Hi Ishan
Thanks for your impressive work.
Thanks for closing my other question. Now I could understand your code. I do however have a question
In line https://github.com/ijindal/Noisy_Dropout_regularization/blob/master/Random_noise.m#L28 it is written that we are generating a sample from the distribution
vect_prob = mnrnd(1,w(tt,:)); for the tt class
This has been done for both the files Uniform_noise.m and Random_noise.m.
According to your paper, the matrix is column stochastic and hence we should sample from each column. So should not be the line replaced with
vect_prob = mnrnd(1,w(:,tt)); for the tt class ?
I mean for the Uniform_noise.m it should not matter but for the Random_noise.m it should matter.
Please let me know this or is my understanding wrong?
Thanks
Devraj
Hi Ishan
Thanks for your impressive work.
Thanks for closing my other question. Now I could understand your code. I do however have a question
In line https://github.com/ijindal/Noisy_Dropout_regularization/blob/master/Random_noise.m#L28 it is written that we are generating a sample from the distribution
vect_prob = mnrnd(1,w(tt,:));for thettclassThis has been done for both the files
Uniform_noise.mandRandom_noise.m.According to your paper, the matrix is column stochastic and hence we should sample from each column. So should not be the line replaced with
vect_prob = mnrnd(1,w(:,tt));for thettclass ?I mean for the
Uniform_noise.mit should not matter but for theRandom_noise.mit should matter.Please let me know this or is my understanding wrong?
Thanks
Devraj