Equivariance and Geometric Transport in Reproducing Kernel Hilbert Spaces: A Unified Framework for Orthogonal Polynomial and Kernel Estimation
by: Nembé, Jocelyn
Published: (2025)

Average Marginal Effects in One-Step Partially Linear Instrumental Regressions
by: Girard, Lucas, et al.
Published: (2026)

Doubly Robust Inference on Causal Derivative Effects for Continuous Treatments
by: Zhang, Yikun, et al.
Published: (2025)

A simplified directional KeRF algorithm
by: Isidoros, Iakovidis, et al.
Published: (2024)

Unbiased Regression-Adjusted Estimation of Average Treatment Effects in Randomized Controlled Trials
by: Abadie, Alberto, et al.
Published: (2025)

On a transform of the Vincze-statistic and its exact and asymptotic distribution
by: Ferger, Dietmar
Published: (2025)

Leveraging LLMs to Improve Experimental Design: A Generative Stratification Approach
by: Gui, George, et al.
Published: (2025)

Sparse Anomaly Detection Across Referentials: A Rank-Based Higher Criticism Approach
by: Stoepker, Ivo V., et al.
Published: (2023)

Conditional validity and a fast approximation formula of full conformal prediction sets
by: Amann, Nicolai
Published: (2025)

Optimal Rate of Kernel Regression in Large Dimensions
by: Lu, Weihao, et al.
Published: (2023)

Nyström Kernel Stein Discrepancy Tests
by: Kalinke, Florian, et al.
Published: (2026)

Generalized Bayes in Conditional Moment Restriction Models
by: Kankanala, Sid
Published: (2025)

Range-Based Volatility Estimators for Monitoring Market Stress: Evidence from Local Food Price Data
by: Andrée, Bo Pieter Johannes
Published: (2026)

Insights into Tail-Based and Order Statistics
by: Almani, Hamidreza Maleki
Published: (2025)

Maximum a posteriori testing in statistical inverse problems
by: Kretschmann, Remo, et al.
Published: (2024)

Kernel Density Estimation and Convolution Revisited
by: Tenkorang, Nicholas, et al.
Published: (2025)

Spectral Regularized Kernel Two-Sample Tests
by: Hagrass, Omar, et al.
Published: (2022)

Spectral Regularized Kernel Goodness-of-Fit Tests
by: Hagrass, Omar, et al.
Published: (2023)

Identification of Latent Group Effects under Conditional Calibration
by: Kurbucz, Marcell T.
Published: (2026)

The Optimality of Kernel Classifiers in Sobolev Space
by: Lai, Jianfa, et al.
Published: (2024)

Confidence intervals for intentionally biased estimators
by: Kaplan, David M., et al.
Published: (2025)

Minimax Optimal Kernel Two-Sample Tests with Random Features
by: Mukherjee, Soumya, et al.
Published: (2025)

Minimax Optimal Goodness-of-Fit Testing with Kernel Stein Discrepancy
by: Hagrass, Omar, et al.
Published: (2024)

Conditional nonparametric variable screening by neural factor regression
by: Fan, Jianqing, et al.
Published: (2024)

The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels
by: Kalinke, Florian, et al.
Published: (2024)

Change-Point Analysis of Time Series with Evolutionary Spectra
by: Casini, Alessandro, et al.
Published: (2021)

A Novel Multiple Imputation Approach For Parameter Estimation in Observation-Driven Time Series Models With Missing Data
by: Pumi, Guilherme, et al.
Published: (2026)