Found 126 papers
Sorted by: Newest FirstUniform Estimation and Inference for Nonparametric Partitioning-Based M-Estimators
Matias D. Cattaneo, Yingjie Feng, Boris Shigida
Local geometry of high-dimensional mixture models: Effective spectral theory and dynamical transitions
Aukosh Jagannath, Gerard Ben Arous, Reza Gheissari et al.
Optimal Integrative Estimation for Distributed Precision Matrices with Heterogeneity Adjustment
Yinrui Sun, Yin Xia
A novel statistical approach to analyze image classification
Juntong Chen, Sophie Langer, Johannes Schmidt-Hieber
Statistical Inference in Tensor Completion: Optimal Uncertainty Quantification and Statistical-to-Computational Gaps
Dong Xia, Wanteng Ma
Dual Induction CLT for High-dimensional m-dependent Data
Heejong Bong, Arun Kumar Kuchibhotla, Alessandro Rinaldo
Minimax optimal seriation in polynomial time
Yann Issartel, Christophe Giraud, Nicolas Verzelen
Attainability of Two-Point Testing Rates for Finite-Sample Location Estimation
Spencer Compton, Gregory Valiant
Test of Independence Using Generalized Distance Correlation
Jianqing Fan, Zhipeng Lou, Danna Zhang
A non-asymptotic distributional theory of approximate message passing for sparse and robust regression
Gen Li, Yuting Wei
A Two-step Estimating Approach for Heavy-tailed AR Models with Non-zero Median GARCH-type Noises
She Rui, Dai Linlin, Ling Shiqing
Towards a Unified Theory for Semiparametric Data Fusion with Individual-Level Data
Ellen Sandra Graham, Marco Carone, Andrea Rotnitzky
Identification and estimation for matrix time series CP-factor models
Qiwei Yao, Jinyuan Chang, Yue Du et al.
Markov stick-breaking processes
Antonio Lijoi, Maria F. Gil-Leyva, Ramses H. Mena et al.
Uncertainty quantification for iterative algorithms in linear models with application to early stopping
Kai Tan, Pierre C Bellec
Adaptive Bayesian regression on data with low intrinsic dimensionality
Tao Tang, Xiuyuan Cheng, Nan Wu et al.
VECCHIA GAUSSIAN PROCESSES: ON PROBABILISTIC AND STATISTICAL PROPERTIES
Botond Tibor Szabo, Yichen Zhu
Vecchia Gaussian Processes: Probabilistic Properties, Minimax Rates and Methodological Developments
Botond Tibor Szabo, Yichen Zhu
Statistical-Computational Trade-offs for Recursive Adaptive Partitioning Estimators
Yan Shuo Tan, Jason M. Klusowski, Krishnakumar Balasubramanian
Reviving pseudo-inverses: Asymptotic properties of large dimensional Moore-Penrose and Ridge-type inverses with applications
Taras Bodnar, Nestor Parolya
Generalized Linear Spectral Statistics of High-dimensional Sample Covariance Matrices and Its Applications
Yanlin Hu, Qing Yang, Xiao Han
The out-of sample prediction error of the $\sqrt{\text{LASSO}}$ and related estimators
José Luis Montiel Olea, Cynthia Rush, Amilcar Velez et al.
Generalized Multilinear Models for Sufficient Dimension Reduction on Tensor-valued Predictors
Daniel Kapla, Efstathia Bura
Parameter identification in linear non-Gaussian causal models under general confounding
Jalal Etesami, Mathias Drton, Daniele Tramontano
Object detection under the linear subspace model with application to cryo-EM images
Samuel Davenport, Amitay Eldar, Keren Mor Waknin et al.
