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Computational Optimal Transport: With Applications to Data Science - Foundations and Trends® in Machine Learning
Gabriel Peyre
Computational Optimal Transport: With Applications to Data Science - Foundations and Trends® in Machine Learning
Gabriel Peyre
Presents an overview of the main theoretical insights that support the practical effectiveness of OT before explaining how to turn these insights into fast computational schemes. This book will be a valuable reference for researchers and students wishing to get a thorough understanding of computational optimal transport.
272 pages
Mídia | Livros Paperback Book (Livro de capa flexível e brochura) |
Lançado | 12 de fevereiro de 2019 |
ISBN13 | 9781680835502 |
Editoras | now publishers Inc |
Páginas | 272 |
Dimensões | 234 × 156 × 20 mm · 416 g |
Idioma | English |
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