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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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What’s more efficient in multihead attention: multiply QKV by W_i then split or linearly project QKV h times into dimensions d_k?

I’m looking to bridge two implementations of multihead attention. Approach 1: Multiply and Split Each of the queries, keys, and values is multiplied by a separate square weight matrix of size (...
marcocamilo's user avatar
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Advice on Handling Variable Input Sizes in a Neural Network Model for Predicting Football Match Outcomes

I am developing a machine learning model aimed at predicting football match outcomes based on past team performances. The model incorporates data from the last 10 home games for the home team and the ...
Drk's user avatar
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2 answers
41 views

What do we mean by "AI is correlated"?

From Wikipedia Causal AI is a technique in artificial intelligence that builds a causal model and can thereby make inferences using causality rather than just correlation. One practical use for ...
quanity's user avatar
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How To Resolve This Error

I have a cell here in google colab: And here is the error message: I don't really understand how to resolve this error. Could someone help me understand how to fix this? Any help is greatly ...
zed's user avatar
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1 answer
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Best way to classify chess pieces on a chessboard (on a square) [more details in the post]?

Ok, so I am working on a project which classifies chess pieces. The input is just a chess piece from a specific chess set on a white / black square on the chessboard. So it's just an image of a chess ...
vct12345's user avatar
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1 answer
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Proof that Temporal-Difference TD(1) is Equivalent to Widrow-Hoff

I'm reading Sutton's "Learning to Predict by the Methods of Temporal Differences" and I'm getting hung up on a derivation (p. 14). We are considering (observation-sequence, outcome) pairs. $[...
Matheo Xenakis's user avatar
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24 views

Segment a spectrogram into a series of images by (constant) beats per minute to train a Deep Neural Network

I have a .csv file with information about a soundtrack and it is divided into beats (per minute), which are ordered by row. As in: the index corresponds to each beat, and the columns have info about ...
Johnathan Smitherton's user avatar
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8 views

Why people always use l2 loss in Neural Tangent Kernel and other neural network theory?

What if we use l1 loss? I attempt to use NTK to get the convergence rate of a NN. Here is the original l2 loss version: https://rajatvd.github.io/NTK/. When I relpace it to l1 loss, I find the ...
orbin Lee's user avatar
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How are experienced and learned situations being stored?

Memorized events or experienced situations can really vary. The fact is that computer memory is a shadow of human intelligence. Therefore, humans could not disclosure human-beings' brain completely, ...
cell's user avatar
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Is it Possible to fit a sklearn model using a excel spreadsheet

hi i am new to this community, but i came up with this curiosity as i am having an embedded board to train a sklearn i have nvidia jetson tx2 with 256 nvidia cuda cores so inorder to take less load in ...
Ashok's user avatar
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Neural Network with Incorrect Calculation Better than Correct One

I have designed my own neural network and discovered an error. During backpropagation, instead of inserting the Z-values into the derivative of the activation function, I inserted the A-values. The ...
Apro9991's user avatar
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What machine learning algorithms are used in demand forecasting?

What are the most commonly used machine learning algorithms used in demand forecasting?
Mika's user avatar
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xLSTM parallel computation - mismatch in dimensions

In this recent paper, a new architecture is proposed, called xLSTM. I've implemented the sequential version in PyTorch, but it's slower than I would like, so I'm now implementing the parallel version ...
Quaere Verum's user avatar
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i have a combined pandas dataframe X_train with 22200 samples and 3 features. how can i model this

more info on how data is generated: A signal is passed to a concrete specimen while increasing the frequency of the signal conductance,susceptance of concrete is measured.The experiment is performed ...
Saketh's user avatar
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1 answer
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How to evaluate the KL divergence between two distributions that may require sampling?

The KL divergence between two distributions is: \begin{equation} \int \mathbf{p}(x;\theta_{1}) \; log \frac{\mathbf{p}(x;\theta_{1})}{\mathbf{p}(x;\theta_{2})} \nu(dx) \\ \end{equation} If the ...
xiaolingxiao's user avatar
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NN with user as a teacher

I have similar question to the following one. Could an AI be built to learn based of interaction with a human? What category of NN is the situation when the network learns from users feedback? The NN ...
Jacek's user avatar
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1 answer
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Does a random forest classifier always get 100% accuracy on its own training data?

