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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 rates

Marc Hoffmann, Judith Rousseau, and Johannes Schmidt-Hieber

Functional Additive Regression

Yingying Fan, Gareth James, and Peter Radchenko

A Likelihood Ratio Framework for High Dimensional Semiparametric Regression

Yang Ning, Tianqi Zhao, and Han Liu

A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives

Rahul Mazumder, Robert Freund, and Paul Grigas

'Local' vs. 'global' parameters -- breaking the gaussian complexity barrier

Shahar Mendelson

Confounder Adjustment in Multiple Hypothesis Testing

Jingshu Wang, Qingyuan Zhao, Trevor Hastie, and Art B. Owen

Gaussian Approximation for High Dimensional Time Series

Danna Zhang and Wei Biao Wu

Detection and Feature Selection in Sparse Mixture Models

Nicolas Verzelen and Ery Arias-Castro

Minimax Estimation of a Functional on a Structured High-Dimensional Model

James M. Robins, Lingling Li, Rajarshi Mukherjee, Eric Tchetgen Tchetgen, and Aad van der Vaart

Asymptotic theory of generalized estimating equations based on jack-knife pseudo-observations

Morten Overgaard, Erik Thorlund Parner, and Jan Pedersen

Bayesian Poisson Calculus for Latent Feature Modeling via Generalized Indian Buffet Process Priors

Lancelot Fitzgerald James

Information-regret compromise in covariate-adaptive treatment allocation

Asya Metelkina and Luc Pronzato

Sparse CCA: Adaptive Estimation and Computational Barriers

Chao Gao, Zongming Ma, and Harrison Zhou

Optimal designs for dose response curves with common parameters

Chrystel Feller, Kirsten Schorning, Holger Dette, Georgina Bermann, and Björn Bornkamp

False Discoveries occur Early on the Lasso Path

Weijie Su, Malgorzata Bogdan, and Emmanuel Candes

Phase transitions for high dimensional clustering and related problems

Jiashun Jin, Zheng Tracy Ke, and Wanjie Wang

Bayesian Detection of Image Boundaries

Meng Li and Subhashis Ghosal

On the validity of resampling methods under long memory

Murad S. Taqqu and Shuyang Bai

Spectrum Estimation from Samples

Weihao Kong and Gregory Valiant

On the contraction properties of some high-dimensional quasi-posterior distributions

Yves F Atchadé

CoCoLasso for High-dimensional Error-in-variables Regression

Abhirup Datta and Hui Zou

Nonasymptotic Analysis of Semiparametric Regression Models with High-Dimensional Parametric Coefficients

Ying Zhu

Consistent Parameter Estimation for LASSO and Approximate Message Passing

Ali Mousavi, Arian Maleki, and Richard G. Baraniuk

Support recovery without incoherence: A case for nonconvex regularization

Po-Ling Loh and Martin Wainwright

Optimal Design of fMRI Experiments Using Circulant (Almost-)Orthogonal Arrays

Yuan-Lung Lin, Frederick Kin Hing Phoa, and Ming-Hung Kao

Chernoff Index for Cox Test of Separate Parametric Families

Xiaoou Li, Jingchen Liu, and Zhiliang Ying

Adaptive Bernstein-von Mises theorems in Gaussian white noise

Kolyan Ray

Targeted sequential design for targeted learning inference of the optimal treatment rule and its mean reward

Antoine Chambaz, Wenjing Zheng, and Mark J van der Laan

Nonparametric goodness-of-fit tests for uniform stochastic ordering

Chuan-Fa Tang, Dewei Wang, and Joshua M Tebbs

Selecting the Number of Principal Components: Estimation of the True Rank of a Noisy Matrix

Yunjin Choi, Jonathan Taylor, and Robert Tibshirani

Extended Conditional Independence and Applications in Causal Inference

Panayiota Constantinou and A. Philip Dawid

A weight-relaxed model averaging approach for exploiting high dimensionality, weak signals and model misspecification in generalized linear models

Tomohiro Ando and Ker-chau Li

Structural similarity and difference testing on multiple sparse Gaussian graphical models

