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Taking Vector Transposes Seriously | Jiahao Chen | JuliaCon 2017

The Julia Programming Language · 7.4K views · 2017-07-17 · 19:12

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Overview

Jiahao Chen's JuliaCon 2017 talk argues that vector transposes should be taken seriously in type systems and linear algebra libraries. It explains why treating vectors as matrices causes trouble in languages.

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Strongly recommended for anyone working with vectors for its clear take on how they should be treated in types.

Recommended by 3 HN people across 5 months · HN mentions 2018–2022

Topics

Programming language designPure mathematics
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julialinear algebratype systemsvectorsjuliacon

What people said

dnautics · 2020-10 · Strong recommendation

> Purist test The short answer is. Yes, but if your PL treats it that way you will wind up in trouble [0]. The long answer is: [VIDEO] (but seriously take the time to watch this, it's fantastic). [0] Separately C- and often C-derived languages/frameworks like numpy also treat them as 1xN matrices, but that's a nearly tabs-vs-spaces level religious war, with actual consequences. I think a lot of people got confused when translating andrew ng's early octave-based ML coursera course (Nx1) to python (1xN), and also in the back and forth between math ML papers which use Nx1 and python.

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dnautics · 2018-03 · Strong recommendation

Addendum: Also really good is this video about how one should treat vectors and matrices in a type system. Has good lessons for python, R, and Matlab. Seriously anyone who does anything with vectors should watch this. [VIDEO]

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gugagore · 2022-04 · Recommendation

If you want a great video on the topic, see [VIDEO] Or equivalently [LINK] There are basically two self-consistent choices for the design of linear algebra libraries.

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Video by The Julia Programming Language, played through YouTube.

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