Mathematical and Statistical Tools for High Dimensional Data on Compressive Networks (24w5199)


Linglong Kong (University of Alberta)

Ping-Shou Zhong (University of Illinois at Chicago)

(University of North Carolina at Chapel Hill)

Jordan Rodu (University of Virginia)


The Casa Matemática Oaxaca (CMO) will host the "Mathematical and Statistical Tools for High Dimensional Data on Compressive Networks" workshop in Oaxaca, from May 26 to May 31, 2024.

Large-scale, high-dimensional data sets are becoming ubiquitous in modern society, particularly in the areas of physical, biomedical, and social applications. For example, in the problem of predicting thyroid malignancy from biopsy images, the images are typically about 150,000 by 100,000 dimensions, which limit the application of many existing methods. There is an urgent need for accurate and efficient mathematical and statistical tools for the analysis and engineering of high-dimensional data sets. The proposed 5-Day workshop will bring researchers from different disciplines to collaboratively address the foundational computational and theoretical challenges in high-dimensional data analysis.

The workshop is designed around the simple question ``how to accurately and efficiently process large-scale data in 10+ dimensions’’. Invited participants will review existing mathematical and statistical tools for high dimensional data sets, including the Monte Carlo methods, randomized algorithms, dimension reduction, sparse grid, network analysis, and interpolation-based deep neural networks, and compare their performance and address their limitations. The invited participants will collaboratively address the current challenges in high-dimensional data analysis, and design new strategies by combining existing tools and by introducing new methodologies for problems in 10+ dimensions.

The Casa Matemática Oaxaca (CMO) in Mexico, and the Banff International Research Station for Mathematical Innovation and Discovery (BIRS) in Banff, are collaborative Canada-US-Mexico ventures that provide an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station in Banff is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT). The research station in Oaxaca is funded by CONACYT