Papers

Found 64 papers

Sorted by: Newest First
AOS Jul 15, 2025
Solving the Poisson Equation Using Coupled Markov Chains

Pierre Etienne Jacob, Randal Douc, Anthony Lee et al.

Machine Learning Bayesian Statistics
AOS Jul 15, 2025
Average Partial Effect Estimation Using Double Machine Learning

Harvey Klyne, Rajen Shah

Machine Learning
AOS Jul 15, 2025
High-Dimensional Hilbert-Schmidt Linear Regression with Hilbert Manifold Variables

Changwon Choi, Byeong U. Park

High-Dimensional Statistics Machine Learning
AOS Jul 15, 2025
Optimal Sequencing Depth for Single-Cell RNA-Sequencing in Wasserstein Space

Jakwang Kim, Sharvaj Kubal, Geoffrey Schiebinger

AOS Jul 15, 2025
A Two-Way Heterogeneity Model for Dynamic Networks

Binyan Jiang, Chenlei Leng, Ting Yan et al.

AOS Jul 15, 2025
A Geometrical Analysis of Kernel Ridge Regression and its Applications

Zong Shang, Guillaume Lecué, Georgios Gavrilopoulos

High-Dimensional Statistics Machine Learning Nonparametric Statistics
AOS Jul 15, 2025
Kurtosis-Based Projection Pursuit for Matrix-Valued Data

Una Radojicic, Klaus Nordhausen, Joni Virta

AOS Jul 15, 2025
Clustering by Hill-Climbing: Consistency Results

Ery Arias-Castro, Wanli Qiao

AOS Jul 15, 2025
A Flexible Defense Against the Winner’s Curse

Tijana Zrnic, William Fithian

Machine Learning
AOS Jul 15, 2025
Rank Tests for PCA Under Weak Identifiability

Davy Paindaveine, Laura Peralvo Maroto, Thomas Verdebout

AOS Jul 15, 2025
Sparse PCA: A New Scalable Estimator Based on Integer Programming

Kayhan Behdin, Rahul Mazumder

High-Dimensional Statistics
AOS Jul 15, 2025
Semi-Supervised U-Statistics

Ilmun Kim, Larry Wasserman, Sivaraman Balakrishnan et al.

AOS Jul 15, 2025
Scalable Inference in Functional Linear Regression with Streaming Data

Jinhan Xie, Enze Shi, Peijun Sang et al.

Machine Learning
AOS Jul 15, 2025
Causal Effect Estimation Under Network Interference with Mean-Field Methods

Sohom Bhattacharya, Subhabrata Sen

Causal Inference
AOS Jul 15, 2025
Clustering risk in Non-parametric Hidden Markov and I.I.D. Models

Elisabeth Gassiat, Ibrahim Kaddouri, Zacharie Naulet

AOS Jul 15, 2025
Efficiently Matching Random Inhomogeneous Graphs via Degree Profiles

Jian Ding, Yumou Fei, Yuanzheng Wang

AOS Jul 15, 2025
Improving Knockoffs with Conditional Calibration

Yixiang Luo, William Fithian, Lihua Lei

AOS Jul 15, 2025
Spectral Density Estimation of Function-Valued Spatial Processes

Rafail Kartsioukas, Stilian Stoev, Tailen Hsing

AOS Jul 15, 2025
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning

Yihong Gu, Cong Fang, Peter Bühlmann et al.

Causal Inference
AOS Jul 15, 2025
Tests of Missing Completely at Random Based on Sample Covariance Matrices

Alberto Bordino, Thomas Benjamin Berrett

AOS Jul 15, 2025
Near Optimal Sample Complexity for Matrix and Tensor Normal Models via Geodesic Convexity

Rafael Mendes de Oliveira, William Cole Franks, Akshay Ramachandran et al.

AOS Jul 15, 2025
Yurinskii’s Coupling for Martingales

Matias Damian Cattaneo, Ricardo Pereira Masini, William George Underwood

AOS Jul 15, 2025
Improved Learning Theory for Kernel Distribution Regression with Two-Stage Sampling

François Bachoc, Louis Béthune, Alberto González-Sanz et al.

