1 option
Machine Learning, Optimization, and Big Data : Second International Workshop, MOD 2016, Volterra, Italy, August 26-29, 2016, Revised Selected Papers / edited by Panos M. Pardalos, Piero Conca, Giovanni Giuffrida, Giuseppe Nicosia.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 10122
- Information Systems and Applications, incl. Internet/Web, and HCI ; 10122
- Language:
- English
- Subjects (All):
- Application software.
- Algorithms.
- Electronic digital computers-Evaluation.
- Artificial intelligence.
- Pattern recognition systems.
- Data mining.
- Computer and Information Systems Applications.
- System Performance and Evaluation.
- Artificial Intelligence.
- Automated Pattern Recognition.
- Data Mining and Knowledge Discovery.
- Local Subjects:
- Computer and Information Systems Applications.
- Algorithms.
- System Performance and Evaluation.
- Artificial Intelligence.
- Automated Pattern Recognition.
- Data Mining and Knowledge Discovery.
- Physical Description:
- 1 online resource (XVIII, 456 pages) : 109 illustrations
- Edition:
- 1st ed. 2016.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2016.
- System Details:
- text file PDF
- Summary:
- This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016. The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions. These proceedings contain papers in the fields of Machine Learning, Computational Optimization and DataScience presenting a substantial array of ideas, technologies, algorithms, methods and applications.
- Contents:
- Machine Learning
- Feature Selection
- Neural Networks
- Optimization
- Deep Learning
- Data Sciences
- Data Analytics
- Artificial Intelligence.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-319-51469-7
- 9783319514697
- Access Restriction:
- Restricted for use by site license.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.