Data Science and Optimization



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Éditeur :

Springer


Paru le : 2026-02-17



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Description

Data science and optimization are increasingly intertwined as both focus on developing computational and methodological approaches to tackling large and otherwise complex datasets. Optimization is primarily concerned with accuracy, computational efficiency, and robustness while data science emphasizes achieving effective results on real datasets. Although some data science approaches involve the implicit optimization of objective functions, there remains a dearth of work that brings advanced optimization techniques to bear on data science problems. The goal of the Fields Focus Program on Data Science and Optimization held in November 2019 at the Fields Institute in Toronto, was to bring together researchers in data science and optimization, both theoretical and applied, in an effort to bridge the fields and stimulate cross-disciplinary interaction and collaboration.
In the spirit of the program, this volume compiles recent development and connections in the fields of data science and optimization, and the ways in which they overlap. It features novel results and state-of-the-art surveys as well as open problems.
Pages
342 pages
Collection
n.c
Parution
2026-02-17
Marque
Springer
EAN papier
9783032038432
EAN PDF
9783032038449

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
34
Taille du fichier
11735 Ko
Prix
210,99 €
EAN EPUB
9783032038449

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
34
Taille du fichier
30679 Ko
Prix
210,99 €

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