Papers to Appear in Subsequent Issues

Testing in High-Dimensional Spiked Models Iain M Johnstone and Alexei Onatski
On Estimation of Isotonic Piecewise Constant Signals Chao Gao, Fang Han, and Cun-Hui Zhang
Limiting Laws for Divergent Spiked Eigenvalues and Largest Non-spiked Eigenvalue of Sample Covariance Matrices Tony Cai, Xiao Han, and Guangming Pan
Non-classical Berry-Esseen inequalities and accuracy of the bootstrap Mayya Zhilova
Multidimensional multiscale scanning in Exponential Families: Limit theory and statistical consequences Claudia König, Axel Munk, and Frank Werner
Designs for estimating the treatment effect in networks with interference Ravi Jagadeesan, Natesh Pillai, and Alexander Volfovsky
Learning a Tree-Structured Ising Model in Order to Make Predictions Guy Bresler and Mina Karzand
On the optimality of sliced inverse regression in high dimensions Qian Lin, Jun S Liu, Dongming Huang, and Xinran Li
On the nonparametric maximum likelihood estimator for Gaussian location mixture densities with application to Gaussian denoising Sujayam Saha and Adityanand Guntuboyina
Prediction error after model search Xiaoying Tian
Joint estimation of parameters in Ising model Promit Ghosal and Sumit Mukherjee
Model-assisted inference for treatment effects using regularized calibrated estimation with high-dimensional data Zhiqiang Tan
Hurst Function Estimation Tailen Hsing and Jinqi Shen
Detection limits in the spiked Wigner model Ahmed El Alaoui, Florent Krzakala, and Michael Jordan
α-Variational Inference with Statistical Guarantees Yun Yang, Debdeep Pati, and Anirban Bhattacharya
Robust machine learning by median-of-means: theory and practice Guillaume Lecué and Matthieu Lerasle
Consistent Maximum Likelihood Estimation Using Subsets with Applications to Multivariate Mixed Models Karl Oskar Ekvall and Galin L. Jones
Asymptotic Optimality in Stochastic Optimization John Duchi and Feng Ruan
Convergence of eigenvector empirical spectral distribution of sample covariance matrices Jun Yin, Haokai Xi, Fan Yang
D-optimal Designs for Multinomial Logistic Models Xianwei Bu, Dibyen Majumdar, and Jie Yang
A unified study of nonparametric inference for monotone functions Ted Westling and Marco Carone
Inference for Archimax copulas Simon Chatelain, Anne-Laure Fougères, and Johanna G. Neslehova
Admissible Bayes equivariant estimation of location vectors for spherically symmetric distributions with unknown scale Yuzo Maruyama and William E. Strawderman
Worst-case vs Average-case Design for Estimation from Partial Pairwise Comparisons Ashwin Pananjady, Cheng Mao, Vidya Muthukumar, Martin J. Wainwright, and Thomas A. Courtade
Non-asymptotic upper bounds for the reconstruction error of PCA Martin Wahl and Markus Reiß
Lasso Guarantees for β-Mixing Heavy Tailed Time Series Kam Chung Wong, Zifan Li, and Ambuj Tewari
High-frequency analysis of parabolic stochastic PDEs Carsten Chong
Functional data analysis in the Banach space of continuous functions Holger Dette, Kevin Kokot, and Alexander Aue
Mean Estimation with Sub-Gaussian Rates in Polynomial Time Samuel Hopkins
Bootstrapping Max Statistics in High Dimensions: Near-Parametric Rates Under Weak Variance Decay and Application to Functional and Multinomial Data Miles Lopes, Zhenhua Lin, and Hans-Georg Mueller
Empirical Bayes oracle uncertainty quantification for regression Eduard Belitser and Subhashis Ghosal
GRID: A variable selection and structure discovery method for high dimensional nonparametric regression Francesco Giordano, Soumendra Nath Lahiri, and Maria Lucia Parrella
Post Hoc Confidence Bounds on False Positives Using Reference Families Gilles Blanchard, Pierre Neuvial, and Etienne Roquain
Distribution and Correlation Free Two-sample Test of High-dimensional Means Kaijie Xue and Fang Yao
Just Interpolate: Kernel “Ridgeless” Regression Can Generalize Tengyuan Liang and Alexander Rakhlin
Bridging the Gap between Constant Step Size Stochastic Gradient Descent and  Markov Chains Alain Durmus, Aymeric Dieuleveut, and Francis Bach
Nonparametric statistical inference for drift vector fields of multi-dimensional diffusions Richard Nickl and Kolyan Ray
Robust inference with knockoffs Rina Foygel Barber, Emmanuel J Candes, and Richard J Samworth
