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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36 views

The results changed even though seed is fixed [closed]

I am using a reinforcement learning model for some tasks. and for the model, I am using stable_baselin3 and for the environment, I am using the gym. I made a small change in the environment and the ...
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1answer
24 views

Does a second-order fully-connected layer have any uses?

I was thinking about implementing second-order regression via a fully-connected layer, and I came up with this: $X$ is the input data, shaped $(features, batch\_number)$. $w0$ is the bias, shaped $(...
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26 views

How to predict the possible next moves of cars from given first moves?

I want to find the next moves of cars from the previous moves, but I could not figure out what should I use as an algorithm. Can you help me to find a way to solve this problem? I have a lot of car ...
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1answer
36 views

What does the complexity equation constitute exactly in “Why Should I Trust You?” LIME paper

I've recently been reading this paper on LIME, an algorithm to interpret ANY machine learning model. I encountered this equation (in red) on page 4 and have just been having a hard time deciphering ...
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1answer
24 views

Why do terms in the computation of state space size scale exponentially?

The image below is from a Berkeley AI course pdf I found. My question is, why do the terms accounting for the ghosts and pellets come in raised to the number of units? For example, there are two ...
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29 views

Are RNN a good approach to solve this type of problem?

I have a problem that can be optimized by taking five actions, and finally, after a series of steps to achieve a solution. The actions (1 to 5) are picked randomly. A time-step (epoch) is concluded ...
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22 views

Minimizing hard and soft margin objective functions in a one dimensional SVM

Given a one-dimensional training dataset with 3 points, 2 negative points at -1 and 1, and a positive point at 0 (as in the picture above): (a) What solution would minimize the linear Hard Margin SVM ...
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1answer
44 views

Is logic AI a complement to learning AI?

I want to know the relation between logic AI and learning AI. Logic AI here refers to the branch of AI that is based on mathematical logic. Learning AI refers to the branch of AI that is based on ...
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1answer
41 views

Which data representation of text as input for NLP Deep Learning models?

I have been given a data set with 30.000 text documents (each text file is rather small with respect to its length and consists in most cases of around 20 sentences), which are labelled with 0 or 1. ...
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30 views

Limit of momentum update equation

I am self-studying on optimization algorithm on https://d2l.ai/chapter_optimization/momentum.html and couldn't get my head around some derivation: Instead of the standard gradient descent update ...
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Deep learning and machine learning [duplicate]

If I was Given a set of large training examples (xi,yi), how can training a neural network (NN) via stochastic gradient descent differs from using regular gradient descent in terms of the mathematical ...
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29 views

Which machine learning algorithm can be used to identify patterns in a large file of numbers?

I'm new to machine learning and have many questions, but today I want to know if my case can be solved by machine learning, and if the answer is yes, I would like to know what to learn first and which ...
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Given embedding vector A and vector B, how to find top k embedding vectors such that they are similar to vector A and dissimilar to vector B

Which would be better approach for getting top k embedding vectors such that they are similar to embedding vector A and dissimilar to vector B. Approach 1: calculate ...
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1answer
48 views

Is there a way to use AI to compare thousands of files and detect the ones containing "unusual" content?

Is there a way to use python and AI to compare thousands of files and detect the ones containing "unusual" content? Those files are supposed to have "homogeneous" configuration ...
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1answer
41 views

Can anyone please explain TFLite quantization part found in Netron neural network viewer?

I was checking tflite file in Netron. There I found the quantization formula in Netron as below: quantization: 0.007709330413490534 * (q + 3) I know the ...
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2answers
48 views

How to make NN distinguish between two types of functions (data)?

I have a neural network which is trying to predict two types of functions in a noisy setting. The input is an array, and the output is also an array. The two types of functions I am trying to predict ...
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29 views

Could anyone please explain this sentence about training in parallel?

One way to reduce the computational complexity of hidden state recurrences is to connect a unit's hidden state to the prior unit's output rather than its hidden state. The resulting RNN has a lower ...
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12 views

Is there some algorithms to get rid of pulses of noise in a video?

At about 0:12, 0:19, 0:21, 0:22 and 0:23 into the video, there are lots of pulses of noise. Is there some algorithms to get rid of them automatically?
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Is categorical cross entropy better than binary cross entropy for imbalanced binary classification problems

I am training a NN model. The data is highly imbalanced (3% for positive labels), and I have not resampled more true classes in the training set. The model performs much better when categorical cross-...
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1answer
60 views

Generating automatic sports commentary (NLG)

I am trying to develop a "simple" announcer for sports segments that mainly consists of events like goals, fouls, substitutions, and many other events that could happen in many sports. The ...
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1answer
40 views

What is the relevance of the concept size to the time constraints in PAC learning?

My question is about the relevance of concept size to the polynomial-time/example constraints in efficient PAC-learning. To ask my question precisely I must first give some definitions. Definitions: ...
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20 views

a loss for binary step function data

I have some data with ground truth that looks like a binary step function, where part of it is 0 and part is one. An example for the GT can be like ...
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24 views

How do we give recommendations when users create/post content (like in YouTube)?

I've explored tools like amazon personalize, etc. for generating recommendations. It seems like amazon personalize is appropriate when all the content is with the company/a single entity. For example, ...
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24 views

Why is there a Hessian diagonal approximation? And when can we use it?

This topic has been introduced in "Pattern Recognition and Machine Learning, Bishop, 2006", section 5.4.1. I am a bit confused about this method and I have two questions. Why this method ...
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16 views

Model for predicting whether an event will or will not happen

I am not very learned in the realm of ai and coding, but want to try to learn! There's a specific type of model I'm looking for but don't know how to find. I want to see if ai can predict the chances ...
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32 views

How to teach Machine Learning Agent to destroy replicating objects in a puzzle game?

