The goal of learning theory is to approximate a function from sample values. To attain this goal learning theory draws on a variety of diverse subjects, specifically statistics, approximation theory, and algorithmics. Ideas from all these areas blended to form a subject whose many successful applications have triggered a rapid growth during the last two decades. This is the first book to give a general overview of the theoretical foundations of the subject emphasizing the approximation theory, while still giving a balanced overview. It is based on courses taught by the authors, and is reasonably self-contained so will appeal to a broad spectrum of researchers in learning theory and adjacent fields. It will also serve as an introduction for graduate students and others entering the field, who wish to see how the problems raised in learning theory relate to other disciplines.
In order to be a successful teacher you will need a clear understanding of the different ways in which children learn. Closely examining the learning process, and demonstrating how different theories...
These two volumes consist of chapters written by students and colleagues of W.K. Estes. The books' contributors -- themselves eminent figures in the field -- reflect on Estes' sweeping contributions...