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.
General
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