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Questions tagged [artificial-intelligence]

Artificial Intelligence (AI) is a topic in computer science that deals with the study / creation of intelligent machines. Use this tag for on-topic questions that have an AI aspect.

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Choosing an evaluation model for LLM for Question and Answering

I was learning the basic of LLM evaluation and the framework introduced in one of the short courses in Deep Learning AI was to generate samples of question and answer which act as the ground truth. ...
ShengXue's user avatar
1 vote
0 answers
100 views

Multidirectional propagation of biological neurons - could/should we recreate it e.g. with joint distribution neurons? [closed]

While ANNs are rather trained for unidirectional propagation, action potential propagation in biological neurons is symmetric e.g. ”it is not uncommon for axonal propagation of action potentials to ...
Jarek Duda's user avatar
4 votes
0 answers
80 views

What advantage do sinusoidal positional encodings have over binary positional encodings in transformer LLMs?

I've recently come across an article that discusses the reasons why large language models use sinusoidal functions to generate positional encodings — as per the famous paper Attention Is All You Need (...
Philip Voinea's user avatar
1 vote
1 answer
55 views

How can we implement pipelines using LLMs that can consider information from the internet in their responses?

Let us suppose that we are implementing a data processing pipeline based on LLMs and, in some part of the process, we need to search the internet for finding relevant information regarding some topic, ...
Zaratruta's user avatar
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0 answers
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How should I approach calculating sample size for number of raters required for a study?

I am proposing a study for evaluating reports generated by 3 human experts vs 3 different LLMs on a set of 10 situations. Basically, we're trying to whether the human experts are better or if the LLMs ...
user2615936's user avatar
2 votes
0 answers
23 views

Time Series Anomaly Detection with Class Variables

In ("univariate") time series anomaly detection, what techniques are there to incorporate class variables? For example, in accounting transactional data, we might care about anomalies in the ...
olives's user avatar
  • 31
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0 answers
12 views

Which model to use for word tokenization?

What type of model for word tokenization in a group of words is good?? I want to tokenize skills in a group. There are multiple groups, and I want to predict group number using a single skill. I have ...
bunny's user avatar
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1 vote
1 answer
94 views

Convolutional Neural Networks - Flattening with multiple feature maps

I have a very simple question about CNNs, which I unfortunately couldn't find an explanation for. Imagine we have a CNN, that has four filters (eg right, left, top, bottom edges) each of those outputs ...
Michal Gally's user avatar
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0 answers
26 views

Low MSE between the vectors but different distribution

I have two output tensors whose MSE is really small (0.04) but on checking the distribution of the tensors they are very different. I am using: torch.nn.MSE(output_tensor, input_tensor) = 0.04 I am ...
Bishwa Karki's user avatar
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0 answers
9 views

Error in accuracy test [duplicate]

This is an update from my previous question. I'll put my Model Development code here for your reference: ...
Amsyar Nifail's user avatar
2 votes
1 answer
261 views

How to address bias in AI Image Recognition Model: Oversampling, Undersampling, and Ensemble Techniques Not Working

I am currently working on an image recognition project using AI, but I am facing challenges with bias in my model's predictions. The model seems to be biased toward the majority classes in my dataset. ...
Amsyar Nifail's user avatar
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0 answers
40 views

How this is possible? Test loss is under train

I got this graph for my loss. As you can see the distance between the two graphs is so much! Can we say it shows bias is large and it's underfitting? Is this thing that I just said true or isn't true?...
argo's user avatar
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1 vote
0 answers
27 views

Dataset for Swimming with Heartbeat and Motion Data [closed]

I am currently working on my final project CS degree that involves analyzing swimming data, specifically focusing on both heartbeat and motion data. I am looking for a dataset that includes these two ...
Malak Qaadan's user avatar
1 vote
1 answer
64 views

Understanding bias-variance tradeoff decomposition

This is the formula : $E[(Y−f^2)]=σ^2 +Bias^2[f^]+Var[f^]$ What i cant understand , the expectation is over the training Set for a fixed $x_0$ , thus the $E(ϵ^2) =E(ϵ(x_0)^2) = ϵ(x_0)^2$ and not $...
Hocine Islam GUIA's user avatar
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0 answers
52 views

Should I fit(X_train, y_train) or fit(X,y) when using pipeline with gridsearchCV and cross_validate? (python)

I'm trying to make a pipeline that will do the following things: preprocessing, train one model (e.g. random forest), use GridSearchCV to tune hyperparameters (using nested cross validation to prevent ...
wick's user avatar
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2 votes
0 answers
57 views

Does a 1x1 convolutional Layer have a bias (Inception Modules)?

