Questions tagged [machine-learning]

Machine learning, a branch of artificial intelligence, is the science of getting computer systems to meaningfully act without being explicitly programmed by human.

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Identifying an unknown P.D.E. from solution data

I have a black-box simulation that produces the time evolution of a probability density function p(x, t) in 1 dimension from arbitrary initial conditions p(x, 0). The underlying simulation occurs on a ...
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79 views

Calculus of Variations with unknown cost function but some data

I have a problem that I've framed out in a particular way, but I don't know if I'm re-inventing the wheel here. Is there an existing literature base in this problem? Does it have a corresponding term ...
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112 views

A maximization problem, with motivation in machine learning

Consider the minimization problem described this paper. Let $f_{\lambda}$ be the minimizer. As a part of extending my work, I am able to show the following facts $$\lim_\limits{\lambda \to 0}\|f_{\...
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104 views

Are the No Free Lunch Theorems Useful for Anything?

I have been thinking about the No Free Lunch (NFL) theorems lately, and I have a question which probably every one who has ever thought of the NFL theorems has also had. I am asking this question here,...
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67 views

Variational loss of hp-Variational Physics Informed Neural Networks for 2D-Poisson Equation in Tensorflow

I am trying to reproduce the results from the hp-VPINN paper (https://arxiv.org/pdf/2003.05385.pdf) on tensorflow (v1) for Poisson's equation, particularly the two-dimensional Poisson equation. In one ...
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121 views

Proving convexity of Frobenius norm and correlation function formulations of an optimization problem

I have been working on formulating my requirements in the form of an optimization problem in a multi-output regression setting. Firstly, I would like to make the variables I used in the problem and ...
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256 views

scipy.linalg.sparse.eigsh does not work for generalised eigenvalues

I asked this question over at StackOverflow and someone told me that I'd get a better answer here. So here's my problem: I'm working on a machine learning project which involves doing a Principal ...
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1k views

What is average pooling

I was reading an article where they have a set of pages. For every page they extract a feature vector of dimention 300. Then they fuse these vectors into one vector by using a method called average ...
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1answer
72 views

Activation function with special conditions in machine learning

I only have a basic understanding of deep learning, but looking through it I had an idea on how to approximate global minima of the NN. However, for it's activation function I am only able to use: ...
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48 views

Neural networks trained with subspace iteration algorithms for solving SCF eigenvalue problems

I am toying with the idea of using current libraries available with SCF (Self-Consistent Field) subspace iteration codes to train an ANN (Artificial Neural Network) to solve for SCF eigenvalue ...
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29 views

How property-invariance is imposed to neural nets?

I was wondering how specific symmetries or constraints such as property-invariance transformation are imposed on any (deep) neural net when they are trained. I'll appreciate it if anyone can aware me ...
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30 views

Why is scoring a separate problem even after docking is done?

With regards to protein-ligand interactions, we talk about two concepts, docking and scoring. I understand that docking means to find the best orientation of a ligand at the active site of a protein, ...
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85 views

Eigenfaces Algorithm

This might be a silly quesntion but recently I've been trying to program the eigenface algorithm using PCA, so I arranged the face vectors vertically in a matrix X such as: X = [x1,x2,x3,...,xn]; In ...
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21 views

Tracking channel states using Machine Learning

I am new in AI and would like to apply machine learning to estimate the channel states. I have a set of data. It is a matrix of 10000*8. Each row of this matrix is regarding a time step, i.e., 1st row ...
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51 views

Singular Spectrum Analysis Explanation

I need you to help me understand the Singular Spectrum Analysis algorithm. I already read a lot of articles about the subject but they never answered my questions like what is the mathematical reason ...
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103 views

Connection between piecewise linear basis functions and RELU activation function

ReLU activation is defined as follows $$\sigma(x)=\max(0, x).$$ Let's assume that I have deep network of 1 hidden layer, than output from my layer has form $$ f(x)= \sigma(Wx +b), $$ where matrix W ...
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45 views

What is a performant clustering algorithm for approx 10,000 vectors of approx 30 dimension?

I have a set of real-valed vectors, for example $S = \{v_1, v_2, ..., v_k\}$ $v_i = \begin{pmatrix} age_i \\ height_i \\ weight_i \\ ... \end{pmatrix}$ or whatever. Each vector has on the order of ...
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98 views

Is there any ML solutions for permutations?

In Machine Learning field, is there any work done, or research, or info in general about finding optimal permutations? For eg. to find a number of optimal arrangements of sliced shapes on 2D sheet of ...
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50 views

Update model parameter with new data, discarding old data

I have this dataset, and I am using y = (a * x^n) / (b + x^n) Hill function as the model, where a is the limit of the Hill curve,...
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0answers
15 views

Optimizing estimator of composed functions when function is known

Note: This was cross-posted from comp-sci, as I didn't know this community existed! I have a problem which I'm looking to see if there is literature on: Consider three types of actors, a Director, ...
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261 views

Generalization error and Sample Complexity estimation for Least Squares

I am wondering how to draw a sample complexity plot similar to the following figure which shows the estimated number of samples to incur no more than 10 percent generalisation error on average for the ...
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64 views

How to make the following data separable for the classification into three classes?

The figure below shows the PCA projections of inputs which are 14 meteorological features, (i.e. wind, temperature, humidity, pressure, and so on.) I would like to use any technique to make it more ...
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38 views

How to find active region in treepartition Matlab object

I am trying to identify a non-linear plant using the identification toolbox of Matlab. In particular I would like to identify a non-linear arx model, where the nonlinearities are expressed by means of ...
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85 views

How to create synthetic data from known weights

I'm doing some machine learning where I have lots of data and through optimization I'm trying to learn the weights for the model. I'd like to check that my learning actually works correctly. For that ...
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127 views

Getting euclidean distance between vector A and C without anyway of retrieving them when their distances with a common vector B is known

Motivation: My plan is to get the overall euclidean distance matrix for all the vectors in N number of dataset. Each dataset is basically an array of n-dimensional points. For e.g: A dataset can be ...
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51 views

Unsupervised event prediction with time series data

I have to solve a problem using unsupervised time series forecast. I have a dataset where three columns are given, 1. Endtime: when the row was generated ( it generates a row after each 54-55 seconds)...
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56 views

exploding gradients in gradient descent procedure of multi-output ridge regression

Multi-output ridge regression: $$W^{*}=\underset{W}{\arg \min } \frac{1}{\mathcal{N}}\|Y-WX\|_{F}^{2}+\lambda\|W\|_{F}^{2}$$ There are $Q$ outputs, $N$ samples, and $P$ covariates (features). $\hat{...
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66 views

approximation of nonlinear time-dependent system with history

I have two time-dependent coupled equations. One of which is several orders of magnitude more computationally demanding than the other. I am trying to use machine learning to reproduce the behavior of ...
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2answers
68 views

How to find the relationship between an independent variable in a time series and a single dependent variable

I have a dataset of crop yield of a seasonal crop, under environmental conditions (rainfall, humidity, temperature etc.). Daily environmental conditions are recorded over few years with the crop yield ...