Liu Weidong

Optimal bounds for aggregation of affine estimators

Pierre C. Bellec

Rate-Optimal Perturbation Bounds for Singular Subspaces with Applications to High-Dimensional Statistics

T. Tony Cai and Anru Zhang

Estimating a probability mass function with unknown labels

Dragi Anevski, Richard D. Gill, and Stefan Zohren

Exact formulas for the normalizing constants of Wishart distributions for graphical models

Caroline Uhler, Alex Lenkoski, and Donald Richards

Consistent Parameter Estimation for LASSO and Approximate Message Passing

Ali Mousavi, Arian Maleki, and Richard G. Baraniuk

On semidefinite relaxations for the block model

Arash Ali Amini and Elizaveta Levina

Optimal Sequential Detection in Multi-Stream Data

Hock Peng Chan

A General Theory of Pathwise Coordinate Optimization

Tuo Zhao, Han Liu, and Tong Zhang

Conditional Mean and Quantile Dependence Testing in High Dimension

Xianyang Zhang, Shun Yao, and Xiaofeng Shao

High-Dimensional Asymptotics of Prediction: Ridge Regression and Classification

Edgar Dobriban and Stefan Wager

Testing independence in high dimensions with sums of squares of rank correlations

Dennis Leung and Mathias Drton

High dimensional censored quantile regression

Qi Zheng, Limin Peng, and Xuming He

Local M-estimation with Discontinuous Criterion for Dependent and Limited Observations

Myung hwan Seo and Taisuke Otsu

Mixture Inner Product Spaces and Their Application to Functional Data Analysis

Zhenhua Lin, Hans-Georg Müller, and Fang Yao

Bayesian Estimation of Sparse Signals with a Continuous Spike-and-Slab Prior

Veronika Rockova

Strong orthogonal arrays of strength two plus

Yuanzhen He, Ching-Shui Cheng, and Boxin Tang
Statistical inference for spatial statistics defined in the Fourier domain Suhasini Subba Rao

On the asymptotic theory of new bootstrap confidence bounds

Charl Pretorius and Jan Willem Hendrik Swanepoel

On the inference about the spectral distribution of high-dimensional covariance matrix based on high-frequency noisy observations

Ningning Xia and Xinghua Zheng

Online Rules for Control of False Discovery Rate and False Discovery Exceedance

Adel Javanmard and Andrea Montanari

Frequency Domain Minimum Distance Inference for Possibly Noninvertible and Noncausal ARMA models

Carlos Velasco and Ignacio N. Lobato

On consistency and sparsity for sliced inverse regression in high dimensions

Qian Lin, Zhigen Zhao, and Jun S. Liu

Regularization and the small-ball method I: sparse recovery

Guillaume Lecue and Shahar Mendelson

Gaussian and bootstrap approximations for high-dimensional U-statistics and their applications

Xiaohui Chen

Selective inference with a randomized response

Xiaoying Tian and Jonathan Taylor

Multiscale Blind Source Separation

Merle Behr, Chris Holmes, and Axel Munk

Sharp oracle inequalities for Least Squares estimators in shape restricted regression

Pierre C. Bellec

Oracle Inequalities for Sparse Additive Quantile Regression in Reproducing Kernel Hilbert Space

Shaogao Lv, Huazhen Lin, Heng Lian, and Jian Huang

I-LAMM: Simultaneous Control of Algorithmic Complexity and Statistical Error

Jianqing Fan, Han Liu, Qiang Sun, and Tong Zhang

On Bayesian index policies for sequential resource allocation

Emilie Kaufmann

High-Dimensional A-Learning for Optimal Dynamic Treatment Regimes

Chengchun Shi, Ailin Fan, Rui Song, and Wenbin Lu

Testing independence with high-dimensional correlated samples

Xi Chen and Weidong Liu

Variable selection with Hamming loss

Cristina Butucea, Natalia A. Stepanova, and Alexandre B. Tsybakov

Test for High Dimensional Regression Coefficients Using Refitted Cross-Validation Variance Estimation

Hengjian Cui, Wenwen Guo, and Wei Zhong

Detecting Rare and Faint Signals via Thresholding Maximum Likelihood Estimators

Yumou Qiu, Song X Chen, and Dan Nettleton

Are Discoveries Spurious? Distributions of Maximum Spurious Correlations and Their Applications

