Optimization and Learning via Stochastic Gradient Search (Princeton Series in Applied Mathematics)
by Professor Felisa Vázquez-Abad, Bernd Heidergott
A rigorous examination of stochastic gradient methods for optimization and learning in applied mathematics.
About This Book
This book explores stochastic gradient search techniques within the framework of applied mathematics.
It presents theoretical foundations and practical considerations for optimization problems.
Readers will find discussions on convergence properties and algorithmic implementations.
The text is part of the Princeton Series in Applied Mathematics.
Reviews
No reviews yet. Be the first to review this book!