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Papers to Appear in Subsequent Issues

Fully Adaptive Density-Based Clustering

Ingo Steinwart

Minimax Estimation in Sparse Canonical Correlation Analysis

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

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 rates5

Marc Hoffmann, Judith Rousseau, and Johannes Schmidt-Hieber

Functional Additive Regression

Yingying Fan, Gareth James, and Peter Radchenko

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

Tengyao Wang, Quentin Berthet, and Richard John Samworth

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

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

Estimation in Nonlinear Regression with Harris Recurrent Markov Chains

Degui Li, Dag Tjostheim, and Jiti Gao

Efficient estimation in semivarying coefficient models for longitudinal/clustered data

Ming-Yen Cheng, Toshio Honda, and Jialiang Li

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

Jiashun Jin, Shiqiong Huang Huang, and Zhigang Yao

Local intrinsic stationarity and its inference

Tailen Hsing, Thomas Brown, and Brian Thelen

An unexpected encounter with Cauchy and Levy

Natesh S Pillai and Xiao-Li Meng

Nonparametric estimation of dynamics of monotone trajectories

Debashis Paul, Jie Peng, and Prabir Burman

Causal Inference with a Graphical Hierarchy of Interventions

Ilya Shpitser and Eric Tchetgen Tchetgen

Consistent model selection criteria for quadratically supported risks

Yongdai Kim and Jong-June Jeon

Tensor decompositions and sparse log-linear models

James Edward Johndrow, Anirban Bhattacharya, and David Dunson

Innovated Scalable Efficient Estimation in Ultra-Large Gaussian Graphical Models

Yingying Fan and Jinchi Lv

On the computational complexity of high-dimensional Bayesian variable selection

Yun Yang, Martin J. Wainwright, and Michael I. Jordan

Family wise separation rates for multiple testing

Magalie Fromont, Matthieu Lerasle, and Patricia Reynaud-Bouret

On High-dimensional Misspecified Mixed Model Analysis in Genome-wide Association Study

Jiming Jiang, Cong Li, Debashis Paul, Can Yang, and Hongyu Zhao

Minimax Optimal Rates of Estimation in High Dimensional Additive Models: Universal Phase Transition

Ming Yuan and Ding-Xuan Zhou

Influential Features PCA for high dimensional clustering

Jiashun Jin and Wanjie Wang

On Marginal Sliced Inverse Regression For Ultrahigh Dimensional Model Free Feature Selection

Zhou Yu, Yuexiao Dong, and Jun Shao

Faithful variable screening for high-dimensional convex regression

Min Xu, Minhua Chen, and John Lafferty

Minimax Rates of Community Detection in Stochastic Block Models

Anderson Y. Zhang and Harrison H. Zhou

High-Dimensional Generalizations of Asymmetric Least Squares Regression and Their Applications

Yuwen Gu and Hui Zou

Minimax estimation of linear and quadratic functionals on sparsity classes

Olivier Collier, Laetitia Comminges, and Alexandre Tsybakov

Mimicking counterfactual outcomes to estimate causal effects

Judith Jacqueline Lok

A lava attack on the recovery of sums of dense and sparse signals

Victor Chernozhukov, Christian Hansen, and Yuan Liao

Statistical Guarantees for the EM Algorithm: From Population to Sample-Based Analysis

Sivaraman Balakrishnan, Martin J Wainwright, and Bin Yu

Normal approximation and concentration of spectral projectors of sample covariance

Vladimir Koltchinskii and Karim Lounici

Asymptotic Theory for the First Projective Direction

Michael G. Akritas

Sub-Gaussian mean estimators

Luc Devroye, Matthieu Lerasle, Gabor Lugosi, and Roberto Imbuzeiro Oliveira

Nonparametric covariate-adjusted regression

Aurore Delaigle, Peter Hall, and Wen-Xin Zhou

Optimal Rates of Convergence for Noisy Sparse Phase Retrieval via Thresholded Wirtinger Flow

T.Tony Cai, Xiaodong Li, and Zongming Ma

Convergence rates of parameter estimation for some weakly identifiable finite mixtures

Nhat Ho and XuanLong Nguyen

From Sparse to Dense Functional Data and Beyond

Xiaoke Zhang and Jane-Ling Wang

A General Theory of Hypothesis Tests and Confidence Regions for Sparse High Dimensional Models

Yang Ning and Han Liu

A Bayesian Approach for Envelope Models

Kshitij Khare, Subhadip Pal, and Zhihua Su

Monge-Kantorovich depth, quantiles, ranks, and signs

Victor Chernozhukov, Alfred Galichon, Marc Hallin, and Marc Henry

Identifying the number of factors from singular values of a large sample auto-covariance matrix

Zeng Li, Qinwen Wang, and Jianfeng Yao

Consistency of Spectral Hypergraph Partitioning under Planted Partition Model

Debarghya Ghoshdastidar and Ambedkar Dukkipati

Oracle inequalities for network models and sparse graphon estimation

Olga Klopp, Alexandre Tsybakov, and Nicolas Verzelen

Approximate Group Context Tree

Alexandre Belloni and Roberto Imbuzeiro Oliveira

Flexible results for quadratic forms with applications to variance components estimation

Lee H. Dicker and Murat A. Erdogdu

Likelihood-based model selection for stochastic block modelsLikelihood-based model selection for stochastic block models

Y.X. Rachel Wang and Peter J Bickel

Multiple Testing of Local Maxima for Detection of Peaks in Random Fields

Dan Cheng and Armin Schwartzman

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

Jun Li and Ping-Shou Zhong

Online estimation of the geometric median in Hilbert spaces : non asymptotic confidence balls

