Understand Mathematics, Understand Computing. Discrete Mathematics That All Computing Students Should Know.. Cet article n’est pas disponible.
Langue : anglais
Edité par Cham, Springer International Publishing., 2020
- Éd. originale
- Livre relié
- Occasion

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1st ed. 2020. 1 Online-Ressource (XXVII, 550 p. 151 illus., 2 illus. in color). Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped.
N° de réf. du vendeur 36404AB
- Titre
- Understand Mathematics, Understand Computing. Discrete Mathematics That All Computing Students Should Know.
- Auteur
- Rosenberg, Arnold L.
- Éditeur
- Cham, Springer International Publishing.
- Année de publication
- 2020
- Reliure
- Couverture rigide
- Langue
- anglais
- ISBN à 10 chiffres
- 3030583759
- ISBN à 13 chiffres
- 9783030583750
- Édition
- Edition originale
- Catalogues du vendeur
- Mathematik
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À propos de l’auteur
Prof. Arnold Rosenberg is a distinguished university professor emeritus at the University of Massachusetts, Amherst. He also held research positions at Northeastern University and Colorado State University, a professorship at Duke University, and a staff research position at IBM Watson Research Center. He was elected a fellow of the ACM in 1996 for his work on graph-theoretic models of compuation, emphasizing theoretical studies of parallel algorithms and architectures, VLSI design and layout, and data structures. In 1997, he was elected as a fellow of the IEEE for fundamental contributions to theoretical aspects of computer science and engineering.
Prof. Denis Trystram is a distinguished professor at the Grenoble Institute of Engineering, an honorary member of the Institut Universitaire de France (IUF), and he works at the Laboratoire d'Informatique de Grenoble (LIG) in the team-project DataMove-INRIA. His research interestst include the design and analysis of efficient algorithms for optimizing resource use in parallel and distributed systems, approximation algorithms for scheduling and packing problems, and algorithms for data analytics. Both authors have considerable teaching and practical experience in the application of discrete mathematics approaches to computing tasks.
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