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 blogs.princeton.edu
Guest post by Amir Ali Ahmadi: Sum of Squares (SOS) Techniques: An Introduction, Part I/II | I'm a bandit
| | nhigham.com
What Is a Householder Matrix? - Nick Higham
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| | A Householder matrix is an $latex n\times n$ orthogonal matrix of the form $latex \notag P = I - \displaystyle\frac{2}{v^Tv} vv^T, \qquad 0 \ne v \in\mathbb{R}^n. $ It is easily verified that $LATEX P$ is orthogonal ($LATEX P^TP = I$), symmetric ($LATEX P^T = P$), involutory ($LATEX P^2 = I$ that is, $LATEX P$ is...
| | arnavdhamija.com
Introduction to Model Predictive Control ยท Arnav's Weblog
5.3 parsecs away

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| | [AI summary] A technical blog post introduces Model Predictive Control, explaining its roots in chemical processing, its mathematical formulation using discrete systems and cost functions, and its application to robotics and autonomous vehicles.
| | francisbach.com
Sums-of-squares for dummies: a view from the Fourier domain - Machine Learning Research Blog
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| | thehighergeometer.wordpress.com
Small fun observation about finite topological spaces, and some challenges - theHigherGeometer
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| Here's a fun thing: if you want to generate a random finite $latex T_0$ space, instead select a random subset from $latex \mathbb{S}^n$, the $latex n$-fold power of the Sierpinski space $latex \mathbb{S}$, since every $latex T_0$ space embeds into some (arbitrary) product of copies of the Sierpinski space. (Recall that $latex \mathbb{S}$ has underlying...