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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27 views

Creating Dataset for Image Classification

I want to develop a CNN model to identify 24 hand signs in American Sign Language. I created a custom dataset that contains 3000 images for each hand sign i.e. 72000 images in the entire dataset. For ...
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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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1answer
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Are Q values estimated from a DQN different from a duelling DQN with the same number of layers and filters?

I am confused about the Q values of a duelling deep Q network (DQN). As far as I know, duelling DQNs have 2 outputs Advantage: how good it is to be in a particular state $s$ Value: the advantage of ...
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Possible approaches to dealing with unbalanced dataset and highly biased deep learning algorithm

I have an extremely unbalanced video dataset for a two class video classification problem.All my videos in my current video dataset is $40$ second long with $900p$ resolution.However the dataset is ...
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1answer
61 views

Is possible to train a robot or AI to prune fruit trees?

I live in a rural area where there is a growing necessity for people with knowledge to prune Pear trees, this process is crucial for the industry, but as people go to the big cities, this skill is ...
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5answers
87 views

Which classifier should I use for a dataset with one feature?

I have a labeled dataset composed of 3000 data. Its single feature is the price of the house and its label is the number of bedrooms. Which classifier would be a good choice to classify these data?
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1answer
25 views

What is it called in AI when a program is designed to make “x in the style of y”?

Simplified: What is it called in AI when a program is designed to make "x in the style of y;" when it trains off of two types of sources in order to make a thing from source one, informed by features ...
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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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1answer
225 views

What are some resources for coding some artificial intelligence techniques in the context of games?

I know the most basic rudimentary theory on AI, and I want to delve into actual practical coding with AI and machine learning. I already know a decent bit of coding in C++ and I'm learning Python ...
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25 views

Could zero-padding affect learning in a negative way?

I implemented an LSTM with Keras to perform word ordering task (given a syntactically unordered sentence, the goal is to label ...
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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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1answer
49 views

How can I handle overfitting in reinforcement learning problems?

So this is my current result (loss and score per episode) of my RL model in a simple two players game: I use DQN with CNN as a policy and target networks. I train my model using Adam optimizer and ...
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1answer
56 views

How can I use machine learning to predict properties (such as the area) of simple polygons?

Imagine a set of simple (non-self-intersecting) polygons given by the coordinate pairs of their vertices $[(x_1, y_1), (x_2, y_2), \dots,(x_n, y_n)]$. The polygons in the set have a different number ...
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What is the most efficient data type to store probabilities?

In ML we often have to store a huge amount of values ranging from 0 to 1, mostly being probabilities. The most common data structure to do so seems to be a floating point? Indeed, the range of ...
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1answer
43 views

After having selected the best model with cross-validation, for how long should I train it?

When using k-fold cross-validation in a deep learning problem, after you have computed your hyper-parameters, how do you decide how long to train your final model? My understanding is that, after the ...
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1answer
79 views

What does “off-the-shelf” mean?

I encountered the phrase/concept off-the-shelf CNN in this paper in which authors used off-the-shelf CNN representation, OverFeat, with simple classifiers to ...
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2answers
162 views

Why is creating AI that can code a hard task?

For people who have experience in the field, why is creating AI that has the ability to write programs (that are syntactically correct and useful) a hard task? What are the barriers/problems we have ...
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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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3answers
662 views

Why does the transformer do better than RNN and LSTM in long-range context dependencies?

I am reading the article How Transformers Work where the author writes Another problem with RNNs, and LSTMs, is that it’s hard to parallelize the work for processing sentences, since you have to ...
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10 views

How should I deal with multi-dimensional tensors for nodes in a graph convolution network?

How to work with GCN when the features of each node is not a 1D vector? For example, if the graph has N nodes and each node has features of the form $C \times D \times E$. Also, is there an open-...
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1answer
35 views

What is the theoretical basis for the use of Cross Validation set?

So let's follow this line of reasoning. We use a MLE estimator (implementation doesn't matter) and we have a train set. We assume that we have sampled training set from a Gaussian distribution $\...
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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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1answer
42 views

What are “proxy data sets” in machine learning?

The paper Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration uses the term "proxy data sets" in this way To develop DL ...
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2answers
93 views

Why do we need both the validation set and test set?

