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Optimization techniques are at the core of data science. An understanding of the basic techniques and their fundamental properties provides important grounding for students, researchers, and practitioners. This compact, self-contained text covers the fundamentals of optimization…
"Optimization formulations and algorithms have long played a central role in data analysis and machine learning. Maximum likelihood concepts date to Gauss and Laplace in the late 1700s ; problems of this type drove developments in unconstrained optimization in the latter half of…
Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. Thi…
"Optimization formulations and algorithms have long played a central role in data analysis and machine learning. Maximum likelihood concepts date to Gauss and Laplace in the late 1700s ; problems of this type drove developments in unconstrained optimization in the latter half of…
"Optimization formulations and algorithms have long played a central role in data analysis and machine learning. Maximum likelihood concepts date to Gauss and Laplace in the late 1700s ; problems of this type drove developments in unconstrained optimization in the latter half of…