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Mathematical Modeling for Data Science: N2ADS, Athens, Greece, April, 78, 2025 and M2A25, Marrakech, Morocco, February, 1820, 2025 [Kõva köide]

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  • Formaat: Hardback, 354 pages, kõrgus x laius: 235x155 mm, 65 Illustrations, color; 26 Illustrations, black and white
  • Sari: Springer Proceedings in Mathematics & Statistics
  • Ilmumisaeg: 20-Jun-2026
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3032205042
  • ISBN-13: 9783032205049
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  • Formaat: Hardback, 354 pages, kõrgus x laius: 235x155 mm, 65 Illustrations, color; 26 Illustrations, black and white
  • Sari: Springer Proceedings in Mathematics & Statistics
  • Ilmumisaeg: 20-Jun-2026
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3032205042
  • ISBN-13: 9783032205049
This book presents selected chapters presented in two international conferences where more than 20 countries are represented by more than 100 participants, consisting of academic researchers and scientists working in industry. The conferences cover different areas related to the application of numerical analysis to practical problems in engineering, industry, environment, medical imaging, and new image and information technologies. Participants shared their recent contributions and their experience in different fields. The plenary speakers are very well known and most of them are editors or editors in chief of prestigious international journals (L. Reichel, Y. Saad, D. Szyld, H. Sadok, S. Serra-Capizzano.)



Description of the volumeThe subject of the book is to present selected papers, using two referees for each paper, that were presented during the two conference m2a25 held in Marrakech on February 2025 and n2ads held in Athens on April 2025. The accepted papers were in the topics of the conferences with special applications to data science.



The topics of interested were



Completion Methods and Applications to Data Science.



Inverse-Ill-posed Problems, Optimization.



Applied Statistics, Applications to Engineering, Biodiversity, Imaging, Big Data, Machine Learning,



This book offers numerous benefits to future readers, particularly those interested in data driven. Readers gain a deep understanding of the mathematical principles that under data science techniques. This foundation help them not only use algorithms effectively but also understand why and how these algorithms work.
Spectral theory of matrix-sequences: perspectives of the GLT analysis
and beyond.- Proximal regularisation methods for linear equations in variable
exponent Lebesgue spaces.- WGANMF-DO: matrix factorization with WGAN-GP and
dual objective optimization for accuracy and diversity inrRecommender
systems.- Extended block Hessenberg process for the evaluation of matrix
functions.- Time Series forecasting of Cyprus tourism arrivals using
statistical and machine learning methods.- Multidimensional extrapolated
global proximal gradient and applications in image processing.- Machine
learning approaches for early diagnosis of type 2 Diabetes.- Sign-Matrix
Determinants: Remarks and Results.- Towards the investigation of threshold
ramp secret sharing schemes through factorization of real polynomials.- An
inverse two-dimensional electromagnetic scattering problem in chiral media
for the reconstruction of a perfectly conducting body.- Parallel Schwarz
alternating methods implemented on cloud architecture for solving the coupled
problem of electrophoresis.- A bilevel piecewise linear quadratic
optimization problem.- Computationally cheap estimates for quadratic and
bilinear forms involving matrix inverse.- A numerical solution of an
electromagnetic scattering problem for a penetrable chiral body in
two-dimensions.- Tensor Krylov subspace methods via the T-product for large
Sylvester tensor equations.- Block triangular preconditioning for inverse
source problems in time-space fractional diusion equations.