Jianqing Fan, Qi-Man Shao, and Wenxin Zhou

Adaptive estimation of planar convex sets

Tony Cai, Adityanand Guntuboyina, and Yuting Wei

High-dimensional consistency of AIC and BIC for estimating the number of significant components in principal component analysis

Zhidong Bai, Yasunori Fujikoshi, and Kwok Pui Choi

On the systematic and idiosyncratic volatility with large panel high-frequency data

Xinbing Kong

Ball Divergence: Multivariate Imbalance Test

Wenliang Pan, Yuan Tian, Xueqin Wang, and Heping Zhang

Asymptotic distribution-free tests for semiparametric regressions with dependent data

Juan Carlos Escanciano, Juan Carlos Pardo Fernandez, and Ingrid Van Keilegom

A Smooth Block Bootstrap for Quantile Regression with Time Series

Karl B Gregory, Soumendra N Lahiri, and Dan J Nordman

Gradient-Based Structural Change Detection For Non-stationary Time Series M-estimation

Weichi Wu and Zhou Zhou

Moderate Deviations and Nonparametric Inference for Monotone Functions

Fuqing Gao, Jie Xiong, and Xingqiu Zhao

Uniform Asymptotic Inference and the Bootstrap After Model Selection

Ryan Joseph Tibshirani, Alessandro Rinaldo, Robert Tibshirani, and Larry Wasserman

Detection Thresholds for the β-Model on Sparse Graphs

Rajarshi Mukherjee, Sumit Mukherjee, and Subhabrata Sen

Minimax and adaptive estimation of the Wigner function in quantum homodyne tomography with noisy data

Karim Lounici, Katia Meziani, and Gabriel Peyre

Distributed Testing and Estimation under Sparse High Dimensional Models

Heather Battey, Jianqing Fan, Han Liu, Junwei Lu, and Ziwei Zhu

Large Covariance Estimation Through Ellipitical Factor Models

Jianqing Fan, Han Liu, and Weichen Wang

Current status linear regression

Piet Groeneboom and Kim Hendrickx

Functional Data Analysis by Matrix Completion

Marie-Hélène Descary and Victor Michael Panaretos

Jump filtering and efficient drift estimation for Lévy-driven SDE's

Arnaud Gloter, Hilmar Mai, and Dasha Loukianova

Consistency and convergence rate of phylogenetic inference via regularization

Vu Dinh, Lam Si Tung Ho, Marc Suchard, and Frederick Matsen

Pareto Quantiles of Unlabeled Tree Objects

Ela Sienkiewicz and Haonan Wang

Efficient and Adaptive Linear Regression in Semi-Supervised Settings

Abhishek Chakrabortty and Tianxi Cai

Convexified Modularity Maximization for Degree-corrected Stochastic Block Models

Yudong Chen, Xiaodong Li, and Jiaming Xu

Near-Optimality of Linear Recovery in Gaussian Observation Scheme under ||·|| 22-Loss

Anatoli B. Juditsky and Arkadi S. Nemirovski

An MCMC Approach to Empirical Bayes Inference and Bayesian Sensitivity Analysis via Empirical Processes

Hani John Doss and Yeonhee Park

Curvature and inference for maximum likelihood estimates

Bradley Efron

Empirical Bayes Estimates for a 2-Way Cross-Classified Additive Model

Lawrence D Brown, Gourab Mukherjee, and Asaf Weinstein
Estimating Variance of Random Effects to Solve to Multiple Problems Simultaneously Masayo Yoshimori Hirose and Partha Lahiri

Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model

David L Donoho, Matan Gavish, and Iain M Johnstone

Computation of Maximum Likelihood Estimates in Cyclic Structural Equation Models

Mathias Drton, Christopher Fox, and Y. Samuel Wang

A Bayesian Approach to the Selection of Two-Level Multi-Stratum Factorial Designs