This question is regarding to the 1x1 convolutional layer idea from the paper "Going Deeper with Convolutions"(https://arxiv.org/abs/1409.4842) that describe the idea of so called inception ...
Quikel's user avatar
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-1 votes
1 answer
79 views

Machine learning and Artificial intelligence algorithms in identifying and classifying Airplane parts

Airplane parts and functions Can Machine Learning and Artificial intelligence Algorithms assist in identifying and classifying Airplane images parts?
Prashant Akerkar's user avatar
1 vote
0 answers
46 views

Machine learning and Natural Language Processing Algorithms for Indian Surnames Homophones [closed]

Homophones Indian Surnames List English last names Can machine learning, Natural Language Processing (NLP), Artificial intelligence assist in classifying , interpreting and specifying the differences ...
Prashant Akerkar's user avatar
4 votes
1 answer
110 views

Minimizing the expected loss (PRML)

In Bishop's PRML in section 1.5.2, the author introduces a loss function for classification, which is the expected loss, $$ E[L]=\sum_k \sum_j \int_{R_j} L_{kj}p(\textbf{x},C_k)d\text{x} $$ where Lkj ...
Bruce Murdock's user avatar
0 votes
0 answers
24 views

Should the mean of NN's predicted values match the mean of the original values?

I built a neural network model in R using the Keras' package and for some reason, the mean of the predicted values of the neural network doesn't match the mean of the original values. For every other ...
JerBear's user avatar
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1 vote
1 answer
87 views

entries into machine learning, deep learning, artificial intelligence for social scientists

As far as CrossValidated allows users to ask for reference, does anyone know (top-notch, authoritative) books, resources, or references about ML, DL, or AI for social scientists? If there are still &...
9 votes
1 answer
1k views

What is the roadmap to self-taught probability and statistics for artificial intelligence?

I am trying to self-teach probability and statistics for Machine Learning career. However I want to learn very well as doing research in AI is my goal. Which books should I use to learn probability, ...
1 vote
1 answer
216 views

Neural Networks - Can I Use Any Activation for the Output Layer?

I'm new to neural networks, and in almost everything I'm reading, the activation function recommended on the output layer follows a specific pattern: If the network does binary classification (1 ...
Krusty the Clown's user avatar
2 votes
2 answers
560 views

Reinforcement learning needs dataset?

Sorry for this dummy question based on the number of contents in the field that I am asking about but It seems that there are tons of texts and videos explaining what ...
john22's user avatar
  • 127
1 vote
1 answer
48 views

Can there be 3 initial weights for 2 inputs in a backpropagation network?

I am fairly new to machine learning and Neural Network. I was given a scenario where there is a 2-input single unit backpropagation Neural Network has 3 initial weights. The inputs are x and y. The ...
Tragend's user avatar
  • 11
5 votes
2 answers
598 views

Can I apply a confusion matrix to classification tasks outside of ML?

I would like to know if it's possible to use a confusion matrix to measure the performance of a classification tool outside the realm of ML or a statistical model. For example, if I had a small script ...
user370003's user avatar
1 vote
0 answers
63 views

Tic tac toe AI, general questions

Tl;dr - Very new to AIs and neural networks, trying to make tic tac toe. Trying to use a genetic algorithm that plays against other AIs, and the looser leaves. They seem to never learn even to not ...
Osmar's user avatar
  • 31
6 votes
3 answers
2k views

If dropout is going to remove neurons, why are those neurons built?

I know that Dropout will remove neurons randomly to reduce over-fitting. If Dropout is going to remove neurons, why are those neurons built? We could remove those neurons from the architecture. Why ...
Naren Babu R's user avatar
2 votes
2 answers
3k views

Using AI for human like mouse movement between two points

I am trying to use Neural Networks or ML to make my mouse cursor move as humanly as possible, I want to be able to generate a set of points which are needed for the mouse to move from point A (...
embedded_guy_989's user avatar
-2 votes
1 answer
36 views

Are Deep Learning and GPUs changing the game? [closed]

"Essentially, all models are wrong, but some are useful." --- Box, George E. P.; Norman R. Draper (1987). Empirical Model-Building and Response Surfaces, p. 424, Wiley. ISBN 0471810339. ...
Soumyadeep Ghosh's user avatar
1 vote
0 answers
26 views

CT-Scan Classification Overfitting Problem

I am currently trying to train pretrained convolutional neural networks trained on the imagenet dataset to be able to classify ct-scans into two classes. Viral Pneumonia and Normal. I am using K-fold ...
Simos Ps's user avatar
1 vote
1 answer
534 views

Splitting medical dataset by patient

I am currently trying to train a CNN model to classify CT-scans. I split the dataset using K-fold cross-validation and since the dataset I am using contains multiple slices per patient, I split the ...
Simos Ps's user avatar
1 vote
1 answer
473 views

how many neuron are there in my code?

