Re: [sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-27 Thread rjf
The problem chosen seems to be integrate((16*x^3-42*x^2+2*x)/sqrt(-16*x^8+112*x^7-204*x^6+28*x^5-x^4+1),x) The integrand is of the form dy/sqrt(1-y^2) and so the integral is arcsin(y). An algorithm to look for this kind of pattern (in general) would not be difficult to write, although it does

Re: [sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-26 Thread Dima Pasechnik
On Thu, Dec 26, 2019 at 11:54 AM Brent W. Baccala wrote: > > > I know the Risch algorithm fairly well. > > I made two screencast videos describing how to use Axiom or Sage to simplify > one of the integrals used in the Facebook paper. > > Quick summary - Axiom works quite well. Sage can't do it

Re: [sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-25 Thread Brent W. Baccala
I know the Risch algorithm fairly well. I made two screencast videos describing how to use Axiom or Sage to simplify one of the integrals used in the Facebook paper. Quick summary - Axiom works quite well. Sage can't do it in one step, but the new function field features in Sage 9 allow the i

Re: [sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-19 Thread Dima Pasechnik
On Wed, Dec 18, 2019 at 6:05 PM E. Madison Bray wrote: > > On Wed, Dec 18, 2019 at 6:39 AM rjf wrote: > > > > I was trying to come up with a simple example of how this integration > > program claim > > was bogus. Here it is. > > > > Take one of your favorite prime-testing programs and generate

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-18 Thread rjf
See, for example, Rubi, or my earlier project Tilu, for programs that > absorbed, in some sense learning from tables of integrals. This is not classical machine learning, because the objects being learned are patterns. So the result for sin(x)dx works for sin(u)du, as a trivial pattern matc

Re: [sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-18 Thread E. Madison Bray
On Wed, Dec 18, 2019 at 6:39 AM rjf wrote: > > I was trying to come up with a simple example of how this integration program > claim > was bogus. Here it is. > > Take one of your favorite prime-testing programs and generate > a list of 10,000 Largish Primes. I don't know how large, but > say 5

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-17 Thread rjf
I was trying to come up with a simple example of how this integration program claim was bogus. Here it is. Take one of your favorite prime-testing programs and generate a list of 10,000 Largish Primes. I don't know how large, but say 50 decimal digits or more. Make 10^8 factorization problem

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-17 Thread Richard_L
I was unclear. Davis disagrees with Lample and Charton in their claim of neural nets being somehow superior to established CAS. (And yes, the review is by Davis, not Lample.) On Tuesday, December 17, 2019 at 4:21:07 PM UTC-8, rjf wrote: > > disagrees with me? or Emmanuel? > Lample's abstract (

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-17 Thread rjf
oops, the review is by Davis; the paper is by Lample and Charton, both of Facebook. On Tuesday, December 17, 2019 at 4:21:07 PM UTC-8, rjf wrote: > > disagrees with me? or Emmanuel? > Lample's abstract (of the review) concluded with > > The claim that this outperforms Mathematica on symbolic i

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-17 Thread rjf
disagrees with me? or Emmanuel? Lample's abstract (of the review) concluded with The claim that this outperforms Mathematica on symbolic integration needs to be very much qualified. I glanced at the full review and I don't see that I disagree with it. Generating 80 million randomly generated e

Re: [sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-16 Thread Richard_L
You could e-mail the authors, now that you have names and addresses. Maybe they'd part with source. On Monday, December 16, 2019 at 7:39:11 AM UTC-8, Dima Pasechnik wrote: > > > > On Mon, 16 Dec 2019, 15:14 Richard_L, > > wrote: > >> Apparently, someone disagrees. See Ernest Davis's posting to

Re: [sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-16 Thread 'Martin R' via sage-devel
I tested (some of?) the integrals from Table 7 with FriCAS, without any (bad) surprises. Am Montag, 16. Dezember 2019 16:39:11 UTC+1 schrieb Dima Pasechnik: > > > > On Mon, 16 Dec 2019, 15:14 Richard_L, > > wrote: > >> Apparently, someone disagrees. See Ernest Lample's posting to the arXiv: >>

Re: [sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-16 Thread Dima Pasechnik
On Mon, 16 Dec 2019, 15:14 Richard_L, wrote: > Apparently, someone disagrees. See Ernest Lample's posting to the arXiv: > https://arxiv.org/abs/1912.05752 > > On Friday, September 27, 2019 at 8:06:31 AM UTC-7, Dima Pasechnik wrote: >> >> https://openreview.net/pdf?id=S1eZYeHFDS >> >> I wish they

