Optimization for Machine Learning

Industrial Strength Empirical Modeling clearly explains the main principles of the different machine learning approaches and offers a methodology of how to integrate these techniques for successful r

This book introduces a novel paradigm for machine learning and data mining called predictive clustering, which covers a broad variety of learning tasks and offers a fresh perspective on existing techn

That Monday afternoon, in high-school gyms across America, kids were battling for the only glory American culture seems to want to dispense to the young these days: sports glory.? But at Dos Pueblos High School in Goleta, California, in a gear-cluttered classroom, a different type of “cool” was brewing.? A physics teacher with a dream – the first public high-school teacher ever to win a MacArthur Genius Award -- had rounded up a band of high-I.Q. students who wanted to put their technical know-how to work.? If you asked these brainiacs what the stakes were that first week of their project, they’d have told you it was all about winning a robotics competition – building the ultimate robot and prevailing in a machine-to-machine contest in front of 25,000 screaming fans at Atlanta’s Georgia Dome.?But for their mentor, Amir Abo-Shaeer, much more hung in the balance. ?The fact was, Amir had in mind a different vision for education, one based not on rote learning -- on absorbing facts and fig

Data mining, or knowledge discovery, has become an indispensable technology for businesses and researchers in many fields. Drawing on work in such areas as statistics, machine learning, pattern recog

A concise, rigorous, yet accessible, account of the fundamentals of constrained optimization theory. Many problems arising in diverse fields such as machine learning, medicine, chemical engineering, s

The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish betw

The Support Vector Machine is a powerful new learning algorithm for solving a variety of learning and function estimation problems, such as pattern recognition, regression estimation, and operator inv