Online Debiasing for Adaptively Collected High-dimensional Data with Applications to Time Series Analysis

A flexible framework for hypothesis testing in high dimensions

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Debiasing the lasso: Optimal sample size for Gaussian designs

(2018) Adel Javanmard et al.   ANNALS OF STATISTICS

Regularized estimation in sparse high-dimensional time series models

(2015) Sumanta Basu et al.   ANNALS OF STATISTICS

Granger Causality Analysis in Neuroscience and Neuroimaging

(2015) A. K. Seth et al.   JOURNAL OF NEUROSCIENCE

Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challenges

(2015) Sofía S. Villar et al.   STATISTICAL SCIENCE

On asymptotically optimal confidence regions and tests for high-dimensional models

(2014) Sara van de Geer et al.   ANNALS OF STATISTICS

Hypothesis Testing in High-Dimensional Regression Under the Gaussian Random Design Model: Asymptotic Theory

(2014) Adel Javanmard et al.   IEEE TRANSACTIONS ON INFORMATION THEORY

Confidence intervals for low dimensional parameters in high dimensional linear models

(2013) Cun-Hui Zhang et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Scaled sparse linear regression

(2012) T. Sun et al.   BIOMETRIKA

Square-root lasso: pivotal recovery of sparse signals via conic programming

(2011) A. Belloni et al.   BIOMETRIKA

The BATTLE Trial: Personalizing Therapy for Lung Cancer

(2011) Edward S. Kim et al.   Cancer Discovery

Bayesian adaptive design for targeted therapy development in lung cancer — a step toward personalized medicine

(2008) Xian Zhou et al.   Clinical Trials