Machine Learning Nonparametric Statistics
AOS Jul 15, 2025
Trimmed Sample Means for Robust Uniform Mean Estimation and Regression

Roberto Imbuzeiro Moraes Felinto de Oliveira, Lucas Resende

Machine Learning
AOS Jul 15, 2025
Robust Transfer Learning with Unreliable Source Data

Jianqing Fan, Cheng Gao, Jason Matthew Klusowski

AOS Jul 15, 2025
Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning

Weidong Liu, Jiyuan Tu, Yichen Zhang et al.

AOS Jul 15, 2025
The High-Dimensional Asymptotics of Principal Component Regression

Alden Green, Elad Romanov

High-Dimensional Statistics Machine Learning
AOS Jul 15, 2025
Symmetry: A General Structure in Nonparametric Regression

Louis Goldwater Christie, John A. D. Aston

Machine Learning Nonparametric Statistics
AOS Jul 15, 2025
Advances in Bayesian Model Selection Consistency for High-Dimensional Generalized Linear Models

Jeyong Lee, Minwoo Chae, Ryan Martin

High-Dimensional Statistics Statistical Learning Bayesian Statistics
AOS Jul 15, 2025
Estimation and Inference in Distributional Reinforcement Learning

Liangyu Zhang, Yang Peng, Jiadong Liang et al.

AOS Jul 15, 2025
Online Statistical Inference in Decision Making with Matrix Context

Qiyu Han, Will Wei Sun, Yichen Zhang

AOS Jul 15, 2025
High-Dimensional Statistical Inference for Linkage Disequilibrium Score Regression and Its Cross-Ancestry Extensions

Fei Xue, Bingxin Zhao

High-Dimensional Statistics Machine Learning
AOS Jul 15, 2025
Deep Horseshoe Gaussian Processes

Ismaël Castillo, Thibault Christophe Randrianarisoa

AOS Jul 15, 2025
The Functional Graphical Lasso

Kartik Govind Waghmare, Tomas Masak, Victor Michael Panaretos

High-Dimensional Statistics
AOS Jul 15, 2025
Counterfactual Inference in Sequential Experiments

Raaz Dwivedi, Katherine Tian, Sabina Tomkins et al.

AOS Jul 15, 2025
Optimal Vintage Factor Analysis with Deflation Varimax

Xin Bing, Xin He, Dian Jin et al.

Time Series
AOS Jul 15, 2025
Low-Degree Hardness of Detection for Correlated Erdős-Rényi Graphs

Jian Ding, Hang Du, Zhangsong Li

AOS Jul 15, 2025
Spectral Gap Bounds for Reversible Hybrid Gibbs Chains

Qian Qin, Nianqiao Ju, Guanyang Wang

Machine Learning
AOS Jul 15, 2025
Fixed and Random Covariance Regression Analyses

Tao Zou, Wei Lan, Runze Li et al.

Machine Learning
AOS Jul 15, 2025
Debiased Regression Adjustment in Completely Randomized Experiments with Moderately High-Dimensional Covariates

Xin Lu, Fan Yang, Yuhao Wang

High-Dimensional Statistics Machine Learning
AOS Jul 15, 2025
Algorithmic Stability Implies Training-Conditional Coverage for Distribution-Free Prediction Methods

Ruiting Liang, Rina Foygel Barber

Machine Learning Computational Statistics Statistical Learning
AOS Jul 15, 2025
On the Multiway Principal Component Analysis

Jialin Ouyang, Ming Yuan

AOS Jul 15, 2025
Semiparametric Modeling and Analysis for Longitudinal Network Data

Yinqiu He, Jiajin Sun, Yuang Tian et al.

AOS Jul 15, 2025
On the Structural Dimension of Sliced Inverse Regression

Dongming Huang, Songtao Tian, Qian Lin

Machine Learning
AOS Jul 15, 2025
Asymptotically-Exact Selective Inference for Quantile Regression

Yumeng Wang, Snigdha Panigrahi, Xuming He

Machine Learning
AOS Jul 15, 2025
Entropic Covariance Models

Piotr Zwiernik

AOS Jul 15, 2025
Near-Optimal Inference in Adaptive Linear Regression

Koulik Khamaru, Yash Deshpande, Tor Lattimore et al.

Machine Learning
AOS Jul 15, 2025
A Common-Cause Principle for Eliminating Selection Bias in Causal Estimands Through Covariate Adjustment

Maya Mathur, Ilya Shpitser, Tyler VanderWeele

Causal Inference