Re:Limits on Matrix Multiplication
by crankylinuxuser on Saturday September 01, 2018 @12:36PM
(#17892619)
Then, would it be better to store rationals as 2 ints with understood division, and irrationals as 2 ints as understood powers?
Why are we working with these numbers so imprecisely, and with such discontinuity? When I've done math work in school, I always worked with the primitives without approximating.. 2^.5 was handled as such unless asked for an approximate answer.
I also ran across this in AutoCAD. Because they force arbitrary precision, one cannot define a sqrt length. 1.414 doesn't reach all the way on a r-triangle with 1,1 .
Re:Limits on Matrix Multiplication
by MauranKilom on Saturday September 01, 2018 @03:42PM
(#17893583)
That post completely disregards the fact that subnormals are usually orders of magnitude slower to work with for common hardware.
However, researchers at OpenAI demonstrated that the use of subnormal floating point values and their discontinuity [0] provides sufficient nonlinearity to learn nonlinear associations.
[0] https://blog.openai.com/nonlinear-computation-in-linear-netw...