Journal of Applied & Computational Mathematics

Department of Applied Mathematics, University of Sydney, Sydney, Australia

Publications

• Opinion   
  Adaptive Algorithms for High-dimensional Data Integration: A Computational Approach
  Author(s): Martin Gali*
  
  Integrating high-dimensional data is a crucial challenge in modern computational science. As we generate and collect vast amounts of data from diverse sources, the complexity of this task increases exponentially. High-dimensional data sets are characterized by a large number of variables, which often surpass the number of observations. This disparity creates difficulties in data analysis, as traditional statistical methods tend to falter under such conditions. To address these challenges, adaptive algorithms have emerged as powerful tools, offering a computational approach to effectively integrate and analyze high-dimensional data. Adaptive algorithms are designed to adjust their parameters and structures based on the characteristics of the data they process. This flexibility makes them particularly well-suited for handling high-dimensional data, where the relationships betw.. Read More»
  DOI: 10.37421/2168-9679.2024.13.569

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