Learning extremal graphical structures in high dimensions
Sebastian Engelke, Michael Lalancette, Stanislav Volgushev
Eigenvector Overlaps in Large Sample Covariance Matrices and Nonlinear Shrinkage Estimators
Guangming Pan, Zeqin Lin
Inferring the dependence graph density of binary graphical models in high dimension
Julien Chevallier, Eva Löcherbach, Guilherme Ost
Finite- and large-sample inference for model and coefficients in high-dimensional linear regression with repro samples
Linjun Zhang, Peng Wang, Minge Xie
Precise Asymptotics of Bagging Regularized M-estimators
Pierre C. Bellec, Takuya Koriyama, Jin-Hong Du et al.
Statistical Inference for Low-Rank Tensors: Heteroskedasticity, Subgaussianity, and Applications
Joshua Agterberg, Anru Zhang
Online Tensor Learning: Computational and Statistical Trade-offs, Adaptivity and Optimal Regret
Dong Xia, Jingyang Li, Yang Chen et al.
Dualizing Le Cam’s method for functional estimation I: General theory
Yihong Wu, Yury Polyanskiy
Scalable inference for Nonparametric Stochastic Approximation in Reproducing Kernel Hilbert Spaces
Zuofeng Shang, Meimei Liu, Yun Yang
Spectrum-Aware Debiasing: A Modern Inference Framework with Applications to Principal Components Regression
Yufan Li, Pragya Sur
Nonparametric Estimation of a Covariate-Adjusted Counterfactual Treatment Regimen Response Curve
Ashkan Ertefaie, Luke Duttweiler, Brent A. Johnson et al.
Optimal Eigenvalue Shrinkage in the Semicircle Limit
Michael Jacob Feldman, David Leigh Donoho
Versatile Differentially Private Learning for General Loss Functions
Yumou Qiu, Song X Chen, Qilong Lu
Large-Scale Multiple Testing: Fundamental Limits of False Discovery Rate Control and Compound Oracle
Yihong Wu, Yutong Nie
Estimation of Grouped Time-Varying Network Vector Autoregressive Models
Degui Li, Bin Peng, Songqiao Tang et al.
Trace Test for High-Dimensional Cointegration
Alexei Onatski, Chen Wang
Distributionally Robust Learning for Multi-source Unsupervised Domain Adaptation
Peter Bühlmann, Zijian Guo, Zhenyu Wang
istributionally Robust Learning for Multi-source Unsupervised Domain Adaptation
Peter Bühlmann, Zijian Guo, Zhenyu Wang
Information Theoretic Limits of Robust Sub-Gaussian Mean Estimation Under Star-Shaped Constraints
Matey Neykov, Akshay Prasadan
Optimality of Approximate Message Passing for Spiked Matrix Models with Rotationally Invariant Noise
Rishabh Dudeja, Songbin Liu, Junjie Ma
Communication-Efficient and Distributed-Oracle Estimation for High-Dimensional Quantile Regression
Xuming He, Songshan Yang, Yifan Gu et al.
Optimal Convex $M$-Estimation via Score Matching
Oliver Y. Feng, Yu-Chun Kao, Min Xu et al.
Semiparametric Bernstein-Von Mises Phenomenon via Isotonized Posterior in Wicksell’s Problem
Aad van der Vaart, Francesco Gili, Geurt Jongbloed
Neural Networks Generalize on Low Complexity Data
Sourav Chatterjee, Timothy Sudijono
Berry-Esseen Bounds for Design-Based Causal Inference With Possibly Diverging Treatment Levels and Varying Group Sizes
Peng Ding, Lei Shi
Multivariate Root-N-Consistent Smoothing Parameter Free Matching Estimators and Estimators of Inverse Density Weighted Expectations
Hajo Holzmann, Alexander Meister
Change Point Estimation for a Stochastic Heat Equation
Markus Reiß, Claudia Strauch, Lukas Trottner
Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift
Kaizheng Wang
A Computational Transition for Detecting Correlated Stochastic Block Models by Low-Degree Polynomials
Jian Ding, Zhangsong Li, Guanyi Chen et al.
Solving the Poisson Equation Using Coupled Markov Chains
Pierre Etienne Jacob, Randal Douc, Anthony Lee et al.
