Machine Learning, Optimization, and Big Data
Third International Conference, MOD 2017, Volterra, Italy, September 14–17, 2017, Revised Selected Papers
Seiten
2017
Springer International Publishing (Verlag)
978-3-319-72925-1 (ISBN)
Springer International Publishing (Verlag)
978-3-319-72925-1 (ISBN)
This book constitutes the post-conference proceedings of the Third International Workshop on Machine Learning, Optimization, and Big Data, MOD 2017, held in Volterra, Italy, in September 2017.
The 50 full papers presented were carefully reviewed and selected from 126 submissions. The papers cover topics in the field of machine learning, artificial intelligence, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.
The 50 full papers presented were carefully reviewed and selected from 126 submissions. The papers cover topics in the field of machine learning, artificial intelligence, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.
| Erscheinungsdatum | 22.12.2017 |
|---|---|
| Reihe/Serie | Information Systems and Applications, incl. Internet/Web, and HCI | Lecture Notes in Computer Science |
| Zusatzinfo | XXI, 600 p. 258 illus., 121 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 931 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Schlagworte | Applications • Artificial Intelligence • classification • cluster analysis • Computer Architecture • Computer Science • conference proceedings • Data Mining • Differential evolution • evolutionary algorithms • Genetic algorithms • graph theory • Heuristic Methods • Informatics • Learning Algorithms • Linear Programming • machine learning • Multiobjective Optimization • Neural networks • Problem Solving • Research • Semantics • Simulated annealing • Support Vector Machines (SVM) • wireless telecommunication systems |
| ISBN-10 | 3-319-72925-X / 331972925X |
| ISBN-13 | 978-3-319-72925-1 / 9783319729251 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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