Questions tagged [machine-learning]

For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.

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124 views

possible to train some model to recognize trash?

I want to build a semi autonomous robot/machine that will clean up trash in cities. For this to be possible it needs to recognize 'trash'. As trash can be all sorts of things (think ciggaret buts, ...
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25 views

What is the most compressed audio that I can feed an AI?

The problem I currently have is that I want to train an AI to produce music, like music that contains voices etc... However, the problem is that with a WAV file, one second of audio can be up to 48,...
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9 views

Training Conditional DCGAN with GAN-CLS loss

I am trying to implement conditional GAN using GAN-CLS loss as described in paper: https://arxiv.org/abs/1605.05396 So, while training discriminator, I should I have three batches of data: [...
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25 views

Why do we use a delay when feeding our input data to the echo state network?

I'm new to working with neural networks and have recently began implementing neural networks for time series forecasting in some of my work. I've been particularly using Echo State Networks and have ...
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41 views

Is it possible to create a fair machine learning system?

I started thinking about the fairness of machine learning models recently. Wiki page for Fairness_(machine_learning) defines fairness as: In machine learning, a given algorithm is said to be fair, ...
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45 views

How do I set up rewards to account for unmanned aerial vehicle crashes?

I am working on a project to implement a collision avoidance algorithm on a real unmanned aerial vehicle (UAV). I'm interested in understanding the process to set up a negative reward to account for ...
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22 views

If the output of a model is a ridge function, what should the activation functions at all the nodes be?

I have the following assignment. I can't understand the b part of this question in my assignment. I have completed the 1st part and understand the maths behind it, but the 2nd part has me stumped. I ...
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24 views

Applications of polar decomposition in Machine Learning

Assume there exists a new and very efficient algorithm for calculating the polar decomposition of a matrix $A=UP$, where $U$ is a unitary matrix and $P$ is a positive-semidefinite Hermitian matrix. ...
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23 views

How estimate the minimum size of an autoencoder to overfit the training data?

Given e.g. $1$M vectors of $1000$ floating points each, where every point in vectors is sampled from a uniform distribution between $-1$ to $1$, how to estimate the minimum network size required ...
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1answer
39 views

Why does this multiplication of $Q$ and $K$ have a variance of $d_k$, in scaled dot product attention?

In scaled dot product attention, we scale our outputs by dividing the dot product by the square root of the dimensionality of the matrix: The reason why is stated that this constrains the ...
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15 views

3d representation of a regression with two independent variables one of them is categorical and another is continuous

I have hopefully a fundamental question of Do I understand things right. (Thank you in advance and sorry for my English which might be not so good) 1-Preambula 1: I know that if we have 2 independent ...
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43 views

MNIST Classification code performing with 88%-90% whereas other codes online perform 95% on first epoch

I have been trying to write code to implement plain neural net without convolution from scratch. I took some help online here and added my code to my github account. I don't understand why the ...
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16 views

What if the rewards induced by an environment are related to the policy too?

Assume we have a policy $\pi_{\theta}$ in a classic reinforcement learning setting, and a reward function $R^{\pi}(s,a)$ that changes as long as $\pi$ changes i.e. not only is it predefined by the ...
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26 views

Automating browser actions using AI

I am at a very initial stage of my research so I will try to describe what I am trying to achieve: I want to create an AI model which learns how to navigate the browser's component like clicking or ...
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13 views

How can I design a system that suggests physical exercises to a person while keeping into account the fatigue?

I want to create an exercise suggester. Each day either has a routine or is a rest day. A routine has 4 slots. For each slot we select an exercise. We constrain the legal exercises, only do upper-body ...
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26 views

How do I approach this problem?

Let's say I have a dataset with multiple types of multiple ingredients (salt1,salt2, etc). Each n-th variation of each ingredient vs flavor may be represented by an n×k matrix that where an ingredient ...
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1answer
24 views

What is the meaning of “easy negatives” in the context of machine learning?