Average Partial Effect Estimation Using Double Machine Learning
Harvey Klyne, Rajen Shah
Fundamental Limits of Community Detection From Multi-View Data: Multi-Layer, Dynamic and Partially Labeled Block Models
Subhabrata Sen, Xiaodong Yang, Buyu Lin
Online Estimation with Rolling Validation: Adaptive Nonparametric Estimation with Streaming Data
Tianyu Zhang, Jing Lei
Poisson Empirical Bayes Estimation: When Doesg-Modeling Beatf-Modeling in Theory (And in Practice)?
Yihong Wu, Yandi Shen
High-Dimensional Hilbert-Schmidt Linear Regression with Hilbert Manifold Variables
Changwon Choi, Byeong U. Park
Optimal Sequencing Depth for Single-Cell RNA-Sequencing in Wasserstein Space
Jakwang Kim, Sharvaj Kubal, Geoffrey Schiebinger
A Two-Way Heterogeneity Model for Dynamic Networks
Binyan Jiang, Ting Yan, Qiwei Yao et al.
A Geometrical Analysis of Kernel Ridge Regression and its Applications
Zong Shang, Guillaume Lecué, Georgios Gavrilopoulos
Kurtosis-Based Projection Pursuit for Matrix-Valued Data
Una Radojicic, Klaus Nordhausen, Joni Virta
A Flexible Defense Against the Winner’s Curse
William Fithian, Tijana Zrnic
Rank Tests for PCA Under Weak Identifiability
Davy Paindaveine, Laura Peralvo Maroto, Thomas Verdebout
Sparse PCA: A New Scalable Estimator Based on Integer Programming
Kayhan Behdin, Rahul Mazumder
Semi-Supervised U-Statistics
Larry Wasserman, Ilmun Kim, Sivaraman Balakrishnan et al.
Scalable Inference in Functional Linear Regression with Streaming Data
Linglong Kong, Jinhan Xie, Enze Shi et al.
The Empirical Copula Process in High Dimensions: Stute’s Representation and Applications
Axel Bücher, Cambyse Pakzad
Causal Effect Estimation Under Network Interference with Mean-Field Methods
Subhabrata Sen, Sohom Bhattacharya
Clustering risk in Non-parametric Hidden Markov and I.I.D. Models
Elisabeth Gassiat, Ibrahim Kaddouri, Zacharie Naulet
Efficiently Matching Random Inhomogeneous Graphs via Degree Profiles
Jian Ding, Yumou Fei, Yuanzheng Wang
Improving Knockoffs with Conditional Calibration
William Fithian, Yixiang Luo, Lihua Lei
Spectral Density Estimation of Function-Valued Spatial Processes
Rafail Kartsioukas, Stilian Stoev, Tailen Hsing
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning
Jianqing Fan, Yihong Gu, Cong Fang et al.
Tests of Missing Completely at Random Based on Sample Covariance Matrices
Alberto Bordino, Thomas Benjamin Berrett
Near Optimal Sample Complexity for Matrix and Tensor Normal Models via Geodesic Convexity
Rafael Mendes de Oliveira, William Cole Franks, Akshay Ramachandran et al.
Yurinskii’s Coupling for Martingales
Matias Damian Cattaneo, Ricardo Pereira Masini, William George Underwood
Improved Learning Theory for Kernel Distribution Regression with Two-Stage Sampling
François Bachoc, Louis Béthune, Alberto González-Sanz et al.
Trimmed Sample Means for Robust Uniform Mean Estimation and Regression
Roberto Imbuzeiro Moraes Felinto de Oliveira, Lucas Resende
Pseudo-Likelihood-Based M-Estimation of Random Graphs with Dependent Edges and Parameter Vectors of Increasing Dimension
Jonathan Roy Stewart, Michael Schweinberger
Robust Transfer Learning with Unreliable Source Data
Jianqing Fan, Cheng Gao, Jason Matthew Klusowski
Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning
Xi Chen, Yichen Zhang, Weidong Liu et al.
