Name: Big Data Analysis. High Dimensional Probability, Statistics, Optimization, and Inference
Price: 3414.00 TWD
Availability: InStock
Author: Junwei Lu
ISBN: 9783032031600

portada Big Data Analysis. High Dimensional Probability, Statistics, Optimization, and Inference

Big Data Analysis. High Dimensional Probability, Statistics, Optimization, and Inference

Type

Physical Book

Publisher

Springer Nature Switzerland AG

Author

Junwei Lu

Year

2025

Pages

170

Format

Hardcover

Dimensions

23.50 x 15.50 cm

ISBN13

9783032031600

Big Data Analysis. High Dimensional Probability, Statistics, Optimization, and Inference

Junwei Lu (Author) · Springer Nature Switzerland AG · Hardcover

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Synopsis "Big Data Analysis. High Dimensional Probability, Statistics, Optimization, and Inference"

This book covers the methods and theory of high dimensional probability, statistics, large-scale optimization, and inference. We aim to quickly bring readers to the frontier and interdisciplinary areas of statistics, optimization, probability, and machine learning. This book covers topics in:High dimensional probability, Concentration inequality, Sub-Gaussian random variables, Chernoff bounds, Hoeffding's inequality, Maximal inequalities, High dimensional linear regression, Ordinary least square, Compressed sensing, Lasso, Variations of Lasso including group lasso, fused lasso, adaptive lasso, etc., General high dimensional M- estimators, Variable selection consistency, High dimensional Optimization, Convex geometry, Lagrange duality, Gradient descent, Proximal gradient descent, LARS, ADMM, Mirror descent, Stochastic optimization, Large-Scale Inference, Linear model hypothesis testing, high dimensional inference, Chi-square test, maximal test, and Higher criticism, False discovery rate control.