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Books > Computing & IT > General theory of computing > Data structures
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Lectures on Convex Optimization (Hardcover, 2nd ed. 2018)
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Lectures on Convex Optimization (Hardcover, 2nd ed. 2018)
Series: Springer Optimization and Its Applications, 137
Expected to ship within 10 - 15 working days
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This book provides a comprehensive, modern introduction to convex
optimization, a field that is becoming increasingly important in
applied mathematics, economics and finance, engineering, and
computer science, notably in data science and machine learning.
Written by a leading expert in the field, this book includes recent
advances in the algorithmic theory of convex optimization,
naturally complementing the existing literature. It contains a
unified and rigorous presentation of the acceleration techniques
for minimization schemes of first- and second-order. It provides
readers with a full treatment of the smoothing technique, which has
tremendously extended the abilities of gradient-type methods.
Several powerful approaches in structural optimization, including
optimization in relative scale and polynomial-time interior-point
methods, are also discussed in detail. Researchers in theoretical
optimization as well as professionals working on optimization
problems will find this book very useful. It presents many
successful examples of how to develop very fast specialized
minimization algorithms. Based on the author's lectures, it can
naturally serve as the basis for introductory and advanced courses
in convex optimization for students in engineering, economics,
computer science and mathematics.
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