Lecture notes on high-dimensional data
Functional Analysis
2024-09-24 v7 Machine Learning
Abstract
These are lecture notes based on the first part of a course on 'Mathematical Data Science', which I taught to final year BSc students in the UK in 2019-2020. Topics include: concentration of measure in high dimensions; Gaussian random vectors in high dimensions; random projections; separation/disentangling of Gaussian data. A revised version has been published as part of the textbook [Mathematical Introduction to Data Science, Springer, Berlin, Heidelberg, 2024, https://link.springer.com/book/10.1007/978-3-662-69426-8].
Cite
@article{arxiv.2101.05841,
title = {Lecture notes on high-dimensional data},
author = {Sven-Ake Wegner},
journal= {arXiv preprint arXiv:2101.05841},
year = {2024}
}
Comments
57 pages; link in abstract corrected