Machine Learning, Optimization, and Data Science edited by Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos Pardalos, Giuseppe Di Fatta, Giovanni Giuffrida, Renato Umeton. [electronic resource] :
Material type: TextPublication details: Cham Springer Nature Switzerland 2023Edition: 1st ed. 2023Description: XXIV, 616 p. 203 illus., 180 illus. in color. online resourceISBN:- 9783031255991
- Artificial intelligence
- Artificial Intelligence
- Computer Application in Administrative Data Processing
- Computer Communication Networks
- Computer networksÂ
- Computer System Implementation
- Computer systems
- Data structures (Computer science)
- Data Structures and Information Theory
- Information technology
- Information theory
- Machine learning
- Machine Learning
- 5.3
Item type | Home library | Call number | Status | Notes | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|---|
e-Book | S. R. Ranganathan Learning Hub Online | Available | Platform:Springer | EB2055 |
This two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 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.
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