Nonparametric Bayesian Analysis of the Compound Poisson Prior For Support Boundary Recovery Johannes Schmidt-Hieber and Markus Reiss
Entrywise Eigenvector Analysis of Random Matrices with Low Expected Rank Emmanuel Abbe, Jianqing Fan, Kaizheng Wang, and Yiqiao Zhong
Concentration of tempered posteriors and of their variational approximations Pierre Alquier and James Ridgway
Robust and rate-optimal Gibbs posterior inference on the boundary of a noisy image Nicholas Aaron Syring and Ryan Martin
The Hardness of Conditional Independence Testing and the Generalised Covariance Measure Rajen Dinesh Shah and Jonas Peters
Some Theoretical Properties of GANs Gerard Biau, Cadre Benoit, Sangnier Maxime, and Ugo Tanielian
On post dimension reduction statistical inference Kyongwon Kim, Bing Li, Zhou Yu, and Lexin Li
Statistical and Computational Limits for Sparse Matrix Detection T. Tony Cai and Yihong Wu
Segmentation and estimation of change-point models David O. Siegmund, Xiao Fang, and Jian Li
Robust Covariance Estimation Under L4 − L2 Norm Equivalence Shahar Mendelson and Nikita Zhivotovskiy
Robust inference via multipler bootstrap Xi Chen and Wen-Xin Zhou
On the Optimal Reconstruction of Partially Observed Functional Data Alois Kneip and Dominik Liebl
Large Sample Properties of Partitioning-Based Series Estimators Matias D. Cattaneo, Max H. Farrell, and Yingjie Feng
Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score Qingyuan Zhao, Jingshu Wang, Gibran Hemani, Jack Bowden, and Dylan S Small
Local Uncertainty Sampling for Large-Scale Multi-Class Logistic Regression Lei Han, Kean Ming Tan, Ting Yang, and Tong Zhang
Local nearest neighbour classification with applications to semi-supervised learning Timothy Ivor Cannings, Thomas Benjamin Berrett, and Richard John Samworth
An adaptable generalization of Hotelling’s T2 test in high dimension Haoran Li, Alexander Aue, Debashis Paul, Jie Peng, and Pei Wang
On the validity of the formal Edgeworth expansion for posterior densities John E. Kolassa and Todd A. Kuffner
Model selection for high-dimensional linear regression with dependent observations Ching-Kang Ing
Optimal estimation of Gaussian mixtures via denoised method of moments Yihong Wu and Pengkun Yang
Sharp Instruments for Classifying Compliers and Generalizing Causal Effects Edward H Kennedy, Sivaraman Balakrishnan, and Max G’Sell
Empirical risk minimization and complexity of dynamical models Kevin McGoff and Andrew B. Nobel
Adaptive Estimation in  Structured  Factor Models with Applications to Overlapping Clustering Florentina Bunea, Mike Bing, Yang Ning, and Marten Wegkamp
Partial Identifiability of Restricted Latent Class Models Yuqi Gu and Gongjun Xu
Posterior Concentration for Bayesian Regression Trees and Their Ensembles Veronika Rockova and Stephanie van der Pas
Double-Slicing Assisted Sufficient Dimension Reduction for High Dimensional Censored Data Shanshan Ding, Wei Qian, and Lan Wang
Asymptotic frequentist coverage properties of Bayesian credible sets for sieve priors Judith Rousseau and Botond Szabo
Asymptotic joint distribution of extreme eigenvalues and trace of large sample covariance matrix in a generalized spiked population model Zeng Li, Fang Han, Jianfeng Yao
Convergence Rates of Variational Posterior Distributions Fengshuo Zhang and Chao Gao
Two-sample Hypothesis Testing for Inhomogeneous Random Graphs Debarghya Ghoshdastidar, Maurilio Gutzeit, Alexandra Carpentier, and Ulrike von Luxburg
Beyond HC: More sensitive tests for rare/weak alternatives Thomas Porter and Michael Stewart
Minimax optimal rates for Mondrian trees and forests Jaouad Mourtada, Stéphane Gaïffas, and Erwan Scornet
Identifiability of Nonparametric Mixture Models and Bayes Optimal Clustering Bryon Aragam, Chen Dan, Eric Xing, and Pradeep Ravikumar
A test for separability in covariance operators of random surfaces Pramita Bagchi and Holger Dette
A General Approach for Cure Models in Survival Analysis Valentin Patilea and Ingrid Van Keilegom
Adaptive distributed methods under communication constraints Botond Szabo and Harry van Zanten
Bayesian Analysis of the Covariance Matrix of a Multivariate Normal Distribution with a New Class of Priors James O Berger, Dongchu Sun, and Chengyuan Song
