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A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underl
Sparse Modeling
Sparse Estimation with Math and Python
Sparse Estimation with Math and R
High-Dimensional Statistics
Model Selection and Error Estimation in a Nutshell
Introduction to Statistical Data Science
Sparse Optimization Theory and Methods
High-Dimensional Covariance Estimation
Post-Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data
Introduction to Sparse Stochastic Processes
Introduction to Statistical Machine Learning
Deep Learning through Sparse and Low-Rank Modeling