[HN Gopher] A Little Calculus
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A Little Calculus
Author : __rito__
Score : 41 points
Date : 2023-05-03 09:47 UTC (1 days ago)
(HTM) web link (papl.cs.brown.edu)
(TXT) w3m dump (papl.cs.brown.edu)
| [deleted]
| haskellandchill wrote:
| Wish they covered co-induction. I've read the paper linked in the
| definition but still don't have a very strong intuition for it.
| excalibur wrote:
| A little bit of calculus in my life
|
| A little trigonometry by my side
|
| A little Fibonacci's all I need
|
| A little inequality's what I see
|
| A little bit of lambda in the sun
|
| A little bit binary all night long
|
| A little probability, here I am
|
| A little [?]2 makes me your man
| sampo wrote:
| > We'll implement _numerical_ differentiation, though in
| principle we could also implement _symbolic_ differentiation
|
| I'd like to argue, that when it comes to computers and
| differentiation, _automatic_ differentiation is the most useful,
| most important in practice. But often only _symbolic_ and
| _numerical_ differentiation are mentioned.
| version_five wrote:
| AD is important for training neural networks, or sgd (et al)
| generally. But that's still only one field. Numerical
| differentiation is still important e.g. for differential
| equation solvers. I don't think you can say AD is the most
| important or useful - maybe for understanding pop culture.
| reikonomusha wrote:
| I think this is because automatic differentiation is a
| manifestation of just one rule of differentiation: the chain
| rule. With numerical differentiation, you only need to be able
| to evaluate the function at hand. With automatic
| differentiation, you need to "seed" your program with the
| differentials of all existing functions.
|
| What's nice about a discussion of symbolic differentiation is
| that we can prove a few rules rigorously, and then use those
| rules to purely mechanically differentiate algebraic
| expressions we encountered up to trigonometry.
|
| You're right though, in practice, for complex functions
| expressed as programs, automatic differentiation is superior.
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