I have the following snippet ...
ProcolHarum's user avatar
0 votes
2 answers
197 views

Which metric to use for language translation?

So I am using a pre-trained model to do the language translation Eg: Input = "Good morning" Output = "Bonjour" I would like to see if the ...
10sha25's user avatar
  • 63
4 votes
1 answer
976 views

Should I join train and validation sets for final NN model training? If yes, when to stop training the final model?

Normally we divide our dataset into 3 sets: train set, validation set, test set. We use train set to find optimal parameters (weights and biases of NN) and validation set to find optimal NN ...
loch_ness's user avatar
1 vote
0 answers
106 views

What is Max Pooling?

What is Max Pooling and why would I use it? There are a lot of questions about Max Pooling on Stack Exchange, but none of them explain what it is, why we want to use it, the problem it solves, or ...
Jacob Waters's user avatar
1 vote
1 answer
39 views

The added value of Machine Learning compared to traditional rule based methods

I would like to showcase the value of machine learning compared to traditional rule based (symbolic AI) methods. I would also like to break it down for Unsupervised, Supervised and Reinforcement ...
Vasilis Vasileiou's user avatar
0 votes
1 answer
35 views

Can a DQN learn when to avoid actions?

Imagine there is a problem with 3 possible outputs: A, B and C. But, only output ...
OK 400's user avatar
  • 145
6 votes
2 answers
353 views

What's the MAG of this underlying DAG?

I am studying causal discovery, with an interest on constraint-based algorithms like FCI (Fast Causal Inference). I want to know what's the Maximal Ancestral Graph (MAG) of this underlying DAG (...
Mingzhou Liu's user avatar
1 vote
1 answer
746 views

What is the difference between K-Nearest Neighbor and Adaptive K-Nearest Neighbor algoritms?

While studying KNN, I have come to see "Adaptive K-Nearest Neighbor algorithm" and I understand KNN but I wonder how "Adaptive K-Nearest Neighbor" work. I tried to find some ...
xabzakabecd's user avatar
  • 3,525
2 votes
1 answer
484 views

About "Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation"?

I am reading the Yoshua Bengio et al, Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. After read this paper, I wonder how to establish a GFlowNet if I don't know ...
mz sun's user avatar
  • 31
1 vote
1 answer
73 views

Question about the "sample" in "Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation"

I'm reading this paper recently. I'm confused about the "sample a distribution of trajectories" repeatedly mentioned in the article. I don't understand what this means. What is the sample ...
mz sun's user avatar
  • 31
0 votes
1 answer
18 views

Best grouping rows method with Multi-Armed Bandit

I have a dataframe , here above a sample : ...
user17241's user avatar
  • 249
1 vote
1 answer
2k views

Time series forecasting: classical methods vs. machine learning / artificial intelligence [closed]

Do you know papers that researched how accurate predictions are using time series or AI? I see more papers using VAR/VECM than XGBoost. Do you guys know why this?
waka 's user avatar
  • 31
2 votes
0 answers
40 views

Using Machine Learning to Create Periodic Paths

Question: How can I use Machine Learning to predict the right initial conditions $(P_0,V_0)$, given the angles of the triangular table, that will result in periodic paths in the triangular billiard ...
rb3652's user avatar
  • 141
1 vote
1 answer
889 views

Why applying Grad-CAM to the input layer is not common?

Grad-CAM is a popular tool that could be applied to the last convolutional layer to understand the inner structure of the deep neural network. It is general to apply Grad-CAM onto the last ...
user avatar
0 votes
0 answers
461 views

Which is the correct ROC metric type to use for Imbalanced Dataset (macro,micro, weighted) for multiclass classification?

I am working on a classification task where I have more than 350 classes with HUGE data imbalance. I want to check my model performance but I am confused which metric to use. So I Googled some ...
Deshwal's user avatar
  • 244
2 votes
1 answer
205 views

Objective functions of the flow network based generative model by Yoshua Bengio?

I am reading the Yoshua Bengio et al, Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. The objective function, Equation (11) and (12) are set for a given trajectory ...
Hans's user avatar
  • 1,015
2 votes
1 answer
77 views

Rationale for the objective function in a flow network based generative model by Yoshua Bengio?

I am reading the Yoshua Bengio et al, Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. It seems to me the objective of the paper is to generate the flow $F$ given ...
Hans's user avatar
  • 1,015
1 vote
1 answer
36 views

700,000 data points are true values while 1,300,000 data points are false values, is it an imbalanaced dataset? [closed]

I am trying to build a decision tree model and I have 700,000 true values while 1,300,000 data points are false values, in total, I have 2,000,000 data points including duplicates. I am wondering if ...
xabzakabecd's user avatar
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