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-12-16 Thread Richard_L
Apparently, someone disagrees. See Ernest Lample's posting to the arXiv: https://arxiv.org/abs/1912.05752 On Friday, September 27, 2019 at 8:06:31 AM UTC-7, Dima Pasechnik wrote: > > https://openreview.net/pdf?id=S1eZYeHFDS > > I wish they had code available... > -- You received this message

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-10-07 Thread rjf
I am not aware specifically of the methods used in FriCAS. It is possible, I suppose, that given an expression it immediately tries to find an appropriate differential field and begins some version of the Risch "algorithm" (which actually fails to be an algorithm for various reasons), and doesn't

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-10-07 Thread 'Martin R' via sage-devel
> > >> Are you saying that FriCAS is the only CAS which doesn't do this? >> > > AFAICT, FriCAS dos this also... > > I don't think so - are you sure? Neither do I not know the Risch algorithm nor FriCAS' implementation of it too well, but I would have thought that FriCAS doesn't do pattern mat

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-10-07 Thread Emmanuel Charpentier
! What you describe - is doable, and - is outright academic fraud... I doubt somehow that the authors would be dumb enough to risk that. "Never assign to human ill will what can be explained by human stupidity". (Napoleon Bonaparte, IIRC). However, I agree that using an external

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-10-07 Thread Emmanuel Charpentier
Hi, Martin ! Le lundi 7 octobre 2019 11:30:17 UTC+2, Martin R a écrit : > > > Here's the trick. S' will, with very high probability, be a sum. Say >> s1+s2+s3. >> A CAS will usually try to compute integrate(s1,x) + integrate(s2,x)+ >> integrate(s3,x). >> That's the way integral tables work too

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-10-07 Thread 'Martin R' via sage-devel
> Here's the trick. S' will, with very high probability, be a sum. Say > s1+s2+s3. > A CAS will usually try to compute integrate(s1,x) + integrate(s2,x)+ > integrate(s3,x). > That's the way integral tables work too. > > Are you saying that FriCAS is the only CAS which doesn't do this? Marti

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-10-06 Thread rjf
If they were interested in a fair comparison they would use a test set from (for example) Rubi or one of the CAS. My guess is that they did this: 1. generate a random expression S favoring + and * in the tree. 2. differentiate S to get S' 3. "learn" the integral of S'. Here's the trick. S' w

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-10-01 Thread Emmanuel Charpentier
Le mercredi 2 octobre 2019 01:48:15 UTC+2, rjf a écrit : > > I think that if you read the paper you would not expect it to compete with > a CAS > except on its made-up artificial testset. > Could you amplify ? > RJF > > > On Monday, September 30, 2019 at 10:57:44 AM UTC-4, Martin R wrote: >>

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-10-01 Thread rjf
I think that if you read the paper you would not expect it to compete with a CAS except on its made-up artificial testset. RJF On Monday, September 30, 2019 at 10:57:44 AM UTC-4, Martin R wrote: > > Actually, I think it would be even more interesting to compare with > FriCAS, because FriCAS has

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-09-30 Thread 'Martin R' via sage-devel
Actually, I think it would be even more interesting to compare with FriCAS, because FriCAS has the most complete implementation of the Risch algorithm and does not at all rely on pattern matching. Martin Am Sonntag, 29. September 2019 15:00:01 UTC+2 schrieb mmarco: > > I would be very interest

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-09-29 Thread mmarco
I would be very interested in comparing their results with RUBI. El viernes, 27 de septiembre de 2019, 21:53:00 (UTC+2), Eric Gourgoulhon escribió: > > Thanks for sharing! > This looks very promising. I hope we have it in Sage some day. > > Eric. > > Le vendredi 27 septembre 2019 17:06:31 UTC+2,

[sage-devel] Re: Machine Learning people apparently built a symbolic integrator

2019-09-27 Thread Eric Gourgoulhon
Thanks for sharing! This looks very promising. I hope we have it in Sage some day. Eric. Le vendredi 27 septembre 2019 17:06:31 UTC+2, Dima Pasechnik a écrit : > > https://openreview.net/pdf?id=S1eZYeHFDS > > I wish they had code available... > -- You received this message because you are sub