The High-Dimensional Asymptotics of Principal Component Regression
Alden Green, Elad Romanov
Theory of Functional Principal Component Analysis for Discretely Observed Data
Fang Yao, Hang Zhou, Dongyi Wei
A Unified Analysis of Likelihood-based Estimators in the Plackett–Luce Model
Ruijian Han, Yiming Xu
Symmetry: A General Structure in Nonparametric Regression
Louis Goldwater Christie, John A. D. Aston
Advances in Bayesian Model Selection Consistency for High-Dimensional Generalized Linear Models
Jeyong Lee, Minwoo Chae, Ryan Martin
Estimation and Inference in Distributional Reinforcement Learning
Liangyu Zhang, Yang Peng, Jiadong Liang et al.
Online Statistical Inference in Decision Making with Matrix Context
Yichen Zhang, Qiyu Han, Will Wei Sun
Structured Matrix Learning under Arbitrary Entrywise Dependence and Estimation of Markov Transition Kernel
Jianqing Fan, Jinhang Chai
Optimal and Exact Recovery on the General Non-Uniform Hypergraph Stochastic Block Model
Ioana Dumitriu, Hai-Xiao Wang
High-Dimensional Statistical Inference for Linkage Disequilibrium Score Regression and Its Cross-Ancestry Extensions
Fei Xue, Bingxin Zhao
Deep Horseshoe Gaussian Processes
Ismaël Castillo, Thibault Christophe Randrianarisoa
The Functional Graphical Lasso
Kartik Govind Waghmare, Tomas Masak, Victor Michael Panaretos
Higher-Order Entrywise Eigenvectors Analysis of Low-Rank Random Matrices: Bias Correction, Edgeworth Expansion, and Bootstrap
Yichi Zhang, Fangzheng Xie
Counterfactual Inference in Sequential Experiments
Raaz Dwivedi, Katherine Tian, Sabina Tomkins et al.
Optimal Vintage Factor Analysis with Deflation Varimax
Xin Bing, Xin He, Dian Jin et al.
Low-Degree Hardness of Detection for Correlated Erdős-Rényi Graphs
Jian Ding, Zhangsong Li, Hang Du
Spectral Gap Bounds for Reversible Hybrid Gibbs Chains
Qian Qin, Nianqiao Ju, Guanyang Wang
Fixed and Random Covariance Regression Analyses
Wei Lan, Chih-Ling Tsai, Runze Li et al.
Debiased Regression Adjustment in Completely Randomized Experiments with Moderately High-Dimensional Covariates
Xin Lu, Fan Yang, Yuhao Wang
Reinforcement Learning for Individual Optimal Policy From Heterogeneous Data
Annie Qu, Rui Miao, Babak Shahbaba
Policy Learning “Without” Overlap: Pessimism and Generalized Empirical Bernstein’s Inequality
Zhaoran Wang, Ying Jin, Zhimei Ren et al.
Algorithmic Stability Implies Training-Conditional Coverage for Distribution-Free Prediction Methods
Ruiting Liang, Rina Foygel Barber
Semiparametric Modeling and Analysis for Longitudinal Network Data
Yang Feng, Yinqiu He, Jiajin Sun et al.
On the Structural Dimension of Sliced Inverse Regression
Dongming Huang, Songtao Tian, Qian Lin
Erratum: Quantile Processes and Their Applications in Finite Populations
Anurag Dey, Probal Chaudhuri
Dualizing Le Cam’s Method for Functional Estimation, with Applications to Estimating the Unseens
Yihong Wu, Yury Polyanskiy
Asymptotically-Exact Selective Inference for Quantile Regression
Xuming He, Yumeng Wang, Snigdha Panigrahi
Near-Optimal Inference in Adaptive Linear Regression
Koulik Khamaru, Yash Deshpande, Tor Lattimore et al.
A Common-Cause Principle for Eliminating Selection Bias in Causal Estimands Through Covariate Adjustment
Ilya Shpitser, Maya Mathur, Tyler VanderWeele