Papers to Appear in Subsequent Issues

Community Detection on Mixture Multi-Layer Networks Via Regularized Tensor Decomposition Bing-Yi Jing, Ting Li, Zhongyuan Lyu, and Dong Xia
Continuous-time targeted minimum loss-based estimation of intervention-specific mean outcomes Helene Charlotte Rytgaard, Thomas A. Gerds, and Mark J. van der Laan
Convergence of de Finetti’s mixing measure in latent structure models for observed exchangeable sequences Yun Wei and XuanLong Nguyen
Correction to: Asymptotic genealogies of interacting particle systems with an application to sequential Monte Carlo Jere Koskela, Paul A Jenkins, Adam M Johansen, and Dario Spano
Conditional Calibration for False Discovery Rate Control Under Dependence William Fithian and Lihua Lei
Detecting Multiple Replicating Signals using Adaptive Filtering Procedures Jingshu Wang, Lin Gui, Weijie J. Su, Chiara Sabatti, and Art B. Owen
Optimal signal detection in some spiked random matrix models: likelihood ratio tests and linear spectral statistics Debapratim Banerjee and Zongming Ma
On universally consistent and fully distribution-free rank tests of vector independence Hongjian Shi, Marc Hallin, Mathias Drton, and Fang Han
Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives Hussein Hazimeh, Rahul Mazumder, and Peter Radchenko
Limit theorems for distributions invariant under groups of transformations Morgane Austern and Peter Orbanz
Distributed Adaptive Gaussian Mean Estimation with Unknown Variance: Interactive Protocol Helps Adaptation Tony Cai and Hongji Wei
Asymptotic accuracy of the saddlepoint approximation for maximum likelihood estimation Jesse Goodman
Generalization Error Bounds of Dynamic Treatment Regimes in Regression-Based Learning Eun Jeong Oh, Min Qian, and Ken Cheung
A CLT for second difference estimators with an application to volatility and intensity Emil Aas Stoltenberg, Per Aslak Mykland, and Lan Zhang
Sharp optimal recovery in the two Component Gaussian Mixture Model Mohamed Ndaoud
Precise Statistical Analysis of Classification Accuracies for Adversarial Training Adel Javanmard and Mahdi Soltanolkotabi
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices Jaouad Mourtada
Stochastic Continuum-armed Bandits with Additive Models: Minimax Regrets and Adaptive Algorithm Tony Cai and Hongming Pu
Asymptotic independence of spiked eigenvalues and linear spectral statistics for large sample covariance matrices Zhixiang Zhang, Shurong Zheng, Guangming Pan, and Pingshou Zhong
Central Limit Theorem and Bootstrap Approximation in High Dimensions: Near 1/√n R Rates via Implicit Smoothing Miles Lopes
Learning Mixtures of Permutations: Groups of Pairwise Comparisons and Combinatorial Method of Moments Cheng Mao and Yihong Wu
Generalized resilience and robust statistics Banghua Zhu, Jiantao Jiao, and Jacob Noah Steinhardt
Testing Goodness-of-Fit and Conditional Independence with Approximate Co-Sufficient Sampling Rina Foygel Barber and Lucas Janson
Nonregular and Minimax Estimation of Individualized Thresholds in High Dimension with Binary Responses Huijie Feng, Yang Ning, and Jiwei Zhao
A No-Free-Lunch Theorem for Multitask Learning Steve Hanneke and Samory Kpotufe
On the robustness of minimum-norm interpolators Geoffrey Chinot, Matthias Löffler, and Sara van de Geer
Random Graph Asymptotics for Treatment Effect Estimation under Network Interference Shuangning Li and Stefan Wager
New Edgeworth-type expansions with finite sample guarantees Mayya Zhilova
Improved Central Limit Theorem and Bootstrap Approximations in High Dimensions Victor Chernozhukov, Denis Chetverikov, Kengo Kato, and Yuta Koike
Characterizing the SLOPE Trade-off: A Variational Perspective and the Donoho-Tanner Limit Zhiqi Bu, Jason Matthew Klusowski, Cynthia Rush, and Weijie J Su
Bounds on the Conditional and Average Treatment Effect with Unobserved Confounding Factors Steve Yadlowsky, Hongseok Namkoong, Sanjay Basu, John C Duchi, and Lu Tian
An ℓp theory of PCA and spectral clustering Emmanuel Abbe, Jianqing Fan, and Kaizheng Wang
Estimation of Smooth Functionals in High-Dimensional Models: Bootstrap Chains and Gaussian Approximation Vladimir Koltchinskii
A minimax framework for quantifying risk-fairness trade-off in regression Evgenii Chzhen and Nicolas Schreuder
Affine-equivariant inference for multivariate location under Lp loss functions Alexander Dürre and Davy Paindaveine
Consistency of invariance-based randomization tests Edgar Dobriban
Is infinity that far? A  Bayesian nonparametric perspective of finite mixture models Raffaele Argiento and Maria De Iorio
Global and Individualized Community Detection in Inhomogeneous Multilayer Networks Shuxiao Chen, Sifan Liu, and Zongming Ma
Inference of Synchrosqueezing Transform – Toward a Unified Statistical Analysis of Nonlinear-Type Time-Frequency Analysis Hau-tieng Wu, Matt Sourisseau, and Zhou Zhou
Approximate Kernel PCA Using Random Features: Computational vs. Statistical Trade-off Bharath Sriperumbudur and Nicholas Sterge
Graphical models for nonstationary time series Sumanta Basu and Suhasini Subba Rao
Corrigendum: Asymptotic spectral theory for nonlinear time series Yi Zhang, Xiaofeng Shao, and Weibiao Wu
Optimal estimation of high-dimensional Gaussian mixtures Natalie Doss, Pengkun Yang, Yihong Wu, and Harrison Zhou
Relaxing the Gaussian assumption in Shrinkage and SURE in high dimension Larry Goldstein, Max Fathi, Gesine Reinert, and Adrien Saumard
Nonparametric Bivariate Density Estimation for Censored Lifetimes Sam Efromovich
Linear biomarker combination for constrained classification Yijian Huang and Martin G. Sanda
The Interpolation Phase Transition In Neural Networks: Memorization And Generalization Under Lazy Training Andrea Montanari and Yiqiao Zhong
A Sieve Stochastic Gradient Descent Estimator for Online Nonparametric Regression in Sobolev ellipsoids Tianyu Zhang and Noah Simon
Nonparametric Bayesian inference for reversible multi-dimensional diffusions Matteo Giordano and Kolyan Ray
Scalable estimation and inference for censored quantile regression process Xuming He, Xiaoou Pan, Kean Ming Tan, and Wenxin Zhou
A Study of Orthogonal Array-Based Designs Under a Broad Class of Space-Filling Criteria Guanzhou Chen and Boxin Tang
Two-sample testing of high-dimensional linear regression coefficients via complementary sketching Fengnan Gao and Tengyao Wang
Optimization Hierarchy for Fair Statistical Decision Problems Anil Aswani and Matt Olfat
Nonparametric Regression on Lie Groups with Measurement Errors Jeong Min Jeon, Byeong U Park, and Ingrid Van Keilegom
Locally associated graphical models and mixed convex exponential families Steffen Lauritzen and Piotr Zwiernik
Estimation of time series models using residuals dependence measures Carlos Velasco