Due to the way that decision trees work, do random forest classifiers always get 100% accuracy on their own training data? My random forest classifier got 100% accuracy on its own training data, so I'...
user1181399's user avatar
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2 answers
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One Softmax or two separate logistic regressions for the task of classifying pictures as a/b and c/d

Simply put, the question 11 in chapter 4 of Aurélien Géron's book "Hands-on Machine Learning" asks: Suppose you want to classify pictures as outdoor/indoor and daytime/nighttime. Should you ...
Dimitri's user avatar
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How to learn pattern of lower pixels rate in Pix2Pix GAN AND not background [closed]

I am working on a project to generate a forged image ( Almost a copy of it but not a copy completely!) from some source images. After some epochs, the generator model generates some white images. I ...
Ali AminiBagh's user avatar
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1 answer
32 views

Book(s) recomendation for Probability Theory Foundations

I am in the process of learning ML and AI. I've been taking some courses, and I now understand the foundations of the big picture of Machine Learning. I've been using Pattern Recognition and Machine ...
John Pinto's user avatar
2 votes
1 answer
32 views

How does Training and Validating work with Graph CNNs

I'm training a Graph Convolutional Neural Network to output embeddings for nodes that I eventually want to perform classification on. I am a little confused on how the training, validation, and ...
Kiran Manicka's user avatar
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30 views

Model suggestion for AI based scaling

We are exploring the idea of scaling elements within a UI container based on the given size. The container is represented by a json object, for example: ...
Sameed's user avatar
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How to Implement a Text-Based Question Answering System for PDF Documents using Machine Learning?

As a beginner in machine learning, I've completed a basic text classification project in university. Now, I'm eager to build a system that can answer specific questions from a large collection of PDF ...
Rudra Sarkar's user avatar
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16 views

1D CNN with Single vs. Two Channels for Number Image Recognition

I am taking images of numbers as input, in a convolutional neural network and building a model to predict the number. In particular, I am building a one dimensional convolutional neural network with ...
Ling Guo's user avatar
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Why same learning rate for slope and intercept not working in Linear regression?

I'm a new student in AI, currently learning linear regression. I used the california housing dataset for doing my experiments. My goal is to predict the 'population' column based on the 'total_rooms' ...
Jahid Chowdhury Choton's user avatar
1 vote
1 answer
64 views

why we use learnable positional encoding instead of Sinusoidal positional encoding

In the original paper of transformers they using positional encoding to capture the position of each word in the sentence and for calculate that it using sin and cos ,like shom in the image. In Bert ...
LAILA EL OUEDEGHYRY's user avatar
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2 answers
76 views

Which type of ML algorithm takes the least amount of time for training?

I am doing research on proteins. I have 17,000 *.CSV files on my hard disk. These files represent the chains of proteins. I want to use these ...
user366312's user avatar
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54 views

Drum sound classification using RNN issues - help needed

I am new to the field of machine learning, even tho I have solid background in semi-related fields (am control system engineer by trade) and as a hobby project I wanted to work a bit with sound ...
APasagic's user avatar
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0 answers
27 views

Do neural networks have a perception of space, regardless of dimensionality?

Suppose I have a model M which outputs a three-dimensional tensor of size 3x3x3. I have another model N which outputs a one-dimensional tensor of size 27. Train both models on some arbitrary objective ...
schmixi's user avatar
2 votes
1 answer
40 views

Could LLMs perform the autoregressive generation with probability vectors instead of choosing a discrete token every time?

As I understand it, GPT-style LLMs take a sequence of tokens as input and output a token probability vector. The first thing that happens to an input token is that it goes through the input embedding, ...
MelonDude's user avatar
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1 answer
33 views

Machine Learning Algorithm for identifying the factors contributing to academic performance of students

I have a dataset with several qualitative and quantitative attributes, including age, location (longitude, latitude), city, parent occupation, family size, GPA etc. My task is to find the attributes/...
Dawood Ahmad's user avatar
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2 answers
103 views

How the Q,K,V be calculated in multi-head attention

I want to understand the transformer architecture, so I start with self attention and I understand their mechanism, but when I pass to the multi-head attention I find some difficulties like how ...
LAILA EL OUEDEGHYRY's user avatar
2 votes
2 answers
439 views

Is it easier to use back-propagation or genetic algorithms to teach an artificial intelligence?

I am making a very simple neural network for a school project, and I would like to know what the best and easiest way to "teach" a neural network would be. From what I know, backpropagation ...
AlexanderB's user avatar
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0 answers
26 views

Distribution Based Mapping of Augmented (Noisy) Image and Clean image?