Extending the Validity of Frequency Domain Bootstrap Methods to General Stationary Processes Efstathios Paparoditis, Marco Meyer, and Jens-Peter Kreiss
Minimax  Estimation of Large Precision Matrices with Bandable Cholesky Factor Yu Liu and Zhao Ren
Estimation And Inference for Precision Matrices of Non-stationary Time Series Xiucai Ding and Zhou Zhou
Testing for stationarity of functional time series in the frequency domain Alexander Aue and Anne van Delft
Isotropic covariance functions on graphs and their edges Ethan Anderes, Jesper Møller, and Jakob Rasmussen
On spike and slab empirical Bayes multiple testing Ismael Castillo and Etienne Roquain
Theoretical and Computational Guarantees of Mean Field Variational Inference for Community Detection Anderson Y. Zhang and Harrison H. Zhou
Minimax Optimal Sequential Hypothesis Tests for Markov Processes Michael Fauss, Abdelhak Zoubir, and Harold Vincent Poor
Test of Significance for High-Dimensional Longitudinal Data Ethan X. Fang, Yang Ning,and Runze Li
Geometrizing  rates of convergence under local differential privacy constraints Angelika Rohde and Lukas Steinberger
Additive Regression with Hilbertian Responses Jeong Min Jeon and Byeong U Park
Nonparametric Bayesian Estimation of Multivariate Hawkes Processes Sophie Donnet, Vincent Rivoirard, and Judith Rousseau
Self-normalization for high dimensional time series Runmin Wang and Xiaofeng Shao
Variational Analysis of Constrained M-Estimators Johannes O Royset and Roger J-B Wets
Which Bridge Estimator is the Best for Variable Selection? Shuaiwen Wang, Haolei Weng, and Arian Maleki
Permutation methods for factor analysis and PCA Edgar Dobriban
Concordance and Value Information Criteria for Optimal Treatment Decision Chengchun Shi, Rui Song, and Wenbin Lu
A General Framework for Bayes Structured Linear Models Chao Gao, Aad van der Vaart, and Harrison Zhou
Nonparametric regression using deep neural networks with ReLU activation function Johannes Schmidt-Hieber
Discussion of “Nonparametric Regression using Deep Neural Networks with ReLU Activation Function” Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, and Andrea Montanari
Discussion of “Nonparametric Regression using Deep Neural Networks with ReLU Activation Function” Gitta Kutyniok
Discussion of “Nonparametric regression using deep neural networks with ReLU activation function” Michael Kohler and Langer Sophie
Discussion of  “Nonparametric Regression Using Deep Neural Networks with ReLU Activation Function” Ohad Shamir
Asymptotic Distribution and Detection Thresholds for Two-Sample Tests Based on Geometric Graphs Bhaswar Bikram Bhattacharya
Controlled Sequential Monte Carlo Jeremy Heng, Adrian Bishop, George Deligiannidis, and Arnaud Doucet
A Framework for Adaptive MCMC Targeting Multimodal Distributions Emilia Pompe, Chris Holmes, and Krzysztof Łatuszyński
Valid Post-selection Inference in Model-free Linear Regression Arun Kumar Kuchibhotla, Lawrence David Brown, Andreas Buja, Junhui Cai, Edward I. George, and Linda H. Zhou
Inference for spherical location under high concentration Davy Paindaveine and Thomas Verdebout
Semiparametric Bayesian causal inference Kolyan Ray and Aad van der Vaart
Relaxing the Assumptions of Knockoffs by Conditioning Dongming Huang and Lucas Janson
Analytical Nonlinear Shrinkage of Large-Dimensional Covariance Matrices Olivier Ledoit and Michael Wolf
Coupled conditional backward sampling particle filter Anthony Lee, Sumeetpal Sidhu Singh, and Matti Vihola
Asymptotic risk and phase transition of l_1-penalized robust estimator Hanwen Huang
Singularity, Misspecification, and Convergence Rate of the EM Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, and Bin Yu
Towards Optimal Estimation of Bivariate Isotonic Matrices with Unknown Permutations Cheng Mao, Ashwin Pananjady, and Martin Wainwright
High dimensional consistent independence testing with maxima of rank correlations Mathias Drton, Fang Han, and Hongjian Shi
Optimal rates of entropy estimation over Lipschitz balls Yanjun Han, Jiantao Jiao, Tsachy Weissman, and Yihong Wu
Limit distribution theory for block estimators in multiple isotonic regression Qiyang Han and Cun-Hui Zhang
