Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Most Popular

more tags
1500 questions
5
votes
2 answers

What is feature embedding in the context of convolutional neural networks?

What are feature embeddings in the context of convolutional neural networks? Is it related to bottleneck features or feature vectors?
Kaustubh
  • 51
  • 1
  • 4
5
votes
2 answers

Can translational invariance of CNNs be unwanted if object is likely in certain positions?

Various texts on using CNNs for object detection in images talk about how their translation invariance is a good thing. Which makes sense for tasks where the object could be anywhere in the image. Let's say detecting a kitten in household…
simplename
  • 151
  • 3
5
votes
3 answers

Does the model learn from the average of all the data points in the mini-batch?

I used the example at - https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/5_DataManagement/tensorflow_dataset_api.py - to create my own classification model. I used different data but the basic outline of datasets was used.…
Emile Engelbrecht
  • 51
  • 2
5
votes
1 answer

How to handle varying types and length of inputs in a feedforward neural network?

After learning the basics of neural networks and coding one working with the MNIST dataset, I wanted to go to the next step by making one which is able to play a game. I wanted to make it work on a game like slither.io. So, in order to be able to…
AntonKad
  • 53
  • 4
5
votes
1 answer

Why is breadth-first search only optimal when the cost solution is a non-decreasing function?

I am learning about searching strategies in AI and I was reading that breadth-first search is only optimal when the cost solution is a non-decreasing function? I am not really sure what this refers to since decreasing search cost should be our goal.…
xava
  • 433
  • 1
  • 4
  • 10
5
votes
2 answers

Is it possible to build an AI that learns humanity, morally?

It is a new era and people are trying to evolve more in science and technology. Artificial Intelligent is one of the ways to achieve this. We have seen lots of examples for AI sequences or a simple "communication AI" that are able to think by…
Scarlet62442
  • 53
  • 3
5
votes
1 answer

Over- and underestimations of the lowest and highest values in LSTM network

I'm training an LSTM network with multiple inputs and several LSTM layers in order to set up a time series gap filling procedure. The LSTM is trained bidirectionally with "tanh" activation on the outputs of the LSTM, and one Dense layer with…
Kristof
  • 61
  • 3
5
votes
1 answer

Regression on extreme values

I have a data set that looks like this: I would like to estimate a relationship between x-values and the corresponding 5% extreme y-values, something that might look like that : Do you have an idea of an algorithm that might help me for this ? I…
olafgrossebaf
  • 59
  • 2
5
votes
2 answers

Why use semi-gradient instead of full gradient in RL problems, when using function approximation?

Semi-gradient methods work well in reinforcement learning, but what is there a reason of not using the true gradient if it can be computed? I tried it on the cart pole problem with a deep Q-network and it performed much worse than traditional…
Nestor Sanchez
  • 51
  • 2
5
votes
1 answer

What is the significance of this Stanford University "Financial Market Time Series Prediction with RNN's" paper?

Researchers at Stanford University released, in 2012, the paper Financial Market Time Series Prediction with Recurrent Neural Networks. It goes on to discuss how they used echo state networks to predict things such as Google's stock prices. However,…
BleedObsidian
  • 51
  • 2
5
votes
1 answer

How can genetic programming be used in the context of auto-encoders?

I am trying to understand how genetic programming can be used in the context of auto-encoders. Currently, I am going through 2 papers Training Feedforward Neural Networks Using Genetic Algorithms (a classific one) Training Deep Autoencoder via…
Gabriele
  • 243
  • 1
  • 9
5
votes
1 answer

How can neural networks that extract many features be fooled by adversarial images?

I have been reading a bit about networks where deep layers able to deal with a bunch of features (be it edges, colours, whatever). I am wondering: how can possibly a network based on this 'specialised' layers be fooled by adversarial images?…
magnolia1
  • 51
  • 1
5
votes
4 answers

Use Machine/Deep Learning to Guess a String

I want to be able to input a block of text and then have it guess a string within a predefined range (i.e. a string that starts with three letters and ends with five numbers like "XXX12345", etc). Ideally, the string it will be guessing will be…
TreHoffman
  • 59
  • 5
5
votes
3 answers

What is the most time-consuming part of training deep networks?

Deep networks notoriously take a long time to train. What is the most time-consuming aspect of training them? Is it the matrix multiplications? Is it the forward pass? Is it some component of the backward pass?
echo
  • 713
  • 1
  • 6
  • 12
5
votes
1 answer

Several questions regarding the NEAT algorithm

I've recently read the paper Evolving Neural Networks through Augmenting Topologies which introduces NEAT. I am now trying to prototype it myself in JavaScript. However, I stumbled across a few questions I can't answer. What is the definition of…
Nigk
  • 63
  • 1
  • 6
1 2 3
…
99 100