Ming-Chung Chang and Ching-Shui Cheng

Accuracy Assessment for High-dimensional Linear Regression

Tony Cai and Zijian Guo

Randomization-based causal inference from split-plot designs

Anqi Zhao, Peng Ding, Rahul Mukerjee, and Tirthankar Dasgupta

A New Perspective on Robust M-Estimation: Finite Sample Theory and Applications to Dependence-Adjusted Multiple Testing

Wen-Xin Zhou, Koushiki Bose, Jianqing Fan, and Han Liu

Robust Covariance and Scatter Matrix Estimation under Huber's Contamination Model

Mengjie Chen, Chao Gao, and Zhao Ren

Empirical best prediction under a nested error model with log transformation

Isabel Molina and Nirian Martin

Backward Nested Descriptors Asymptotics with Inference on Stem Cell Differentiation

Stephan Huckemann and Benjamin Eltzner

Change-point detection in multinomial data with a large number of categories

Guanghui Wang, Changliang Zou, and Guosheng Yin

Local Asymptotic Normality Property for Fractional Gaussian Noise Under High-Frequency Observations

Masaaki Fukasawa and Alexandre Brouste

Global Testing Against Sparse Alternatives under Ising Models

Rajarshi Mukherjee, Sumit Mukherjee, and Ming Yuan

Principal Component Analysis for Second-order Stationary Vector Time Series

Jinyuan Chang, Bin Guo, and Qiwei Yao

Estimation of a monotone density in s-sample biased sampling models

Kwun Chuen Gary Chan, Hok Kan Ling, Tony Sit, and Sheung Chi Phillip Yam

Community Detection in Degree-Corrected Block Models

Chao Gao, Zongming Ma, Anderson Zhang, and Harrison Zhou

CLT for Largest Eigenvalues and Unit Root Testing for High-Dimensional Nonstationary Time Series

Guangming Pan, Bo Zhang, and Jiti Gao

Smooth Backfitting for Errors-in-Variables Additive Models

Kyunghee Han and Byeong U Park

Unifying Markov Properties for Graphical Models

Steffen Lilholt Lauritzen and Kayvan Sadeghi

Adaptation in log-concave density estimation

Arlene Kyoung Hee Kim, Adityanand Guntuboyina, and Richard John Samworth

Exact recovery in the Ising blockmodel

Quentin Berthet, Philippe Rigollet, and Piyush Srivastava

Weak convergence of a pseudo maximum likelihood estimator for the extremal index

Betina Berghaus and Axel Bücher

Semi-parametric efficiency bounds for high-dimensional models

Jana Jankova and Sara van de Geer

Limit theorems for eigenvectors of the normalized Laplacian for random graphs

Minh Tang and Carey Priebe

Fréchet regression for random objects with Euclidean Predictors

Alexander Petersen and Hans-Georg Müller

On the Optimality and Sub-optimality of PCA in Spiked Random Matrix Models

Amelia Perry, Alexander S. Wein, Afonso S. Bandeira, and Ankur Moitra

On the Exponentially Weighted Aggregate with the Laplace Prior

Arnak Dalalyan, Edwin Grappin, and Quentin Paris

Goodness-of-fit Testing of Error Distribution in Linear Measurement Error Models

Hira L. Koul, Weixing Song, and Xiaoqing Zhu

Finding a Large Submatrix of a Gaussian Random Matrix

David Gamarnik and Quan Li

Support Points

Simon Mak and V. Roshan Joseph

Debiasing the Lasso: Optimal Sample Size for Gaussian Designs

Adel Javanmard and Andrea Montanari

Margins of Discrete Bayesian Networks

Robin Evans

Multi-threshold Accelerated Failure Time Model

Jialiang Li and Baisuo Jin

Divide and Conquer in Non-Standard Problems and the Super-Efficiency Phenomenon

Moulinath Banerjee, Cecile Durot, and Bodhisattva Sen

Rank Verification for Exponential Families

Kenneth Hung and William Fithian

Measuring and testing for interval quantile independence

Liping Zhu, Yaowu Zhang, and Kai Xu

Barycentric Subspace Analysis on Manifolds

Xavier Pennec

The Landscape of Empirical Risk for Non-convex Losses

Song Mei, Yu Bai, and Andrea Montanari
 
   
 
 

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