I have a task of training a Denoising Autoencoder which will be augmented MNIST dataset and and I have to reproduce the clean image, I have to use the ResBlocks in the Encoder(Conv Layer) as well as ...
Jivitesh's user avatar
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0 answers
11 views

Adding Feature in HGNN to Count Connections to Types of Nodes

So I'm making a HGNN currently in which the number of connections a node has to other nodes of a certain type matters. Its a social network, so I care about how many person-person connections a person ...
Daniel Eban's user avatar
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1 answer
29 views

Can/should a reward function depend on something other than state in a DQN

Question: Is it OK to have a reward function on a DQN or any RL algorithm that depends on variables other than the enviroment state? I'm asking because, so far I'm learning from tutorials, but I've ...
Oliver Mohr Bonometti's user avatar
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0 answers
20 views

Is it necessary that the number of samples of one class be balanced with other classes in a classification problem?

Consider a classification problem using machine learning techniques (e.g. malware detection). In such a problem, is it necessary that the number of samples from each class (in the mentioned example, ...
user16385455's user avatar
1 vote
0 answers
44 views

What is the best way to train a neural network with a variable number of inputs?

Suppose I have a neural network with 5 inputs: [A,B,C,D,E] There is only 1 output. The expected accuracy of the model should increase when all 5 inputs are ...
user18959's user avatar
0 votes
1 answer
54 views

What ML/DL algorithms for frequency spectrum pattern classifications?

I have a set of known frequency spectrum data for this set of chemical compounds. Then the unknown Y is the mixture of some of these compounds. The task is to determine what compounds are in this ...
David293836's user avatar
4 votes
2 answers
1k views

Why different noise in GAN generate different images?

I understand that noise $z$ serves as the input to the generator. Noise $z$ is essentially a vector of random numbers, typically from Gaussian distribution with chosen size of like $100$. However, I ...
user avatar
1 vote
0 answers
82 views

How do transformer-based architectures generate contextual embeddings?

How do transformer-based architectures like Roberta generate contextual embeddings? The articles I've read keep saying that transformer encoders work bidirectionally. Because of self-attention, they ...
user avatar
4 votes
3 answers
162 views

In the VAE, why is $z \sim \mathcal{N}(\mu, \sigma^2)$ equivalent to $z = \mu + \sigma \odot \epsilon$?

In the reparameterization trick of a Variational Autoencoder (VAE), instead of sampling noise $z$ from $z \sim \mathcal{N}(\mu, \sigma^2)$, we can use a different method: $z = \mu + \sigma \odot \...
user avatar
1 vote
1 answer
63 views

Fine tuning or just feature extraction or both using Roberta?

I'm reading a program that use the pre-trained Roberta model (roberta-base). The code first extracts word embeddings from each caption in the batch, using the last hidden state of the Roberta model. ...
user avatar
1 vote
1 answer
70 views

What kind of language in theory of computation language includes current LLMs?

We obviously know that Turing machines are enough for current LLMs training and inference. Are there languages behind the hierarchy that are enough for these processes (e.g. context-sensitive ...
sw.'s user avatar
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1 vote
1 answer
44 views

Using the definition of APAC learning and uniform convergence in practice

I am currently studying "Understanding Machine Learning from Theory to Practice" written by Shai Shalev-Shwartz and Shai Ben-David. I want to understand how i can use the Definitions and ...
MathAccount12's user avatar
0 votes
1 answer
118 views

What does it mean to "learn a distribution", and what does it contain?

When I was reading about discriminative vs generative models, I came across their definitions: Given a distribution of inputs $X$ and labels $Y:$ Discriminative models learn the conditional ...
user avatar
1 vote
1 answer
39 views

Beginner need help - identify data [closed]

I am learning Tensorflow, and I have a specific problem I want to solve. I want to identify on/off of my large power consumers at home. And calculate the power consumption elsewhere. I expect to input ...
povlhp's user avatar
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0 answers
15 views

Enhancing Soil Moisture Predictions Using Multimodal Data Integration in Agriculture

I am exploring an interdisciplinary research area involving multimodal data, focusing on agriculture. My study incorporates both visual and tabular data: crop and soil images from three distinct ...
Md Rakib's user avatar
4 votes
1 answer
138 views

Notation used in paper on Continuous Time Reinforcement Learning

I am working on implementing the learning shown in this paper: https://homes.cs.washington.edu/~todorov/courses/amath579/reading/Continuous.pdf In the paper, the authors devise a continuous time ...
Derick Diana's user avatar
2 votes
1 answer
67 views

Is it a requirement/recommendation to normalize my inputs into [0,1] range?

All features of my input dataset, which is going to be used for training a simple multi-layered neural network, are in range $[-1,+1]$ and the output of $NN$ is a single number again in range $[-1,+1]$...
Bikay's user avatar
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