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# 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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16 votes
5 answers
5k views

### Apply PCA on very large sparse matrix

I am doing a text classification task with R, and I obtain a document-term matrix with size 22490 by 120,000 (only 4 million non-zero entries, less than 1% entries). Now I want to reduce the ...
• 325
16 votes
3 answers
4k views

### Python OSS alternatives for Matlab Neural Network Toolbox. Any intercomparisons?

I'd like to be independent of commercial software for my scientific work. I find a dependence an commercial packages such as Matlab and its toolboxes unsatisfactory, because I do not know if I will ...
• 260
14 votes
3 answers
2k views

### Why aren't Krylov subspace methods popular in the Machine Learning community compared to Gradient Descent?

Historically, iterative methods for solving relatively simple-structured systems $Ax=b$ with $A$ being a $4\times 4$ matrix or to find the eigenvalues of that matrix assuming in both problems that $A$ ...
• 169
13 votes
6 answers
5k views

• 264
10 votes
2 answers
3k views

### Do RBF kernel matrices tend to be ill-conditioned?

I use RBF kernel function to implement one kernel based machine learning algorithm(KLPP), the resulting kernel matrix $K$ $$K(i,j)= \exp\left({\frac{-(x_{i}-x_{j})^2}{ \sigma_{m}^2}}\right)$$ is ...
• 317
10 votes
2 answers
4k views

### Calculating Lagrange coefficients for SVM in Python

I'm trying to write a full SVM implementation in Python and I have a few issues computing the Lagrange coefficients. First let me rephrase what I understand from the algorithm to make sure I'm on the ...
10 votes
1 answer
334 views

### Is it possible to express an arbitrary tensor contraction in terms of BLAS routines?

I noticed that libraries like numpy and pytorch are able to perform arbitrary tensor contractions at speeds similar to comparably sized matrix multiplications. This leads me to believe that underneath ...
• 111
9 votes
2 answers
187 views

### Predict runtimes for dense linear algebra

I would like to predict runtimes for dense linear algebra operations on a specific architecture using a specific library. I would like to learn a model that approximates the function $F_{op} \;::\;$...
• 3,058
9 votes
3 answers
4k views

### Are there tasks in machine learning which require double precision floating points?

Double-precision calculations are significantly slower or more expensive than single-precision calculations. For example, the NVidia Tesla which performs well on doubles is much more expensive then ...
9 votes
2 answers
4k views

### Markov (Chain) image generators?

Markov Chains can be used to generate, or auto-complete, text. https://en.wikipedia.org/wiki/Markov_chain#Markov_text_generators Training text is read, and some information about the text is ...
• 193
8 votes
3 answers
5k views

### fmincg implementation in Python

I'm trying to re-implement Neural Networks in Python. I implemented the cost function and the backpropagation algorithm correctly. I have checked them by executing its Octave equivalent code. But ...
• 223
7 votes
2 answers
244 views

### Learning parameters of noise and filter coefficients from data where data and noise both have Gaussian distributions

Assume $X$ and $N$ are two sets of vectors (observations) from two different normal distributions, where $X$ represents clean data and $N$ represents noise; and $A$ a projection matrix of a filter. ...
• 195
7 votes
4 answers
300 views

### Testing for stability of a simulated dynamical system

Background and question I often work with simulations of dynamical systems and I usually track a single parameter $x$, such as the number of agents (for agents based models) or the error rate (for ...
6 votes
1 answer
193 views

### Support Vector Machines as Neural Nets?

This is more of a conceptual question. I have learned about Neural Nets, and I have some clue as to how Support Vector Machines work. I read somewhere however that given the appropriate kernel (is ...
• 165
6 votes
2 answers
181 views

### Books/Resources on Sparse Optimization?

I'm looking to learn more about Sparse Optimization and apply it to machine learning problems. Could you please recommend some books/resources on this topic? Both theoretical and applied are fine.
5 votes
3 answers
510 views

• 141
3 votes
0 answers
108 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,...
2 votes
1 answer
142 views

### Machine Learning for Optimization

I have a function which takes 100+ coefficients and outputs $x$. I wish to optimise $x$. Running the simulation 50 000 times will take around 15 minutes, however, this happens in parallel - and the ...
• 123
2 votes
2 answers
189 views

### Handling inconsistent solutions obtained by PCA

In order to achieve a 2D representation $X\in\mathbb{R}^{n\times 2}$ of some high-dimensional data residing in $Y\in\mathbb{R}^{n\times k}$, I use PCA:$$X=Y\cdot U,$$where $U\in\mathbb{R}^{k\times 2}$ ...
• 1,663
2 votes
2 answers
133 views

• 1,663
2 votes
1 answer
72 views

### How to filter customer voice from customer - agent conversation recordings?

I have a doubt on the project I'm working now. Actually I want only customer voice from the recordings which contains customer-agent conversation.But I have no idea to filter customer voice from ...
• 21
2 votes
1 answer
177 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 ...
• 21
2 votes
1 answer
27 views

### How To Interpret PCA Points Labeled With Specific Data Dimensions

I've done some PCA on my own, and am familiar with the basic concepts of how PCA components are calculated and applied. However, I'm working on a research project and am confused as to how to ...
2 votes
1 answer
137 views

### Why can't we just use machine learning to select which model to use for a given model?

Suppose you have a classification problem, now what if I implement and train all classification models like logistic regression, KKN, naive Bayes, decision tree or random forest on the training data ...