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Papers to Appear in Subsequent Issues

Graph connection laplacian methods can be made robust to noise

Noureddine El Karoui and Hau-tieng Wu

Efficient Calibration for Imperfect Computer Models

Rui Tuo and Jeff Wu

Functional Linear Regression with Points of Impact

Alois Kneip, Dominik Poss, and Pascal Sarda

Fully Adaptive Density-Based Clustering

Ingo Steinwart

Minimax Estimation in Sparse Canonical Correlation Analysis

Harrison Zhou, Chao Gao, Zongming Ma, and Zhao Ren

A General Bernstein--von Mises Theorem in semiparametric models

Ismael Castillo and Judith Rousseau

Subsampling Bootstrap of Count Features of Networks

Sharmodeep Bhattacharyya and Peter J Bickel

Computing exact D-optimal designs by mixed integer second order cone programming

Guillaume Sagnol and Radoslav Harman

Globally adaptive quantile regression with ultra-high dimensional data

Qi Zheng, Limin Peng, and Xuming He

On adaptive posterior concentration rates

Marc Hoffmann, Judith Rousseau, and Johannes Schmidt-Hieber

Asymptotics in directed exponential random graph models with an increasing bi-degree sequence

Ting Yan, Chenlei Leng, and Ji Zhu

Aggregation of predictors for non stationary sub-linear processes and online adaptive forecasting of time varying autoregressive processes

Andres Sanchez-Perez, François Roueff, and Christophe Giraud

Functional Additive Regression

Yingying Fan, Gareth James, and Peter Radchenko

Simultaneous confidence bands for change point tests in high dimension

Moritz Jirak

Coupling methods for multistage sampling

Guillaume Chauvet

Near-optimal estimation of jump activity in semimartingales

Adam David Bull

Empirical risk minimization for heavy-tailed losses

Gabor Lugosi, Christian Brownlees, and Emilien Joly

Bootstrap and permutation tests of independence for point processes

Mélisande Albert, Yann Bouret, Magalie Fromont, and Patricia Reynaud-Bouret

Optimal Experimental Designs for fMRI via Circulant Biased Weighing Designs

Ming-Hung Kao and Ching-Shui Cheng

Spectral statistics of large dimensional Spearman's rank correlation matrix and its application

Zhigang Bao, Liang-Ching Lin, Guangming Pan, and Wang Zhou

Rate-optimal Graphon Estimation

Gao Chao, Yu Lu, and Harrison Zhou

Bootstrap confidence sets under model misspecification

Vladimir Spokoiny and Mayya Zhilova

Model Selection and Structure Specification in Ultra-High Dimensional Generalised Semi-Varying Coefficient Models

Degui Li, Yuan Ke, and Wenyang Zhang

Estimation of Functionals of Sparse Covariance Matrices

Jianqing Fan, Philippe Rigollet, and Weichen Wang

Inference using noisy degrees - Differentially private beta model and synthetic graphs

Vishesh Karwa and Aleksandra Slavkovic

Bridging centrality and extremity: refining empirical data depth using extreme value statistics

John H.J. Einmahl, Jun Li, and Regina Y. Liu

Optimization via Low-rank Approximation for Community Detection in Networks

Can M. Le, Elizaveta Levina, and Roman Vershynin

Optimal designs in regression with correlated errors

Holger Dette, Andrey Pepelyshev, and Anatoly Zhigljavsky

Asymptotics for change-point models under varying degrees of mis-specification

Rui Song, Moulinath Banerjee, and Michael Kosorok

Functional data analysis for density functions by transformation to a Hilbert space

Alexander Petersen and Hans-Georg Müller

Projected Principal Component Analysis in Factor Models

Jianqing Fan, Yuan Liao, and Weichen Wang

Estimating the Smoothness of a Gaussian Random Field from Irregularly Spaced Data Via Higher-Order Quadratic Variations

Wei-Liem Loh

Adaptation to lowest density regions with application to support recovery

Tim Patschkowski and Angelika Rohde

Additive Partially Linear Quantile Regression in Ultra-high Dimension

Ben Sherwood and Lan Wang

Adaptive Bayesian Estimation via Block Prior

Chao Gao and Harrison Zhou

Statistical and computational trade-offs in estimation of sparse principal components

