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 djalil.chafai.net
A probabilistic proof of the Schoenberg theorem - Libres pensées d'un mathématicien ordinaire
| | windowsontheory.org
A blitz through classical statistical learning theory - Windows On Theory
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| | Previous post: ML theory with bad drawings Next post: What do neural networks learn and when do they learn it, see also all seminar posts and course webpage. Lecture video (starts in slide 2 since I hit record button 30 seconds too late - sorry!) - slides (pdf) - slides (Powerpoint with ink and animation)...
| | quanttype.net
What is functional analysis? - quanttype
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| | Spoiler: It's not related to functional programming.
| | fa.bianp.net
On the Convergence of the Unadjusted Langevin Algorithm
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| | The Langevin algorithm is a simple and powerful method to sample from a probability distribution. It's a key ingredient of some machine learning methods such as diffusion models and differentially private learning. In this post, I'll derive a simple convergence analysis of this method in the special case when the ...
| | nhigham.com
What Is a Unitarily Invariant Norm? - Nick Higham
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| A norm on $latex \mathbb{C}^{m \times n}$ is unitarily invariant if $LATEX \|UAV\| = \|A\|$ for all unitary $latex U\in\mathbb{C}^{m \times m}$ and $latex V\in\mathbb{C}^{n\times n}$ and for all $latex A\in\mathbb{C}^{m \times n}$. One can restrict the definition to real matrices, though the term unitarily invariant is still typically used. Two widely used matrix norms...