What does the term "easy negatives" exactly mean in the context of machine learning for a classification problem or any problem in general? From a quick google search, I think it means just negative ...
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7 views

Using AI to find the correct set of object/numbers based on previous data

There are 11 objects of which 4 are "Bad" objects. So there are 7 "Good" objects. You have to choose as many Good objects before proceeding to another set of objects of a different sequence. How ...
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30 views

How can I approximate a function that determines the priority of objects?

I am facing the following supervised learning problem: An object is fully characterized by its position in $R^n$. There are $m$ objects. There are fully observable (i.e. their positions are always ...
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15 views

Are there any novel quantum machine learning algorithms that are fundamentally different from “classical” ones?

Generally, if one googles "quantum machine learning" or anything similar the general gist of the results is that quantum computing will greatly speed up the learning process of our "classical" machine ...
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38 views

What is the relationship between PAC learning and classic parameter estimation theorems?

What are the differences and similarities between PAC learning and classic parameter estimation theorems (e.g. consistency results when estimating parameters, e.g. with MLE)?
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6 views

How does optical computing work and deal with nonlinearity?

This article states that: One of the algorithms that photonics is very good at implementing is matrix multiplication But how are parameters stored and updated(in backpropagation)? One more ...
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36 views

Why is the number of neurons used in various neural networks power of 2?

I have noticed that almost all tutorials take the number of neurons as a power of 2. Is there any proper mathematical and well-proven reason for that? If you sometimes change it to some other odd ...
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1answer
50 views

Finding patterns in binary files using deep learning

I am a newbie in deep learning and wanted to know if the problem I have at hand is a suitable fit for deep learning algorithms. I have thousands of fragments each of about 1000 bytes size (i.e. ...
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1answer
38 views

Machine learning to find coordinate in image

I am trying to figure out how to approach this. Given training data of images and the pixel coordinates of the centre of an object in that image, would it be possible to predict the pixel coordinates ...
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43 views

Why does the growth function need to be polynomial in order for the learning algorithm to be consistent?

Could someone please explain to me why in VC theory, specifically, when calculating the VC dimension, the growth function needs to be polynomial in order for the learning algorithm to be consistent? ...
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19 views

To perform a white box adversarial attack, would the use of a numerical gradient suffice?

I am trying to perform a white box attack on a model. Would it be possible to simply use the numerical gradient of the output wrt input directly rather than computing each subgradient of the network ...
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7 views

How do I format task features with a one-hot task identification vector to ensure separate weight matrices for each task in multi-task RL?

I am on Lecture 2 of Stanford CS330 Multi-Task and Meta-learning, and on slide 10, the professor describes using a one-hot input vector to represent the task, and she also explained that there would ...
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18 views

Why does the result when restoring a saved DDPG model differ significantly from the result when saving it?

I save the trained model after a certain number of episodes with the special save() function of the DDPG class (the network is saved when the reward reaches zero), but when I restore the model again ...
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10 views

Feature extraction for exponentially damped signals

I am looking into exponentially damped signals where it is a stationary signal (after implementing the Adfuller statistical test) and I would like to look into how can I extract meaningful features ...
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20 views

How I can identify holes in a 3D CAD file?

How I can identify holes in a 3D CAD file? I want to identify different types of holes, counterbored or countersunk holes. My program lets me extract, for example, the faces and adjacency of the ...
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40 views

Where can I get exercises and problems to implement machine learning models and algorithms?

I'm an intermediate machine learning student and want to get more detailed and specific practical intuition about artificial intelligence. I have made a couple of searches over the well-observed ...
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10 views

What are the current research trends in recognizing narrative similarity?

I am currently working on a term paper on the topic of Narrative Similarity, based on Loizos Michael's work "Similarity of Narratives". I am trying to find the latest trends within this field of study ...
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9 views

How do I decide which norm to use for placing a constraint on my adversarial perturbation?

I am performing an adversarial machine learning attack on a neural network for network traffic classification. For adding adversarial perturbations in features such as packet interarrival times and ...
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20 views

How do we minimize loss for a single neuron with a feedback?