Tengyao Wang, Quentin Berthet, and Richard John Samworth

A Goodness-of-fit Test for Stochastic Block Models

Jing Lei

Exact Post-Selection Inference, with Application to the Lasso

Jason D Lee, Dennis L Sun, Yuekai Sun, and Jonathan E Taylor

Estimation for single-index and partially linear single-index integrated models

Chaohua Dong, Jiti Gao, and Dag Bjarne Tjostheim

Nonparametric Modal Regression

Yen-Chi Chen, Christopher R. Genovese, Ryan J. Tibshirani, and Larry Wasserman

Local Independence Feature Screening for Nonparametric and Semiparametric Models by Marginal Empirical Likelihood

Jinyuan Chang, Cheng Yong Tang, and Yichao Wu

Cramér Type Moderate Deviations for Studentized Two-Sample U-statistics with Applications

Jinyuan Chang, Qi-Man Shao, and Wen-Xin Zhou

Estimating multivariate latent-structure models

Koen Jochmans, Stephane Bonhomme, and Jean-Marc Robin

Optimal Shrinkage Estimation of Mean Parameters in Family of Distributions with Quadratic Variance

Xianchao Xie, Samuel Kou, Lawrence Brown

Large sample behaviour of high dimensional autocovariance matrices

Monika Bhattacharjee and Arup Bose

Estimation in Nonlinear Regression with Harris Recurrent Markov Chains

Degui Li, Dag Tjostheim, and Jiti Gao

Global solutions to folded concave penalized nonconvex learning

Hongcheng Liu, Tao Yao, and Runze Li

Batched Bandit Problems

Vianney Perchet, Philippe Rigollet, Sylvain Chassang, and Erik Snowberg

Optimal Large-Scale Quantum State Tomography with Pauli Measurements

Yazhen Wang, Tony Cai, Donggyu Kim, Ming Yuan, and Harrison Zhou

A Rate Optimal Procedure for Recovering Sparse Differences between High-Dimensional Means under Dependence

Jun Li and Ping-Shou Zhong

Statistical Inference for the Mean Outcome Under a Possibly Non-Unique Optimal Treatment Strategy

Alexander R Luedtke and Mark J van der Laan

Efficient estimation in semivarying coefficient models for longitudinal/clustered data

Ming-Yen Cheng, Toshio Honda, and Jialiang Li

Inference in Adaptive Regression via the Kac-Rice formula

Jonathan Edward Taylor, Joshua Loftus, and Ryan Tibshirani

Amplitude and Phase Variation of Generalised Functional Data

Victor Michael Panaretos and Yoav Zemel

Best Subset Selection via a Modern Optimization Lens

Dimitris Bertsimas, Angela King, and Rahul Mazumder

Estimation in exponential families on permutations

Sumit Mukherjee

Bayesian manifold regression

Yun Yang and David B. Dunson

Non-Parametric Stochastic Approximation with large step sizes

Aymeric Dieuleveut and Francis Bach

Partial Correlation Screening for estimating large precision matrices, with applications to classification

Jiashun Jin, Shiqiong Huang Huang, and Zhigang Yao

Nonparametric Eigenvalue-Regularized Precision or Covariance Matrix Estimator

Clifford Lam

Global Rates of Convergence of the MLEs of Log-Concave and S-Concave Densities

Charles R Doss and Jon A Wellner

Classification with the nearest neighbor rule in general finite dimensional spaces

Sébastien Gadat, Thierry Klein, and Clément Marteau

A new prior for discrete DAG models with a restricted set of directions

Helene Menexia Massam and Jacek Wesolowski

Slope is Adaptive to Unknown Sparsity and Asymptotically Minimax

Weijie Su and Emmanuel Candes

Supremum Norm Posterior Contraction and Credible Sets for Nonparametric Multivariate Regression

William Weimin Yoo and Subhashis Ghosal

Optimal designs for comparing curves

Holger Dette and Kirsten Schorning

Randomization-based models for multitiered experiments: I. A chain of randomizations

Rosemary Anne Bailey and Christopher J. Brien

Vector Quantile Regression: An Optimal Transport Approach

Guillaume Carlier, Victor Chernozhukov, and Alfred Galichon

Local intrinsic stationarity and its inference

Tailen Hsing, Thomas Brown, and Brian Thelen

Structure Identification in Panel Data Analysis

Yuan Ke, Jialiang Li, and Wenyang Zhang

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