Questions tagged [derivation]

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Deriving vectorized form of linear regression

We first have the weights of a D dimensional vector $w$ and a D dimensional predictor vector $x$, which are all indexed by $j$. There are $N$ observations, all D dimensional. $t$ is our targets, i.e, ...
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38 views

Why is it valid to remove a constant factor from the derivative of an error function?

I was reading the book 'Make your own neural network' by Tariq Rashid. In his book, he said: (Note - He's talking about normal feed forward neural networks) The $t_k$ is the target value at node $k$, ...
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46 views

How is this score function estimator derived?

In this paper they have this equation, where they use the score function estimator, to estimate the gradient of an expectation. How did they derive this?
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Are the equations following equations derived for the delta of weights in back propagation correct?

Specifically, I am wondering about summing the partial derivative of error in relation to the previous node's output for all superseding layers. My network is a 4 layer feed forward network; layer one ...
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1answer
31 views

Is it valid to use numpy.gradient to find slope of line as well as slope of curve at any point?

what is the difference between slope of the line and slope of the curve? Is it valid to use numpy.gradient to find the slope of the line and slope of the curve at ...
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1answer
97 views

1st order Taylor Series derivative calculation for autoregressive model

I wrote a blog post where I calculated the Taylor Series of an autoregressive function. It is not strictly the Taylor Series, but some variant (I guess). I'm mostly concerned about whether the ...
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Derivative of Loss wrt bias term

I read this and have an ambiguity. I try to understand well how to calculate the derivative of Loss w.r.t to bias. In this question, we have this definition: ...
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43 views

Maximum Entropy Policy Gradient Derivation

I am reading through the paper on Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review by Sergey Levine. I am having a difficulty in understanding this part of the ...
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17 views

Derivation of Bayes classifier in Murphy's book

I am reading Kevin Murphy's Machine Learning book (MLAPP, 1st printing) and want to know how he got the expression for the Bayes classifier using minimization of the posterior expected loss. He wrote ...
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back propagation through time derivation issue

I read several posts about BPTT for RNN, but I am actually a bit confused about one step in the derivation. Given $$h_t=f(b+Wh_{t-1}+Ux_t)$$ when we compute $\frac{\partial h_t}{\partial W}$, does ...
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1answer
48 views

Doubt in Derivation of Backpropagation

I was going through the derivation of backpropagation algorithm provided in this document (adding just for reference). I have doubt at one specific point in this derivation. The derivation goes as ...
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A Derivation in Combinatory Categorial Grammer

I am reading about CCG on page 23 of Speech and Language processing. There is a derivation as follows: (VP/PP)/NP , VP\((VP/PP)/NP) => VP? Can anyone example ...