Questions tagged [models]

For questions related to modelling external environment, functional models tuned through convergent methods such as artificial networks or fuzzy logic containers, loss models, semantic models, model-based reasoning, or other kinds of models used in AI research, development, or practice.

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23 views

Is there a complement to GPT/2/3 that can be trained using supervised learning methods?

This is a bit of a soft question, not sure if it's on topic, please let me know how I can improve it if it doesn't meet the criteria for the site. GPT models are unsupervised in nature and are (from ...
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1answer
51 views

What is the difference between parametric and non-parametric models?

A model can be classified as parametric or non-parametric. How are models classified as parametric and non-parametric models? What is the difference between the two approaches?
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18 views

Literature on computational modelling involving neuronal ensemblies

Straying from the current trends in deep learning, there is an, arguably, interesting idea of neuronal ensembles possibly providing an alternative to the current "layered feature detectors" ...
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1answer
59 views

What are some examples of functions that machine learning models compute?

My simple understanding of AI is that it is based on a mathematical model of a problem. If I understood correctly, the model is a polynomial equation and its weights are calculated by training the ...
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10 views

How to combine specific CNN models that work better at slightly different tasks?

I'm not sure how to describe this in the most accurate way but I'll give it a shot. I've developed a Inception-Resnet V2 model for detecting audio signals via spectrogram. It does a pretty good job ...
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2answers
64 views

How can I be sure that the final model, trained on all data, is correct?

The 'by the book' method of delivering final machine learning models is to include all data in the final training (including validation and test sets). To check robustness of my model I use randomly ...
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0answers
46 views

Is it good practice to save NLP Transformer based pre-trained models into file system in production environment

I have developed a multi label classifier using BERT. I'm leveraging Hugging Face Pytorch implementation for transformers. I have saved the pretrained model into the file directory in dev environment. ...
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1answer
31 views

Detect data in tables of roughly the same structure

I would like to train a model that serializes a table of nutrition facts into it's values. The tables can vary in form and colour, but always contain the same set of keys (e.g. carbs, fats). Examples ...
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49 views

What are the differences between backbones, frontends, models and architectures in applied deep learning?

Context I'm trying to dive into deep learning for tasks on images, and trying to figure out how to reuse some well-known structures* that have been published, mainly on github. ( *Here, structure can ...
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1answer
26 views

What are the main differences between a language model and a machine translation model?

What are the main differences between a language model and a machine translation model?
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1answer
37 views

Why is the hypothesis function $h_{\theta}(x)$ equivalent to $E[y | x; \theta]$ in generalised linear models?

Reading through the CS229 lecture notes on generalised linear models, I came across the idea that a linear regression problem can be modelled as a Gaussian distribution, which is a form of the ...
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22 views

Training a model for text document transformation?

I have a bunch of text documents, split into source documents and transformed documents. These text documents have multiple lines and are edited at specific locations, in a specific way. I make use ...
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2answers
38 views

Is it theoretically possible (or impossible) that principal component analysis worsens the performance of the model?

In case I had a prediction model and decided to add a PCA step prior to the model, is it theoretically possible/impossible that the number of output dimensions that is better for all tests may perform ...
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33 views

Is there a theory that captures the following ideas?

A big class of problems that are relevant in today's society are full of uncertainty and are also sometimes computationally intractable. Along our lives we come to realize that we are solving the same ...
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1answer
33 views

How to work on different models for a given problem?

I am working on the MNIST data on my own. The idea is to use different values for the number of hidden layers, number of nodes in a given layer, etc. How do you organize these things while you are ...
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38 views

What is the difference between FC and MLP in as used in PointNet?

I am trying to understand the PointNet network for dealing with point clouds and struggling with understanding the difference between FC and MLP: "FC is fully connected layer operating on each ...
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1answer
39 views

Neural networks with internal dynamics in the state-space form

Neural networks with feedback (Hopfield, Hamming, etc.) differ from ordinary neural networks (multilayer perceptrons, etc.), which turns them into a dynamic element with its own internal dynamics (if ...
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1answer
47 views

Isn't a simulation a great model for model-based reinforcement learning?

Most reinforcement learning agents are trained in simulated environments. The goal is to maximize performance in (often) the same environment, preferably with a minimum amount of interactions. Having ...
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1answer
38 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?
3
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1answer
88 views

What are pros and cons of Bi-LSTM as compared to LSTM?

What are the pros and cons of LSTM vs Bi-LSTM in language modelling? What was the need to introduce Bi-LSTM?
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2answers
439 views

What are the main differences between skip-gram and continuous bag of words?

The skip-gram and continuous bag of words (CBOW) are two different types of word2vec model. What are the main differences between them? What are the pros and cons of both methods?
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41 views

What are the advantages and disadvantages of extrinsic and perplexity model evaluation in NLP?

In the video Evaluation and Perplexity by Dan Jurafsky, the author talks about extrinsic and perplexity evaluation in the context of natural language processing (NLP). What are the advantages and ...
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1answer
49 views

What is the current state-of-the-art in unsupervised cross-lingual representation learning?

What is the current state-of-the-art in unsupervised cross-lingual representation learning?
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0answers
61 views

How get matrix of word embeddings in FastText of gensim?

I try get the matrix embedding of my model but I can't because although this code gives no error it never ends running. The code is: ...
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0answers
32 views

Using ML for Enemy Generation in Video Games

I am attempting to make a 2-D platformer game where the player traverses through an evil factory that is producing killer robots. The robots spawn at multiple specific locations in each level and ...
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1answer
26 views

YOLOv3 Model Structure: Why is filters = (classes + coords + 1) * num?