I know that this has been asked a hundred times before, however, I was not able to find a question (and an answer) which actually answered what I wanted to know, respectively, which explained it in a ...
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1answer
26 views

What is the difference between model and data distributions?

Is there any difference between the model distribution and data distribution, or are they the same?
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1answer
45 views

Do I need to denormalise results in linear regression?

I have learned so far how to linear regression with one or multiple features. So far, so good, everything seems to work fine, at least for my first simple examples. However, I now need to normalise ...
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0answers
32 views

Is maximum likelihood estimation meaningless for a dataset of only outliers?

From my understanding, maximum likelihood estimation chooses the set of parameters for the estimator that maximizes likelihood with the ground truth distribution. I always interpreted it as the ...
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5answers
61 views

How can artificial intelligence predict the next possible moves of the player?

When you play video games, sometimes there is an AI that attempts to predict what are you going to do. For example, in the Candy Crush game, if you finish the level and you still have moves ...
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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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1answer
28 views

What is the role of convex optimisation in AI systems?

Convex optimisation is defined as: I have seen a lot of talk about convex loss functions in Neural Networks and how we are optimising rewards or penalty in AI/ML systems. But I have never seen any ...
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1answer
37 views

Is the derivative of the loss wrt a single scalar parameter proportional to the loss?

I am wondering about the correlation between the loss and the derivative of the loss wrt a single scalar parameter, with the same sample. That means: considering a machine learning model with ...
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0answers
18 views

How can I implement a Facial Recognition algorithm in C++ from scratch, without using OpenCV?

I wanna implement an algorithm for Facial Recognition in C++ with the help of Viola-Jones, aka Adaboost, but without using OpenCV or any other similar library. I wanna do it all from scratch. Any tips?...
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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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8 views

How can I perform object detection by cutting the image into many pieces each containing one object?

Our task is to do a special object detection: In the traditional case, the neural network will output some rectangle bounding boxes. But in our case, the network should output many nearly-vertical ...
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Do I have to downsample the input and upsample the output of the neural network when implementing the NICE algorithm?

Consider that my input is an RGB image. The size of my image is $N\times N$. I'm trying to implement NICE algorithm presented by Dinh. The bijective function $f: \mathbb{R}^d \to \mathbb{R}^d$ maps $X$...
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0answers
16 views

What is the difference between training a model with RGB images and using only the color channels separately?

What is the difference between training a model with RGB images and using only the color channels separately (like only the red channel, green channel, etc.)? Would the model also learn patterns ...
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1answer
25 views

How are the weights retained for filters for a particular class in a CNN?

I am new to CNN. What I have learned so far about the filters is that when we are giving a training example to our model, our model updates the weights by gradient descent to minimize the loss ...
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0answers
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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0answers
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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0answers
28 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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1answer
30 views

How can I develop a reinforcement learning agent that plays memory cards game?

I am new to RL, and I am thinking of doing a little project. The goal of the project is to learn an agent play the memory game with cards. I already created the program for detecting the cards on the ...
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33 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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0answers
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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1answer
39 views

How should I deal with variable-length inputs for neural networks?

I am a very beginner in the field of AI. I am basically a Pharma Professional without much coding experience. I use GUI based tools for the neural network. I am trying to develop an ANN that receives ...
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1answer
63 views

Can an artificial intelligence be unbeatable at simple games?

There are (two-players, perfect information) combinatorial games for which, at any configuration of the game, a winning move (if there is one) can be quickly computed by a short program. This is the ...
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11 views

Suitable kernels for Gaussian processes

Consider a stochastic process $\{X_t \colon t \in T\}$ indexed by a set $T$. We assume for simplicty that $T \in \mathbb{R}^n$. We assume that for any choice of indexes $t_1, \dots, t_n$, the random ...
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0answers
53 views

Why is the loss associated with my neural network increasing?

I am currently learning neural networks. Using data from http://www.mariofrank.net/touchalytics/index.html, I am trying to predict "User ID" by training the neural network model shown below. However, ...
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1answer
47 views

Why MLP cannot approximate a closed shape function?

[TL;DR] I generated two classes Red and Blue on a 2D space. Red are points on Unit Circle and Blue are points on a Circle Ring with radius limits (3,4). I tried to train a Multi Layer Perceptron ...
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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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