I have an unusual but very interesting problem. I have a game that is very similar to Toon Blast (a puzzle mobile game). It's based on a Match-2 mechanic in which you can destroy 2 or more connected ...
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33 views

What is the best machine learning algorithm for clustering dots based on coordinates $(x,y)$ with consideration of weight of the points?

I'm looking for a machine learning algorithm for clustering points based on their coordinates. Furthermore, I want to take into consideration the weights of each point. Suppose there is a weight in ...
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1answer
52 views

How to train an ML model to convert the given lyrics into a song by a particular singer?

I am interested in training a machine algorithm to convert the lyrics I give into a song by a particular singer. My language is non-English (south Indian) The songs are mostly monophonic (very few ...
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21 views

What model to train to restore MNIST test dataset

I came across this problem, and am not sure where to start. What model would work best for this problem and why? Imagine the digits in the test set of the MNIST dataset (http://yann.lecun.com/exdb/...
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XLMRoberta loss remains constant over iterations for TokenClassification task

I have created a simple XLMRoberta model for token classification. The task is to predict the quality of translation for each token/word. The data looks something like this, where the first sentence ...
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1answer
64 views

What does "at inference time" on Tesla's cars mean?

I've watched Tesla AI Day 2021 and there was a question Tesla staff tried to answer, but I did not quite understand the question (Note: quote taken from autogenerated subtitles, I do not hear ...
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10 views

How does the distribution of the parameters change in logistic regression?

I have my own data to train a logistic regression model (for a multi-class classification task), and I want to know how the distribution of weight parameters changes after each update with gradient ...
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19 views

Fine tuning BERT for token level classification

I want to try self-supervised and semi-supervised learning for my task, which relates to token-wise classification for the 2 sequences of sentences (source and translated text). The labels would be ...
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6 views

Predicting single floats based on set of 2 feature arrays each of 100 values

I am trying to predict audio to video desynchronization based on ser od two arrays of lenght 100 which consist of coresponding audio and video samples. The problem is that my labels are single floats (...
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33 views

Predict placement of an object in 3D space

I am trying to find a way to train a model to predict the correct placement of entities like a tree, dog and cat in a natural 3D environment. Any help regarding how I could use textual data to learn ...
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9 views

Is the average accuracy of each class (computed from the confusion matrix) equal to the accuracy calculated from cross-validation?

When I calculate the accuracy using cross-validation, it gives me a different accuracy than when I calculate using the confusion matrix. Why does it give a different accuracy? Is the accuracy ...
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20 views

Expectation-maximization calculation for example shown in Artificial intelligence A modern approach

I am reading learning Bayes net parameter values for hidden variables in Artificial intellegence A modern approach by Russel and Norvig. My questions on above text: Author mentioned that "...
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57 views

How can Siamese Neural Networks accept a variable number of inputs?

Traditionally, Siamese Neural Networks have two inputs. With some tweaking, you can get them to accept any number of inputs. What I don't understand is how to get them to accept variable numbers of ...
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31 views

Variational Inference: Approximate expected log likelihood via sampling

I'm working my way through a simple variational inference from scratch. For that, I assume that z denotes the probability of a coin showing ...
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1answer
68 views

What is the definition of a trace of a tensor?

Tensor is a multi-dimensional ordered collection of elements, which is used in deep learning to store and process data as well as intermediate steps. We are aware of the trace of a two-dimensional ...
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69 views

Which ML algorithm is the best for predict the next PRNG generated numbers?

I have a homework. The task is to decide, if the PRNG generated lottery is attackable/crackable or not. Details: Lottery: There is a lottery game where you have to choose 8 numbers between 1-20 for ...
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1answer
32 views

Non-sliding kernels for location-aware processing in Convolutional Neural Networks

My understanding of how CNN operates in image detection is through the use of kernels that slide through the image to detect features (edges and so on). So a single kernel could potentially be ...
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1answer
54 views

Can neural networks learn noise?

I'm interested in the following graphs. A neural network was trained to recognise digits from the MNIST dataset and then the labels were randomly shuffled and the following behaviour was observed. ...
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18 views

Does a complex problem need a complex model?

I ask in general if a complex problem needs a complex model, more concrete: The spread of corona in our society is a complex problem, which depends on several parameters (even parameters as education)....
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1answer
44 views

How the vector-space isomorphism between $\mathbb{R}^{m \times n}$ and $\mathbb{R}^{mn}$ guarantees reshaping matrices to vectors?

Consider the following paragraph from section 5.4 Gradients fo Matrices of the chapter Vector Calculus from the textbook titled Mathematics for Machine Learning by Marc Peter Deisenroth et al. Since ...
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17 views

What is remembering in Hopfield network?

Hopfield is a simple and traditional network. We feed into the network some patterns (Learning/Training). Actually, there is no training in Hopfield as the weight calculation is just adding up all the ...
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1answer
74 views

How do I use machine learning to create an optimization algorithm?

Let's say that I want to create an optimization algorithm, which is supposed to find an optimum value for a given objective function. Creating an optimization algorithm to explore through the search ...
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24 views

Encoding Image Priors into CNN

There's a core problem with all of ML which I haven't really seen made explicit: the issue is every model needs to have an assumption on the structure of the data you learn and this assumption needs ...
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70 views

Why is val accuracy 100% within 2 epochs and incorrectly predicting new images? (1,000 images per class when training)

My CNN tensorflow model reports 100% validation accuracy within 2 epochs. But it incorrectly predicts on single new images. (It is multiclass problem. I have 3 classes). How to resolve this? Can you ...
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13 views

How to find the accuracy of LDA model?

I am working on topic modeling using the latent Dirichlet allocation model. I have a dataset that contains tweets and topics corresponding to these tweets. In total, there are 65 different topics. I ...

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