This textbook offers an accessible introduction to the theory and numerics of approximation methods, combining classical topics of approximation with recent adv

This book is intended to be used as a textbook for graduate students studying theoretical computer science. It can also be used as a reference book for research

Covering the basic techniques used in the latest research work, the author consolidates progress made so far, including some very recent and promising results,

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying thei

This is a textbook on classical polynomial and rational approximation theory for the twenty-first century. Aimed at advanced undergraduates and graduate student