<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Uddant</title><description>My personal website</description><link>https://uddant.com/</link><item><title>Form Follows Function(al): Improving a Matrix Algorithm</title><link>https://uddant.com/blog/top-k-sv-algorithm/</link><guid isPermaLink="true">https://uddant.com/blog/top-k-sv-algorithm/</guid><description>This blog post uses concepts from functional analysis and approximation theory including Chebyshev polynomials and Lp space theory to prove the quadratic improvement of the Lanczos method over the simple power method to find the largest or top singular value of a matrix. Keywords: functional analysis, approximation theory, linear algebra, matrix algorithms, data science, singular value decomposition</description><pubDate>Mon, 13 Jul 2026 00:00:00 GMT</pubDate></item></channel></rss>