Assessment of the extent of corroboration of an elaborate theory of a causal hypothesis using partial conjunctions of evidence factors Bikram Karmakar and Dylan S. Small
Fréchet Change-Point Detection Paromita Dubey and Hans-Georg Mueller
Rejoinder to discussions of “Nonparametric regression using deep neural networks with ReLU activation function” Johannes Schmidt-Hieber
Testability of High-Dimensional Linear Models with Non-Sparse Structures Jelena Bradic, Jianqing Fan, and Yinchu Zhu
Nonparametric drift estimation for  i.i.d. paths of stochastic differential equations Fabienne Comte and Valentine Genon-Catalot
Distance-based and RKHS-based Dependence Metrics in High Dimension Xiaofeng Shao, Changbo Zhu, Xianyang Zhang, and Shun Yao
The Distance Standard Deviation Dominic Edelmann, Donald Richards, and Daniel Vogel
Robust Multivariate Nonparametric Tests via Projection-Averaging Ilmun Kim, Sivaraman Balakrishnan, and Larry Wasserman
Inference for Conditional Value-at-Risk of a Predictive Regression Yi He, Yanxi Hou, Liang Peng, and Haipeng Shen
Simultaneous high-probability bounds on the false discovery proportion in structured, regression, and online settings Eugene Katsevich and Aaditya Ramdas
Clustering in Block Markov Chains Jaron Sanders, Alexandre Proutiere, and Se Young Yun
Model selection and local geometry Robin Evans
On the convergence of Hamiltonian Monte Carlo Alain Durmus, Eric Moulines, and Eero Saksman
Statistically Optimal and Computationally Efficient Low Rank Tensor Completion from Noisy Entries Dong Xia, Ming Yuan, and Cunhui Zhang
Test for High Dimensional Covariance Matrices Yuefeng Han and Wei Biao Wu
Optimal estimation of variance in nonparametric regression with random design Yandi Shen, Chao Gao, Daniela Witten, and Fang Han
Analysis of a Two-Layer Neural Network via Displacement Convexity Adel Javanmard, Marco Mondelli, and Andrea Montanari
Beyond Gaussian Approximation: Bootstrap for Maxima of Sums of Independent Random Vectors Hang Deng and Cun-Hui Zhang
Isotonic Regression in Multi-Dimensional Spaces and Graphs Hang Deng and Cun-Hui Zhang
Robust Bayes-Like Estimation: Rho-Bayes Estimation Yannick Baraud and Lucien Birgé
Transfer Learning for Nonparametric Classification: Minimax Rate and Adaptive Classifier Tony Cai and Hongji Wei
Adaptation in Multivariate Log-Concave Density Estimation Oliver Y. Feng, Adityanand Guntuboyina, Arlene K. H. Kim, and Richard J. Samworth
Asymptotically Independent U-Statistics in High-Dimensional Testing Yinqiu He, Gongjun Xu, Chong Wu, and Wei Pan
Frequentist validity of Bayesian limits Bas Kleijn
Optimal Change Point Detection and Localization in Sparse Dynamic Networks Daren Wang, Yi Yu, and Alessandro Rinaldo
Convergence of covariance and spectral density estimates for high dimensional locally stationary processes Danna Zhang and Wei Biao Wu
Wordlength Enumerator for Fractional Factorial Designs Yu Tang and Hongquan Xu
Estimating minimum effect with outlier selection Alexandra Carpentier, Sylvain Delattre, Etienne Roquain, and Nicolas Verzelen
Multiple block sizes and overlapping blocks for multivariate time series extremes Nan Zou, Stanislav Volgushev, and Axel Bücher
Estimation of Low-Rank Matrices via Approximate Message Passing Andrea Montanari and Ramji Venkataramanan
Asymptotics for Spherical Functional Autoregressions Alessia Caponera and Domenico Marinucci
Singular vector and singular subspace distribution for the matrix denoising model Zhigang Bao, Xiucai Ding, and Ke Wang
Robust multivariate mean estimation: the optimality of trimmed mean Gabor Lugosi and Shahar Mendelson
Classification accuracy as a proxy for two-sample testing Ilmun Kim, Aaditya Ramdas, Aarti Singh, and Larry Wasserman
Asymmetry Helps: Eigenvalue and Eigenvector Analyses of Asymmetrically Perturbed Low-Rank Matrices Yuxin Chen, Chen Cheng, and Jianqing Fan
Complex sampling designs:  uniform limit theorems and applications Jon A. Wellner and Qiyang Han
Predictive inference with the jackknife+ Rina Foygel Barber, Emmanuel J Candes, Aaditya Ramdas, and Ryan J Tibshirani
Robust Estimation of Superhedging Prices Jan Krzysztof Obloj and Johannes Wiesel
Concentration of kernel matrices with application to kernel spectral clustering Arash Ali Amini and Zahra Sadat Razaee