Here's a tutorial about doing custom training of YOLO (Darknet): https://medium.com/@manivannan_data/how-to-train-yolov3-to-detect-custom-objects-ccbcafeb13d2 The tutorial guides how to set values in ...
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0answers
22 views

What models will you suggest to use in Industrial Anomaly Detection and Predictive analysis on live streamed data?

I have been working on industrial data, that is fed live, I want to explore a few models which might suit for this the best. The data are KPI data from the manufacturing Industry.
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2answers
210 views

Will AI always depend on models and thus approximations?

In section 3 of the paper The Limits of Correctness (1985) Brian Cantwell Smith writes When you design and build a computer system, you first formulate a model of the problem you want it to solve, ...
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0answers
264 views

Why isn't there a model playing FPS like CoD or Battlefield already existing?

Assuming we had an unlimited time to train a model and a very powerful machine to use our model in real-time (hello quantum computer), I'd like to know why no one could achieve to build an AI able to ...
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0answers
21 views

What are the properties of a model that is well suited for for high performance real-time inference

What are general best practices or considerations in designing a model that is optimized for real-time inference?
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0answers
53 views

Correlating two models to predict the output of one that corresponds to an output of the other

I am currently working on a problem and now got stuck to implement one of it's steps. This is a simple attempt to explain what I am currently facing, which is something that I am aiming to implement ...
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0answers
15 views

What is a good model for regression problem with binary features and small data?

I am trying to predict the solution time for riddles in which matchsticks are combined into digits and operators. An example of a matchstick riddle is 4-2=8. The solution for this riddle would be ...
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0answers
44 views

Which deep neural networks are appropriate for the detection of bombs?

This is a follow-up question from my previous post here about explosion detection. I gathered a dataset of explosions. As I'm new to Deep Learning in Keras, I'm trying to see what architecture best ...
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1answer
45 views

Is the “symbol grounding” problem about building a physics engine?

In the past, most reinforcement learning agents were developed to solve existing domains. At first, a game was given, for example the snake game, and after a bit of training, the neural network was ...
2
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1answer
47 views

Will a .h5 file trained with Xception model work with Resnet50?

I have been running my 2013 server box since 2 weeks ago for training an AI model. I set up 30 epochs to run but since than it only ran 1 epoch as my PC config is super slow. But it generates 1 .h5 ...
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1answer
293 views

Is “dataset size” and “model size” same thing?

I mean what is determine my model size, connection amount between layers and neurons, or size of my dataset?
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2answers
2k views

What is the “thing” which is trained in AI model training

I am a newbie in the fantastic AI world, I have started my learning recently. After a while, my understanding is, we need to feed in tremendous data to train a or many models. Once the training is ...
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0answers
22 views

A NN based model of a Cattle for 'Heat Detection'

I am very new to AI/ML but have lot of interest in these. I am trying to understand how this gadget works. So far I have understood that a NN model of the cattle is generated by offline ...
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1answer
15 views

Should I model a problem with quantised output as classification or regression?

Say I have some data I am trying to learn, and I'm aware that the output is quantised in some way, e.g. I can get only get discrete values (0.1, 0.2, 0.3...0.9) in a finite range. Would you treat ...
4
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1answer
155 views

Can a computer conclude following philosophical concepts from a story?

Say you have to enter a story to a computer. Now the computer has to identify the philosophical concept on which the story is based, say: Was it a "self-fulfilling prophecy"? Was it an example of "...
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1answer
177 views

Is there a simple way of classifying images of size differing from the input of existing image classifiers?

Most image classifiers like Inception-v3 accept images of about size 299 x 299 x 3 as input. In this particular case, I cannot resize the image and lose resolution. Is there an easy solution of ...
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0answers
59 views

Designing state representation for board game

I am trying to write self-play RL (NN + MCTS http://web.stanford.edu/~surag/posts/alphazero.html) to "solve" a board game. However, I got stuck in designing boardgame same (input layer for NN). 1) ...
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0answers
70 views

How to use TensorFlow with hyperparameter tuning to optimize parameters for a robot simulator

I am trying to implement a DNN to optimize a set of 7 parameters that are used in a robot swarm simulator on the ARGoS platform. the program is a compiled C++ executable that reads the parameters from ...
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1answer
97 views

What approach should I take to model forecasting problem in machine learning?

I have a dataset which contains 4000k rows and 6 columns. The goal is to predict travel time demand of a taxi. I have read many articles regarding how to approach the problem. So, every writer tell ...
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0answers
22 views

Prediction of values with an unsupervised model

Given a set of historical data points, I am trying to predict a continuous output of which I have no historical record of, therefore the problem is of an unsupervised nature. I am wondering if there ...
3
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0answers
37 views

How to know when a Environment will yield a deterministic model

Given enough experiment data on time taken for objects to fall to earth from different heights, one can create various models that will accurately predict the time it will take for an object falling ...
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0answers
25 views

Encrypting and decrypting model files

I want my models to be accessible only by my programs. How do I encrypt and decrypt the model when I run inference on my model? Is there any existing technology that is widely used?
2
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1answer
297 views

After a model has been trained, how do I use it to address the real-world problems?

I understand the way we build and train a model, but all of the online courses I've found end with this. I can't find any course explaining the process of utilizing the trained model to address the ...
2
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1answer
22 views

Is it mostly the case to train with available models

I quite often find projects using pre-trained model and using them as a starting point for their new model that learns something novel from thier dataset or on-live learning process - e.g. using a ...
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1answer
88 views

How do I normalise/un-normalise data when loading a model?

I am following this TensorFlow JS tutorial where you load car data. The data looks like this: [{x:100, y:20}, {x:80, y:33}] X is the horsepower of a car, Y is ...