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New edition of a graduate-level textbook on that focuses on online convex optimization, a machine learning framework that views optimization as a process.
In many practical applications, the environment is so complex that it is not feasible to lay out a comprehensive theoretical model and use classical algorithmic theory and/or mathematical optimization. Introduction to Online Convex Optimization presents a robust machine learning approach that contains elements of mathematical optimization, game theory, and learning theory: an optimization method that learns from experience as more aspects of the problem are observed. This view of optimization as a process has led to some spectacular successes in modeling and systems that have become part of our daily lives.
Based on the “Theoretical Machine Learning” course taught by the author at Princeton University, the second edition of this widely used graduate level text features:
The price of "Introduction To Online Convex Optimization, Second Edition (Hardcover Book)" at Downtown Comics in Castleton is USD $60.00.
The publisher of "Introduction To Online Convex Optimization, Second Edition (Hardcover Book)" is MIT Press.
The genres of "Introduction To Online Convex Optimization, Second Edition (Hardcover Book)" are Computers - Data Science - Machine Learning, Mathematics - Game Theory, and Mathematics - Optimization.
"Introduction To Online Convex Optimization, Second Edition (Hardcover Book)" falls under the category of Hardcover Books.
The writer of "Introduction To Online Convex Optimization, Second Edition (Hardcover Book)" is Elad Hazan.
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