Offline reinforcement learning (offline RL), which aims to find an optimal policy from a
previously collected static dataset, bears algorithmic difficulties due to function …

This manuscript provides a detailed synopsis of the contemporary advancements in the
nascent area of real-time structural damage detection for vibrating systems. The paper …

Since the early 1980. the first author has taught a graduate course in numerical linear
algebra at MIT and Cornell. The alumni of this course, now numbering in the hundreds, have …

Excerpt More than 25 years have passed since the first edition of this book was published in
1996. Least squares and least-norm problems have become more significant with every …

This book presents a broad overview of numerical methods for students and professionals in
computationally oriented disciplines who need to solve mathematical problems. It differs …

Praise for the First Edition"... outstandingly appealing with regard to its style, contents,
considerations of requirements of practice, choice of examples, and exercises."—Zentralblatt …

This work is aimed at mathematics and engineering graduate students and researchers in
the areas of optimization, dynamical systems, control sys tems, signal processing, and linear …

I am delighted that SIAM Publications in Philadelphia has undertaken the republication of
my book in their prestigious Classics in Applied Mathematics series. The book appeared first …

No applied mathematician can be properly trained without some basic un derstanding
ofnumerical methods, Le., numerical analysis. And no scientist and engineer should be …

Differential evolution has been shown to be an effective methodology for solving
optimization problems over continuous space. In this paper, we propose an eigenvector …