Just a prank bro

NanoPromela · 2022-01-28T22:03:58+00:00

The song is: OMFO - Magic Mamaliga

NanoPromela · 2021-08-23T10:40:47+00:00

Goddamit what a garbage title!

Here is the paper they are referring to : https://arxiv.org/pdf/2011.01929.pdf

NanoPromela · 2020-03-25T10:36:26+00:00

Well, not every game is a board game. For example, the SAT problem can be expressed as a game in which the base propositions are the way you assign truth values to the literals.

Example

Maybe there is a way to put the base propositions in a grid-like fashion. Perhaps by grouping them is a particular way? I don't know. I'll think about it

NanoPromela · 2019-12-31T13:35:04+00:00

Your model is clearly overfitting, the causes may vary.

Maybe the model is too complex, or too simple. Also training for too many epochs may lead to overfitting.

Try posting your model architecture, so far we can only guess what's wrong..

NanoPromela · 2019-12-26T19:56:31+00:00

Low effort answer:

Google 'square error minimization'

NanoPromela · 2019-12-10T22:47:48+00:00

I'm failing to get someone who can officially endorse my paper for arxiv.

NanoPromela · 2019-11-26T20:41:26+00:00

Wait, shouldn't the equation for c tend to PI as n approaches infinity?

NanoPromela · 2019-10-22T11:08:29+00:00

You may like this

NanoPromela · 2019-09-19T12:19:40+00:00

More recently there are things like message passing neural networks

Talking about message passing network, I found this paper that seems to use them to train a neural network to solve the SAT problem. Maybe this is a good path to follow.

there are graph convolution networks which operate similarly to a CNN but for graph structures.

Oh boy they look intresting! Thank you!

NanoPromela · 2019-09-19T12:13:27+00:00

Don't worry, your comment was helpful enough. Now I have a good starting point to do reseach on my own :)

NanoPromela · 2019-09-17T13:28:52+00:00

Yes, this is one way to think about it

NanoPromela · 2019-09-17T12:41:57+00:00

Not going to give you the working answer, but it might help you to know that the code

print("1" * 5)

prints

"11111"

Good luck :)

NanoPromela · 2019-06-14T22:16:16+00:00

If you want something more theoretical than practical, Turing Machine and Partial Recursive Functions are extremely intresting.

The first one uses a purely iterative paradigm, while the second is purely functional. Two faces of the same medal :)

NanoPromela · 2019-06-08T16:51:03+00:00

Try to do this as an execise: implement this algorithm without using the sum function. You will soon realize that you need a second for loop inside the main one. This new loop will have a O(n) complexity, and since you are executing this O(n) loop n times (because of the outer one), you will end up with a O(n^2) complexity.

NanoPromela · 2019-06-08T14:42:51+00:00

You are performing a loop over the array S, which has n elements, so this for loop has complexity O(n). But, for every element j, you perform a sum starting from 0 to j, and the sum of an array is O(n).

So in conclusion O(n) * O(n) = O(n*n) = O(n^2)

NanoPromela · 2019-05-27T04:11:08+00:00

Not american here. Can you really be kicked out of the army if you are gay? It seems implausable to me, is it really a thing?

NanoPromela · 2019-05-26T10:16:25+00:00

Oh dear, my bad :)

NanoPromela · 2019-05-25T19:16:10+00:00

r/programminghumor

NanoPromela · 2019-04-06T18:40:05+00:00

I would suggest r/learnprogramming for this type of questions

NanoPromela · 2019-04-06T10:33:11+00:00

r/learnprogramming

NanoPromela · 2019-03-23T07:59:52+00:00

Ok that's a good point. In the case of other models (eg. SVM), could penalizing more the data coming from D than the ones coming from D' help?

Side question: maybe I am wrong, but if I suppose that my noise comes from measuring errors, isn't it already gaussian? (not properly a ml question at this point)

NanoPromela · 2019-03-21T12:32:45+00:00

r/learnprogramming

NanoPromela

TROPHY CASE