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nhigham.com | ||
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stephenmalina.com
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| | | | | Matrix Potpourri # As part of reviewing Linear Algebra for my Machine Learning class, I've noticed there's a bunch of matrix terminology that I didn't encounter during my proof-based self-study of LA from Linear Algebra Done Right. This post is mostly intended to consolidate my own understanding and to act as a reference to future me, but if it also helps others in a similar position, that's even better! | |
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vxy10.github.io
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| | | | | Course material for MEC 560: Advanced Control Systems taught at Stony Brook University by Dr. Vivek Yadav | |
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spacedome.tv
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| | | | | [AI summary] A technical explanation of trace estimation methods for large matrices using matrix-vector multiplications, including the Girard-Hutchinson estimator and code examples in Haskell. | |
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algorithmsoup.wordpress.com
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| | | The ``probabilistic method'' is the art of applying probabilistic thinking to non-probabilistic problems. Applications of the probabilistic method often feel like magic. Here is my favorite example: Theorem (Erdös, 1965). Call a set $latex {X}&fg=000000$ sum-free if for all $latex {a, b \in X}&fg=000000$, we have $latex {a + b \not\in X}&fg=000000$. For any finite... | ||
