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Machine Learning, Optimization, and Data Science : 7th International Conference, LOD 2021, Grasmere, UK, October 4–8, 2021, Revised Selected Papers, Part II / edited by Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Giorgio Jansen, Panos M. Pardalos, Giovanni Giuffrida, Renato Umeton.
SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online
View online- Format:
- Book
- Series:
- Information Systems and Applications, incl. Internet/Web, and HCI, 2946-1642 ; 13164
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Algorithms.
- Application software.
- Numerical analysis.
- Computer networks.
- Social sciences--Data processing.
- Social sciences.
- Artificial Intelligence.
- Design and Analysis of Algorithms.
- Computer and Information Systems Applications.
- Numerical Analysis.
- Computer Communication Networks.
- Computer Application in Social and Behavioral Sciences.
- Local Subjects:
- Artificial Intelligence.
- Design and Analysis of Algorithms.
- Computer and Information Systems Applications.
- Numerical Analysis.
- Computer Communication Networks.
- Computer Application in Social and Behavioral Sciences.
- Physical Description:
- 1 online resource (571 pages)
- Edition:
- 1st ed. 2022.
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2022.
- Summary:
- This two-volume set, LNCS 13163-13164, constitutes the refereed proceedings of the 7th International Conference on Machine Learning, Optimization, and Data Science, LOD 2021, together with the first edition of the Symposium on Artificial Intelligence and Neuroscience, ACAIN 2021. The total of 86 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 215 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
- Contents:
- Deep Learning
- Machine Learning
- Reinforcement Learning
- Neural Networks
- Deep Reinforcement Learning
- Optimization
- Global Optimization
- Multi-Objective Optimization
- Computational Optimization
- Data Science
- Big Data
- Data Analytics
- Artificial Intelligence.
- Notes:
- Includes bibliographical references and index.
- Other Format:
- Print version: Nicosia, Giuseppe Machine Learning, Optimization, and Data Science
- ISBN:
- 3-030-95470-6
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