Hervé Cardot, Peggy Cénac, Antoine Godichon-Baggioni

Confidence Intervals for High-Dimensional Linear Regression: Minimax Rates and Adaptivity

Tony Cai and Zijian Guo

Estimating the effect of joint interventions from observational data in sparse high-dimensional settings

Preetam Nandy, Marloes H. Maathuis, and Thomas S. Richardson

Extreme eigenvalues of large-dimensional spiked Fisher matrices with application

Jianfeng Yao and Qinwen Wang

Identifiability of restricted latent class models with binary responses

Gongjun Xu

A Bernstein-type Inequality for Some Mixing Processes and Dynamical Systems with an Application to Learning

Ingo Steinwart and Hanyuan Hang

Consistency of likelihood estimation for Gibbs point processes

Frédéric Lavancier and David Dereudre

Tests for high dimensional data based on means, spatial signs and spatial ranks

Anirvan Chakraborty and Probal Chaudhuri

Inference on the mode of weak directional signals: A Le Cam perspective on hypothesis testing near singularities

Davy Paindaveine and Thomas Verdebout

Asymptotic behaviour of the empirical Bayes posteriors associated to maximum marginal likelihood estimator

Botond Szabo and Judith Rousseau

Support Consistency of Direct Sparse-Change Learning in Markov Networks

Song Liu, Suzuki Taiji, Raissa Relator, Jun Sese, Masashi Sugiyama, and Kenji Fukumizu

Statistical consistency and asymptotic normality for high-dimensional robust M-estimators

Po-Ling Loh

Randomized sketches for kernels: Fast and optimal non-parametric regression

Yun Yang, Mert Pilanci, and Martin J. Wainwright

Testing uniformity on high-dimensional spheres against monotone rotationally symmetric alternatives

Christine Cutting, Davy Paindaveine, and Thomas Verdebout

Discussion of AOS1423

Ery Arias-Castro and Nicolas Verzelen

Discussion of Influential Features PCA for High Dimensional Clustering

Boaz Nadler

Discussion of "Influential Features PCA for High Dimensional Clustering"

Tony Cai and Linjun Zhang

Discussion of "Influential Features PCA for High Dimensional Clustering", By J. Jin and W. Wang

Alexandre Tsybakov and Natalia A. Stepanova

Interaction pursuit in high-dimensional multi-response regression via distance correlation

Yinfei Kong, Daoji Li, Yingying Fan, and Jinchi Lv

Nonlinear Sufficient Dimension Reduction for Functional Data

Bing Li and Jun Song

Network Vector Autoregression

Xuening Zhu, Rui Pan, Guodong Li, Yuewen Liu, and Hansheng Wang

On coverage and local radial rates of credible sets

Eduard Belitser

Total positivity in Markov structures

Shaun Fallat, Steffen Lauritzen, Kayvan Sadeghi, Caroline Uhler, Nanny Wermuth, and Piotr Zwiernik

On the Optimality of Bayesian Change-Point Detection

Dong Han, Fugee Tsung, and Jinguo Xian

Global rates of convergence in log-concave density estimation

Arlene Kyoung Hee Kim and Richard John Samworth

Tests for Covariance Structures with High-dimensional Repeated Measurements

Ping-Shou Zhong, Wei Lan, Peter X.K. Song, and Chih-Ling Tsai

Weak Signal Identification and Inference in Model Selection

Peibei Shi and Annie Qu

A Likelihood Ratio Framework for High Dimensional Semiparametric Regression

Yang Ning, Tianqi Zhao, and Han Liu

Semimartingale detection and goodness-of-fit tests

Adam David Bull

Testing for Time-Varying Jump Activity for Pure Jump Semimartingales

Viktor Todorov

Operational time and in-sample density forecasting

Young Kyung Lee, Enno Mammen, Jens P. Nielsen, and Byeong U. Park

Asymptotics of Empirical Eigen-structure for High Dimensional Spiked Covariance

Weichen Wang and Jianqing Fan

Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix

T. Tony Cai, Tengyuan Liang, and Alexander Rakhlin

Peter Hall's Contributions to the Boostrap

Song X Chen

Peter Hall's Contributions to NonParametric Function Estimation and Modeling

Ming-Yen Cheng and Jianqing Fan

Peter Hall's Main Contributions to Deconvulution

Aurore Delaigle

Peter Hall, Functional Data Analysis and Random Objects

Hans-Georg Müller

Peter Hall's Work on High-Dimensional Data and Classification

Richard John Samworth

Editorial

Runze Li

Tests for separability in nonparametric covariance operators of random surfaces

John Aston, Davide Pigoli, and Shahin Tavakoli

Identification of universally optimal circular designs for the interference model

Wei Zheng, Mingyao Ai, and Kang Li

Co-clustering of Nonsmooth Graphons

David Choi

Minimax theory of estimation of linear functionals of the deconvolution density with or without sparsity

Marianna Pensky

Nonparametric change-point analysis of volatility

Markus Bibinger, Moritz Jirak, and Mathias Vetter

A new approach to optimal designs for correlated observations

Holger Dette, Maria Konstantinou, and Anatoly Zhigljavsky

Rejoinder

Jiashun Jin and Wanjie Wang

Rare-event Analysis for Extremal Eigenvalues of white Wishart matrices

Tiefeng Jiang, Kevin Leder, and Gongjun Xu

Robust Discrimination Designs over Hellinger Neighbourhoods

Rui Hu and Douglas P. Wiens

Nonparametric Bayesian Posterior Contraction Rates for Discretely Observed Scalar Diffusions

Richard Nickl and Jakob Soehl
 
   
 
 

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