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Description
The terms 'machine learning', 'pure mathematics and theoretical physics' may first appear to be topics in two very different categories in mathematics and computer science, yet in the past five years, we have seen many articles published that combined machine learning techniques in the search for patterns using big data. The aim of this book, a first of its kind, is to collect research and survey articles from many experts in this emerging collaboration between theoretical mathematicians and computer scientists on topics ranging from combinatorics to number theory, to geometry, to quantum field theory and string theory.This book is put together with PhD students in mind as well as seasoned researchers, as a reference book for collection of publications that cross between mathematics and computer science.
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The terms 'machine learning', 'pure mathematics and theoretical physics' may first appear to be topics in two very different categories in mathematics and computer science, yet in the past five years, we have seen many articles published that combined machine learning techniques in the search for patterns using big data. The aim of this book, a first of its kind, is to collect research and survey articles from many experts in this emerging collaboration between theoretical mathematicians and computer scientists on topics ranging from combinatorics to number theory, to geometry, to quantum field theory and string theory.This book is put together with PhD students in mind as well as seasoned researchers, as a reference book for collection of publications that cross between mathematics and computer science.
Reviews