Cover Image

Deep learning with missing data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ma, Tianyi, Wang, Tengyao, Samworth, Richard J.
Format:	Preprint
Published:	2025
Subjects:	Methodology Machine Learning Statistics Theory 62C20, 62D10, 62G08
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Estimation beyond Missing (Completely) at Random
by: Ma, Tianyi, et al.
Published: (2024)

Optimal In-context Adaptivity and Distributional Robustness of Transformers
by: Ma, Tianyi, et al.
Published: (2025)

A Bernstein polynomial approach for the estimation of cumulative distribution functions in the presence of missing data
by: Gharbi, Rihab, et al.
Published: (2025)

Factor Informed Double Deep Learning For Average Treatment Effect Estimation
by: Fan, Jianqing, et al.
Published: (2025)

Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints
by: Auddy, Arnab, et al.
Published: (2024)

Dirichlet kernel density estimation on the simplex with missing data
by: Daayeb, Hanen, et al.
Published: (2026)

High-probability minimax lower bounds
by: Ma, Tianyi, et al.
Published: (2024)

Nonparametric classification with missing data
by: Sell, Torben, et al.
Published: (2023)

Cheap Permutation Testing
by: Domingo-Enrich, Carles, et al.
Published: (2025)

New Risk Bounds for 2D Total Variation Denoising
by: Chatterjee, Sabyasachi, et al.
Published: (2019)

Adaptation using spatially distributed Gaussian Processes
by: Szabo, Botond, et al.
Published: (2023)

Two-Sample Testing with Missing Data via Energy Distance: Weighting and Imputation Approaches
by: Aleksić, Danijel G., et al.
Published: (2025)

Extreme-PLS with missing data under weak dependence
by: Girard, Stéphane, et al.
Published: (2025)

Sparse semiparametric regression when predictors are mixture of functional and high-dimensional variables
by: Novo, Silvia, et al.
Published: (2024)

Inference with Mondrian Random Forests
by: Cattaneo, Matias D., et al.
Published: (2023)

Asymptotic confidence bands for the histogram regression estimator
by: Neumeyer, Natalie, et al.
Published: (2025)

Distributional Conformal Prediction for Markov Processes
by: Dai, Dehao, et al.
Published: (2026)

Statistical Convergence Rates of Optimal Transport Map Estimation between General Distributions
by: Ding, Yizhe, et al.
Published: (2024)

A Note on Local Linear Regression for Time Series in Banach Spaces
by: Heinrichs, Florian
Published: (2025)

Batch learning equals online learning in Bayesian supervised learning
by: Lê, Hông Vân
Published: (2025)

Semiparametric Uncertainty Quantification via Isotonized Posterior for Deconvolutions
by: Gili, Francesco, et al.
Published: (2026)

Adaptive functional principal components analysis
by: Wang, Sunny G. W., et al.
Published: (2023)

The Projected Covariance Measure for assumption-lean variable significance testing
by: Lundborg, Anton Rask, et al.
Published: (2022)

Invariant quantile regression for heterogeneous environments
by: Fu, Bo, et al.
Published: (2026)

Learning the score under shape constraints
by: Lewis, Rebecca M., et al.
Published: (2025)

A new and flexible class of sharp asymptotic time-uniform confidence sequences
by: Gnettner, Felix, et al.
Published: (2025)

Nonparametric Regression for Random Unbiased Perturbations
by: Lyubarskaja, Anna, et al.
Published: (2025)

A Minimax Theory of Nonparametric Regression Under Covariate Shift
by: Zamolodtchikov, Petr
Published: (2026)

Identifying arbitrary transformation between the slopes in scalar-on-function regression
by: Niyogi, Pratim Guha, et al.
Published: (2024)

Mean and Covariance Estimation for Discretely Observed High-Dimensional Functional Data: Rates of Convergence and Division of Observational Regimes
by: Petersen, Alexander
Published: (2024)

Estimating a Function and Its Derivatives Under a Smoothness Condition
by: Lim, Eunji
Published: (2024)

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

Handling Missing Data in Probabilistic Regression Trees: Methods and Implementation in R
by: Prass, Taiane Schaedler, et al.
Published: (2025)

Strong consistency of the local linear estimator for a generalized regression function with dependent functional data
by: Matsuoka, Danilo Hiroshi, et al.
Published: (2026)

High-Dimensional Change-Point Detection via Angular Kernel Statistics
by: Choudhury, Jyotishka Ray, et al.
Published: (2026)

Efficient Inference on High-Dimensional Linear Models with Missing Outcomes
by: Zhang, Yikun, et al.
Published: (2023)

Asymptotic confidence bands for centered purely random forests
by: Neumeyer, Natalie, et al.
Published: (2025)

A uniform kernel trick for high-dimensional two-sample problems
by: Cárcamo, Javier, et al.
Published: (2022)

Estimation and Hypothesis Testing of Derivatives in Smoothing Spline ANOVA Models
by: Liu, Ruiqi, et al.
Published: (2023)

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