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20240909213021.0 |
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210424s2021 xx o ||| 0 eng d |
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|a EBLCP
|b eng
|c EBLCP
|d EBLCP
|d LIV
|d OCLCQ
|d REDDC
|d OCLCO
|d OCLCL
|d ESU
|d U3W
|d K6U
|d OCLCQ
|d UEJ
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|c (S
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|a 9781119821564
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|a 1119821568
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|a (OCoLC)1247656654
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|a QA276-280
|b .D56 2021
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| 049 |
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|a HCDD
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| 100 |
1 |
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|a Dimotikalis, Yannis.
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| 245 |
1 |
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|a Applied Modeling Techniques and Data Analysis 1
|h [electronic resource] :
|b Computational Data Analysis Methods and Tools.
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| 260 |
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|a Newark :
|b John Wiley & Sons, Incorporated,
|c 2021.
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| 300 |
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|a 1 online resource (297 p.)
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| 500 |
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|a Description based upon print version of record.
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|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
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|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
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|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
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| 505 |
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|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
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| 500 |
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|a 5.2.5. PageRank centrality.
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| 520 |
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|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.
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| 650 |
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|a Quantitative research
|x Data processing.
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| 700 |
1 |
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|a Karagrigoriou, Alex.
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| 700 |
1 |
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|a Parpoula, Christina.
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| 700 |
1 |
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|a Skiadas, Christos H.
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| 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
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| 856 |
4 |
0 |
|u https://ebookcentral.proquest.com/lib/holycrosscollege-ebooks/detail.action?docID=6532360
|y Click for online access
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| 880 |
8 |
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|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
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| 903 |
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|a EBC-AC
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| 994 |
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|a 92
|b HCD
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