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Applied Modeling Techniques and Data Analysis 1 Computational Data Analysis Methods and Tools.
This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working o...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Newark :
John Wiley & Sons, Incorporated,
2021.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 001 | EBOOKCENTRAL_on1247656654 | ||
| 003 | OCoLC | ||
| 005 | 20240329122006.0 | ||
| 006 | m o d | ||
| 007 | cr ||||||||||| | ||
| 008 | 210424s2021 xx o ||| 0 eng d | ||
| 040 | |a EBLCP |b eng |c EBLCP |d EBLCP |d LIV |d OCLCQ |d REDDC |d OCLCO |d OCLCL |d ESU | ||
| 066 | |c (S | ||
| 020 | |a 9781119821564 | ||
| 020 | |a 1119821568 | ||
| 035 | |a (OCoLC)1247656654 | ||
| 050 | 1 | 4 | |a QA276-280 |b .D56 2021 |
| 082 | 0 | 4 | |a 519.5 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Dimotikalis, Yannis. | |
| 245 | 1 | 0 | |a Applied Modeling Techniques and Data Analysis 1 |h [electronic resource] : |b Computational Data Analysis Methods and Tools. |
| 260 | |a Newark : |b John Wiley & Sons, Incorporated, |c 2021. | ||
| 300 | |a 1 online resource (297 p.) | ||
| 500 | |a Description based upon print version of record. | ||
| 505 | 0 | |a Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Preface -- PART 1: Computational Data Analysis -- 1 A Variant of Updating PageRank in Evolving Tree Graphs -- 1.1. Introduction -- 1.2. Notations and definitions -- 1.3. Updating the transition matrix -- 1.4. Updating the PageRank of a tree graph -- 1.4.1. Updating the PageRank of tree graph when a batch of edges changes -- 1.4.2. An example of updating the PageRank of a tree -- 1.5. Maintaining the levels of vertices in a changing tree graph -- 1.6. Conclusion -- 1.7. Acknowledgments -- 1.8. References | |
| 505 | 8 | |a 2 Nonlinearly Perturbed Markov Chains and Information Networks -- 2.1. Introduction -- 2.2. Stationary distributions for Markov chains with damping component -- 2.2.1. Stationary distributions for Markov chains with damping component -- 2.2.2. The stationary distribution of the Markov chain X0,n -- 2.3. A perturbation analysis for stationary distributions of Markov chains with damping component -- 2.3.1. Continuity property for stationary probabilities -- 2.3.2. Rate of convergence for stationary distributions -- 2.3.3. Asymptotic expansions for stationary distributions | |
| 505 | 8 | |a 2.3.4. Results of numerical experiments -- 2.4. Coupling and ergodic theorems for perturbed Markov chains with damping component -- 2.4.1. Coupling for regularly perturbed Markov chains with damping component -- 2.4.2. Coupling for singularly perturbed Markov chains with damping component -- 2.4.3. Ergodic theorems for perturbed Markov chains with damping component in the triangular array mode -- 2.4.4. Numerical examples -- 2.5. Acknowledgments -- 2.6. References -- 3 PageRank and Perturbed Markov Chains -- 3.1. Introduction -- 3.2. PageRank of the first-order perturbed Markov chain | |
| 505 | 8 | |a 3.3. PageRank of the second-order perturbed Markov chain -- 3.4. Rates of convergence of PageRanks of first- and second-order perturbed Markov chains -- 3.5. Conclusion -- 3.6. Acknowledgments -- 3.7. References -- 4 Doubly Robust Data-driven Distributionally Robust Optimization -- 4.1. Introduction -- 4.2. DD-DRO, optimal transport and supervised machine learning -- 4.2.1. Optimal transport distances and discrepancies -- 4.3. Data-driven selection of optimal transport cost function -- 4.3.1. Data-driven cost functions via metric learning procedures -- 4.4. Robust optimization for metric learning | |
| 500 | |a 5.2.5. PageRank centrality. | ||
| 520 | |a This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. -- |c Edited summary from book. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Quantitative research |x Data processing. | |
| 650 | 6 | |a Recherche quantitative |x Informatique. | |
| 700 | 1 | |a Karagrigoriou, Alex. | |
| 700 | 1 | |a Parpoula, Christina. | |
| 700 | 1 | |a Skiadas, Christos H. | |
| 758 | |i has work: |a Applied Modeling Techniques and Data Analysis 1 (Text) |1 https://id.oclc.org/worldcat/entity/E39PCXy3fPJr4GgYKTFP6vV9WC |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Dimotikalis, Yannis |t Applied Modeling Techniques and Data Analysis 1 |d Newark : John Wiley & Sons, Incorporated,c2021 |z 9781786306739 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=6532360 |z Texto completo |
| 880 | 8 | |6 505-00 |a 4.4.1. Robust optimization for relative metric learning -- 4.4.2. Robust optimization for absolute metric learning -- 4.5. Numerical experiments -- 4.6. Discussion and conclusion -- 4.7. References -- 5 A Comparison of Graph Centrality Measures Based on Lazy Random Walks -- 5.1. Introduction -- 5.1.1. Notations and abbreviations -- 5.1.2. Linear systems and the Neumann series -- 5.2. Review on some centrality measures -- 5.2.1. Degree centrality -- 5.2.2. Katz status and β-centralities -- 5.2.3. Eigenvector and cumulative nomination centralities -- 5.2.4. Alpha centrality | |
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL6532360 | ||
| 994 | |a 92 |b IZTAP | ||