A Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge and observation, by providing mechanistic interpretation of the dynamic functioning of the brain circuit, and by suggesting optimal ways of deciphering...

This book is written by award-winning author, Frank Morgan. It offers a simple and sophisticated point of view, reflecting Morgan's insightful teaching, lecturing, and writing style. Intended for undergraduates studying real analysis, this book builds the theory behind calculus directly from the basic concepts of real numbers, limits, and...

This graduate-level textbook introduces fundamental concepts and methods in machine learning. It describes several important modern algorithms, provides the theoretical underpinnings of these algorithms, and illustrates key aspects for their application. The authors aim to present novel theoretical tools and concepts while giving concise...

All day, every day, Americans seek information. We research major purchases. We check news and sports. We visit government Web sites for public information and turn to friends for advice about our everyday lives. Although the Internet influences our information-seeking behavior, we gather information from many sources: family and friends,...

Software development would seem to be a quintessential example of today's Internet-enabled "knowledge work"--a global profession not bound by the constraints of geography. In Coding Places, Yuri Takhteyev looks at the work of software developers who inhabit two contexts: a geographical area--in this case, greater Rio de...