Martin Wainwright Books
Martin Wainwright is a professor at the University of California, Berkeley, specializing in statistics, electrical engineering, and computer science.
Known for: Statistical Learning with Sparsity: The Lasso and Generalizations
Books by Martin Wainwright
Statistical Learning with Sparsity: The Lasso and Generalizations
This book provides a comprehensive treatment of sparse statistical modeling, focusing on the Lasso and its extensions. It covers theoretical foundations, computational algorithms, and practical applications in high-dimensional data analysis. The authors present a unified framework for understanding sparsity-inducing methods and their role in modern machine learning and statistics.
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The Birth of Sparsity: Historical Roots and Conceptual Foundation of the Lasso
The story of the Lasso begins with the challenge of high-dimensional statistics. Classical linear regression worked beautifully when the number of observations far exceeded the number of variables, but as scientists began to collect richer data, we soon found ourselves in situations where predictors...
From Statistical Learning with Sparsity: The Lasso and Generalizations
Mathematical Formulation and Geometry of the Lasso
Let us step inside the mathematics. The classical Lasso problem can be formulated as a constrained optimization: minimize the residual sum of squares subject to an upper bound on the L1 norm of the coefficients. Equivalently, one may view it as a penalized optimization, adding the L1 norm times a re...
From Statistical Learning with Sparsity: The Lasso and Generalizations
About Martin Wainwright
Martin Wainwright is a professor at the University of California, Berkeley, specializing in statistics, electrical engineering, and computer science.
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Martin Wainwright is a professor at the University of California, Berkeley, specializing in statistics, electrical engineering, and computer science.
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