Papers to Appear in Subsequent Issues

When papers are accepted for publication, they will appear below. Any changes that are made during the production process will only appear in the final version. Papers listed here are not updated during the production process and are removed once an issue is published.

Graphical models for nonstationary time series Sumanta Basu and Suhasini Subba Rao
The Right Complexity Measure in Locally Private Estimation: It is not the Fisher Information John Duchi and Feng Ruan
Testing network correlation efficiently via counting trees Cheng Mao, Yihong Wu, Jiaming Xu, and Sophie H. Yu
Bootstrapping Persistent Betti Numbers and Other Stabilizing Statistics Benjamin Thomas Roycraft, Johannes Krebs, and Wolfgang Polonik
On lower bounds for the bias-variance trade-off Alexis Derumigny and Johannes Schmidt-Hieber
A Cross Validation Framework for Signal Denoising with Applications to Trend Filtering, Dyadic Cart and Beyond Sabyasachi Chatterjee and Anamitra Chaudhuri
Off-Policy Evaluation in Partially Observed Markov Decision Processes under Sequential Ignorability Yuchen Hu and Stefan Wager
Maximum likelihood for high-noise group orbit estimation and single-particle cryo-EM Zhou Fan, Roy R. Lederman, Yi Sun, Tianhao Wang, and Sheng Xu
StarTrek: Combinatorial Variable Selection with False Discovery Rate Control Lu Zhang and Junwei Lu
Optimal Change-Point Detection and Localization Nicolas Verzelen, Magalie Fromont, Matthieu Lerasle, and Patricia Reynaud-Bouret
Noisy linear inverse problems under convex constraints: exact risk asymptotics in high dimensions Qiyang Han
Projected State-action Balancing Weights for Offline Reinforcement Learning Jiayi Wang, Zhengling Qi, and Raymond K. W. Wong
Post-Selection Inference via Algorithmic Stability Tijana Zrnic and Michael I. Jordan
Bridging Factor and Sparse Models Marcelo C Medeiros, Jianqing Fan, and Ricardo Masini
Matching recovery threshold for correlated random graphs Jian Ding and Hang Du
Learning Low-Dimensional Nonlinear Structures from High-Dimensional Noisy Data: An Integral Operator Approach Xiucai Ding and Rong Ma
Single Index Fréchet Regression Satarupa Bhattacharjee and Hans-Georg Müller
The Impacts of  Unobserved Covariates on  Covariate-Adaptive Randomized Experiments Yang Liu and Feifang Hu
Universality of regularized regression estimators in high dimensions Qiyang Han and Yandi Shen
Sharp Optimality for High Dimensional Covariance Testing under Sparse Signals Song X Chen, Yumou Qiu, and Shuyi Zhang
Testing Nonparametric Shape Restrictions Javier Hidalgo and Tatiana Komarova
Estimation of mixed fractional stable processes using high-frequency data Fabian Mies and Mark Podolskij
Efficient Estimation of the Maximal Association between Multiple Predictors and a Survival Outcome Tzu-Jung Huang, Alex Luedtke, and Ian W. McKeague
Statistical Inference on a Changing Extreme Value Dependence Structure Holger Drees
Relaxing the I.I.D. Assumption: Adaptively Minimax Optimal Regret via Root-Entropic Regularization Blair Bilodeau, Jeffrey Negrea, and Daniel M. Roy
Assigning Topics to Documents by Successive Projections Olga Klopp, Maxim Panov, Suzanne Sigalla, and Alexandre Tsybakov
Order-of-addition orthogonal arrays to study the effect of treatment ordering Eric D. Schoen and Robert W. Mee
Carving model-free inference Snigdha Panigrahi
Adaptive and Robust Multi-task Learning Yaqi Duan and Kaizheng Wang
Inference for extremal regression with dependent heavy-tailed data Abdelaati Daouia, Gilles Stupfler, and Antoine Usseglio-Carleve
Differentially private inference via noisy optimization Marco Avella-Medina, Casey Bradshaw, and Po-Ling Loh
Robust High-Dimensional Tuning Free Multiple Testing Jianqing Fan, Zhipeng Lou, and Mengxin Yu
Nonparametric conditional local independence testing Alexander Mangulad Christgau, Lasse Petersen, and Niels Richard Hansen
On backward smoothing algorithms Hai-Dang Dau and Nicolas Chopin
Characterization of causal ancestral graphs for time series with latent confounders Andreas Gerhardus
Optimal Nonparametric Testing of Missing Completely at Random, and its Connections to Compatibility Thomas Benjamin Berrett and Richard J Samworth
The Lasso with general Gaussian designs with applications to hypothesis testing Michael Celentano, Andrea Montanari, and Yuting Wei
Optimal subgroup selection Henry William Joseph Reeve, Richard Samworth, and Timothy Cannings
Adjusted chi-square test for degree-corrected block models Linfan Zhang and Arash Ali Amini
Local Whittle estimation of high-dimensional long-run variance and precision matrices Changryong Baek, Marie-Christine Düker, and Vladas Pipiras