Topic: Scientific

A ground-breaking study on how natural disasters can escalate or defuse wars, insurgencies, and other strife. Armed conflict and natural disasters have plagued the twenty-first century. Not since the end...

What global shifts in markets and power mean for the politics and governance of sustainability. In recent years, major shifts in global markets from North to South have created a...

Essays on evolvability from the perspectives of quantitative and population genetics, evolutionary developmental biology, systems biology, macroevolution, and the philosophy of science. Evolvability—the capability of organisms to evolve—wasn't recognized as...

An innovative, wide-ranging consideration of the global ecological crisis and its deep philosophical and theological roots. Global crises, from melting Arctic ice to ecosystem collapse and the sixth mass extinction,...

The main topic of the book is closed-loop design and the computation of performance limits using convexity. The book introduces a standard framework for the control design problem and describes...

In this book the authors reduce a wide variety of problems arising in system and control theory to a handful of convex and quasiconvex optimization problems that involve linear matrix...

Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency....

This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative approach to teaching linear algebra. Requiring no prior knowledge of the subject, it covers...

Understanding Linear Algebra is a freely available linear algebra textbook suitable for use in a first undergraduate linear algebra course. The text aims to support readers as they develop their ability...

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to...

This leading textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers...

This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the...