# Questions tagged [matrix]

A matrix is a collection of numbers arranged into a fixed number of rows and columns.

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### What are the general rules or principles for finding matrix operations that are used as filters in convolutional neural networks?

Is there a set of rules or guidelines for designing filters for convolutional neural networks? For example, a 3 x 3 layer with ones in the first column, zeroes in the second, and negative ones in the ...
33 views

### What is numpy.dot(a, b)[i,j,k,m] = sum(a[i,j,:] * b[k,:,m]) in numpy.dot() documentation?

I was trying to understand difference between np.dot and np.matmul and in the docs of np.dot() there is this code dot(a, b)[i,j,k,m] = sum(a[i,j,:] * b[k,:,m]). ...
15 views

### How do I reconstruct irregularly spaced lat-lon data (in the form of a matrix) using spherical harmonic fitting?

Introductory Links to spherical harmonics give a mildly rigorous introduction to the concept; but very few links describe how to actually use them. I have latitude-longitude data arranged the ...
124 views

### Flattening before Fully-connected Layer (DENSE)

Can anyone explain why we need to flatten the data before inputting it into a fully-connected layer? What will happen if we input a matrix of size (m,n) into a fully-connected layer that has k ...
639 views

### Using pyspark to create a large precomputed cosine similarity matrix from text data

I would like to precompute a cosine similarity matrix for a large dataset (upwards of 5 million rows) using pyspark. Here's what I have so far. libraries: ...
17 views

### Averaging subregion correlation coefficients into a single measure

I've got a 257x257 correlation matrix of functional connectivity (fMRI) data. It is a symmetric matrix where each value is the Pearsons correlation of the brain area in the row with the brain area in ...
41 views

### Determining "filters" dimension after a convolution operation

I tried to calculate the "filtered" dimension and I seem to be getting it wrong. Below there is the image I am trying to calculate the "filtered" dimension for, where you have 192 ...
10 views

### Rotate vector anticlockwise

I'm learning mathematics for Machine Learning, and there given a vector [ 1 0 ] and [ 0 1 ]. The vector is packed on a matrix, ...
18 views

### How to derive expression for gradient in BPPT

I have the following problem: I am trying to derive final expressions for error gradients in a simple recurrent neural network (Backpropagation through Time, BPPT). The parameters and state update ...
1 vote
289 views

### Is it possible to reverse the layers of a convolutional neural network?

From my understanding typically a convolutional neural network has a matrix (e.g. an image) as input and output is either an integer or a vector of integers in regression and in classification a ...
12 views

8k views

### What types of matrix multiplication are used in Machine Learning? When are they used?

I'm looking at equations for neural networks and backpropagation and I see this symbol in the equations, ⊙. I thought matrix multiplication of neural networks always involved matrices that matched ...
1 vote
43 views

### Can all known ML algorithms be written as a sequence of matrix operations?

I keep hearing that machine learning is just linear algebra. Does that mean all known (and all possible?) ML algos, from random forest, to support-vector machines, to recursive neural networks, can ...
554 views

### How to create a matrix from two given vectors in R in RStudio?

Suppose, $c(1, 2, 3, 4)$ and $c(2, 4, 5, 6)$ are two vectors. Then in R or RStudio, How to create a $4\times 2$ matrix from these two vectors? Also, how to add another vector $c(8, 9, 10, 11)$ ...
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### Trying to understand the result provided by np.linalg.norm function in numpy (normalisation)

I'm new to data science with a moderate math background. I'm playing around with numpy and can across the following: So after reading np.linalg.norm, to my ...
124 views

### How do I use matrix math in irregular neural networks such as those generated from neuroevolution (NEAT)?

I understand how to structure the matrix when every node in a layer is fully connected to every node in adjacent layers and I understand that in "irregular" neural networks I can just process each ...
1 vote
30 views

### What is the kernel matrix used for in the kernel trick?

I have $n$ linearly inseperable datapoints, $x_1 \dots , x_n$. I use the kernel trick to map and compute the dot product in higher dimensions (without actually mapping / transforming the data). ...
1 vote
672 views

### How to compute Hessian matrix for log-likelihood function for Logistic Regression

I am currently studying the Elements of Statistical Learning book. The following equation is in page 120. It calculates the Hessian matrix for the log-likelihood function as follows \begin{equation} ...