Taking Vector Transposes Seriously | Jiahao Chen | JuliaCon 2017
Taking Vector Transposes Seriously | Jiahao Chen | JuliaCon 2017 on HackerTube: recommended by 3 Hacker News commenters across 5 separate months, 2018–2022.
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.
What HN commenters said
5 Hacker News comments link this video. Each one links back to its thread.
dnauticsOct 2020Strongly recommends
> 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: ▶ this 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.
in “A Programmer’s Intuition for Matrix Multiplication” · View on HN
dnauticsMar 2018Strongly recommends
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. ▶ this video
in “Types, and Why You Should Care [video]” · View on HN
gugagoreApr 2022Recommends
If you want a great video on the topic, see ▶ this video Or equivalently [link] There are basically two self-consistent choices for the design of linear algebra libraries.
in “Eigen: A C++ template library for linear algebra” · View on HN
freemintJul 2021Recommends
If you will do a lot of matrix stuff you might want to listen to ▶ this video taking Vector Transpose Seriously
in “Julia Computing raises $24M Series A” · View on HN
dnauticsJun 2020Recommends
I happened to be the other way, I learned first that matrices were linear transformations and, being thick-headed, it took me a really long time to understand that matrices could also be used as "dumb excel spreadsheets". there's a fantastic historiography of linear algebra and why we're stuck in this situation here: ▶ this video
in “Why is it important for a matrix to be square? (2018)” · View on HN