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Author:   Junwei Lu
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
ISBN:  

9783032031600

ISBN 10:   3032031605
Pages:   170
Publication Date:   07 November 2025
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Not yet available  
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Table of Contents

Part I Foundations of Big Data Analysis.- Chapter 1 Introduction.- Chapter 2 Preliminaries in Probability.- Chapter 3 Preliminaries in Linear Algebra.- Part II High-Dimensional Probability.- Chapter 4 Concentration Inequalities.- Chapter 5 Sub-Exponential Random Variables.- Chapter 6 Maximal Inequality.- Part III High-Dimensional Statistics.- Chapter 7 Ordinary Least Squares.- Chapter 8 Compressive Sensing.- Chapter 9 Restricted Isometry Property.- Chapter 10 Statistical Properties of Lasso.- Chapter 11 Variations of Lasso.- Part IV High-Dimensional Optimization.- Chapter 12 Convexity and Subgradient.- Chapter 13 Gradient Descent.- Chapter 14 Proximal Gradient Descent.- Chapter 15 Mirror Descent and Nesterov’s Smoothing.- Chapter 16 Duality and ADMM.- Part V High-Dimensional Inference.- Chapter 17 High Dimensional Inference.- Chapter 18 Debiased Lasso.- Chapter 19 Multiple Hypotheses.- Chapter 20 False Discovery Rate.- Chapter 21 Knock-Off.- References.

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Author Information

Junwei Lu is an Assistant Professor in Harvard T.H. Chan School of Public Health. His research focuses on the intersection of statistical machine learning and clinical studies, revealing scientific associations among clinical treatment strategies and patient phenotyping, especially focusing on precision medicine leveraging real-world clinical data such as electronic health records data for risk prediction and clinical optimization.

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