Optimization, Discrete Mathematics and Applications to Data Sciences
This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address comp...
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| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Ausgabe: | 1st ed. 2025. |
| Schriftenreihe: | Springer Optimization and Its Applications,
220 |
| Schlagworte: | |
| Online-Zugang: | https://doi.org/10.1007/978-3-031-78369-2 |
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Inhaltsangabe:
- On the morphism 1 → 121, 2 → 12221
- Polynomials and combinatorial identities
- Rainbow Greedy Matching Algorithms
- Predictive models of Non-Performing Loans: the case of Greece
- The Cost of Detection in Interaction Testing
- On the study of cycle chains representing non-reversible Markov chains associated with random walks with jumps in fixed environments
- Applying Distance Measures for Discrete Data
- Demand aggregation and mid-term energy planning problem on the business layer
- Factor Fitting, Rank Allocation, and Partitioning in Multilevel Low Rank Matrices
- A Code-based Watermarking Scheme for the Protection of Authenticity of Medical Images
- The minimum cost energy flow problem under demand uncertainty Effect on optimal solution, variability, worst and best case scenarios
- A mathematical study of the Braess’s Paradox within a network comprising four nodes, five edges, and linear time functions
- On similiarities between two global optimization algorithms based on different (Bayesian and Lipschitzian) approaches.