Suppose we had a series of single-dimensional data points $X = \{x_1, x_2, \dots, x_n \}$, where $n$ is the number of data points and there corresponding output values $T = \{t_1, t_2, \dots, t_n \}$. ...
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29 views

Are PreLU and Leaky ReLU better than ReLU in the case of noisy labels?

Let's assume I want to build a semantic segmentation algorithm, based on Multires-UNET. My GT-masks are messy and generated by a GAN, but they are getting better and better over time. The goal is ...
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34 views

What are the pros and cons of deep learning and machine learning to develop a trading system?

As I want to start coding a new Trading AI in this year (first based on Python and later maybe in C++) I stumbled over the following question: Today, I would like to make a pro/contra list with you ...
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14 views

How to output a filter of equal size to the original image in Fully Convolutional Neural networks

I'm trying to perform a segmentation task on images of multiple sizes using fully convolutional neural networks. Currently, I'm using efficientnet as a feature extractor, and adding a deconvolution/...
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26 views

Human Aggression Detection Community, Competition and dataset

I'm looking for a community or competition website related to human aggression detection using Deep Learning in a video. Also, I'm looking for a dataset of human aggression activities. Any ...
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16 views

Multiple-dimension scaling (MDS) objective for MDS and PCA

The following is the MDS Objective. Let's think of a senario where I apply MDS with/from the solution I obtained from PCA. Then I calculate the objective function on the initial PCA solution ...
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27 views

Which activation functions can lead to the vanishing gradient problem?

From this video tutorial Vanishing Gradient Tutorial, the sigmoid function and the hyperbolic tangent can produce the vanishing gradient problem. What other activation functions can lead to the ...
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38 views

Neural Network Results always the same

I have a GRU model which has 12 features as inputs and I'm trying to predict output power. I really do not understand though whether I choose 1 layer or 5 layers 50 neurons or 512 neuron 10 epochs ...
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0answers
17 views

What algorithm to use for finding artists/bands in text and differentiating between artists that share the same name

Here's the data I have: Text from articles from various music blogs & music news sites (title, summary, full content, and sometimes tags). I used a couple different NLP/NER tools (nltk, ...
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1answer
40 views

Understaning Bayesian Optimisation graph

I came across the concept of Bayesian Occam Razor in the book Machine Learning: a Probabilistic Perspective. According to the book: Another way to understand the Bayesian Occam’s razor effect is ...
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41 views

Which model should I choose to maximise reward of having chosen two numbers from a list?

I am looking for a technique to train a machine learning model to choose two items from a list. So, given a list $x=[x_1, x_2, x_3, x_4, \dots, x_n]$, the model needs to choose two elements $(x_i, ...
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1answer
34 views

Pros and Cons of Seq2Seq vs Bidirectional RNN

It seems to me that Seq2Seq models and Bidirectional RNNs try to do the same thing. Is that true? Also, when would you recommend one setup over another? Thanks!
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32 views

How can I normalize gamestates in order to use with a machine learning library?

I have currently collected 150000 gamestates from playing a Monte Carlo Tree Search AI player against a basic rule based AI at the game of Castle. The information captured represents the information ...
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1answer
38 views

How is the probability transition matrix populated in the Markov process (chain) for a board game?

Following on from my other (answered) question: With regards to the Markov process (chain), if an environment is a board game and its states are the various position the game pieces may be in, how ...
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29 views

Where can I find people solving this smoothing, filtering, temporal learning problem?

Consider a prediction problem for example. This is a loss function (negative log likelihood) that I am roughly talking about: \begin{align*} J_{\text{train}} &= -\sum_t \log L\left(\theta_t, ...
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119 views

What's the difference in using multiple convolutional layers and no pooling versus using a single convolutional layer and a single max pooling layer?

I'm currently working on a college project in which I'm designing a Deep Q-Network that takes images/frames as an input. I've been searching online to see how other people have designed their ...

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