Unanswered Questions
1,252 questions with no upvoted or accepted answers
13
votes
2answers
161 views
Are Modular Neural Networks more effective than large, monolithic networks at any tasks?
Modular/Multiple Neural networks (MNNs) revolve around training smaller, independent networks that can feed into each other or another higher network.
In principle, the hierarchical organization ...
12
votes
2answers
1k views
Input/output encoding for a neural network to learn a grid-based game
I am writing a simple toy game with the intent of training a deep neural network on top of it. The games rules are roughly the following:
The game has a board made up of hexagonal cells.
Both players ...
10
votes
1answer
538 views
Are Cellular Neural Networks one type of Neural Networks?
I am researching Cellular Neural Networks and have already read Chua's two articles (1988). In cellular neural networks, a cell is only in relation with its neighbors. So its is easy to use it for ...
10
votes
1answer
783 views
Intelligent vision and gestalt processing
Decades ago there were and are books in machine vision, which by implementing various information processing rules from gestalt psychology, got impressive results with little code or special hardware ...
10
votes
3answers
177 views
What are some tactics for recognizing artificially made media?
With the growing ability to cheaply create fake pictures, fake soundbites, and fake video there becomes an increasing problem with recognizing what is real and what isn't. Even now we see a number of ...
9
votes
2answers
723 views
What topologies are largely unexplored in machine learning?
Geometry and AI
Matrices, cubes, layers, stacks, and hierarchies are what we could accurately call topologies. Consider topology in this context the higher level geometrical design of a learning ...
9
votes
5answers
278 views
Can an AI be trained to generate the outline of a story?
I know that one of the recent fads right now is to train a neural network to generate screenplays and new episodes of e.g. the Friends or The Simpsons, and that's fine: it's interesting and might be ...
8
votes
1answer
166 views
Deep Networks and generalisation of Hopfield Networks
Hopfield Nets are able to store a vector and retrieve it starting from a noisy version of it. They do so setting weights in order to minimise the energy function when all neurons are set equal the ...
7
votes
1answer
100 views
Synapses automatically select it's neurons
I know the basics of Artificial Neural Networks. For instance; make dot product with the weights and every neuron from previous layer. Adjust the weight by error. And done, That is how I see neural ...
7
votes
5answers
4k views
Which machine learning algorithm can be used for pattern recognition?
I need a machine learning algorithm to identify any patterns in a CSV file, which contains details of a cache performance of a CPU workload. More specifically, the CSV file contains columns like ...
6
votes
2answers
487 views
How to create a good fitness function?
In genetic algorithms, a function called "fitness" (or "evaluation") function is used to determine the "fitness" of the chromosomes. Creating a good fitness function is one of the challenging tasks in ...
6
votes
1answer
383 views
Loss function for Hierarchical Multi-label classification
I am looking to try different loss functions for a hierarchical multi-label classification problem. So far, I have been training different models or submodels like multilayer perceptron ( MLP )branch ...
6
votes
2answers
196 views
Can some one help me understand this paragraph from Nvidia's progressive gan paper?
Furthermore, we observe that mode collapses traditionally
plaguing GANs tend to happen very quickly, over the course of a dozen minibatches. Commonly
they start when the discriminator overshoots, ...
6
votes
0answers
226 views
Can we use the recursive least squares as a learning algorithm to an ADALINE?
I'm new to neural network, I study electrical engineering, and i just started working with ADALINEs.
I use Matlab, and in their Documentation they cite :
However, here the LMS (least mean squares) ...
6
votes
2answers
73 views
How much can the addition of new features improve the performance?
How much can the addition of new features improve the performance of the model during the optimization process?
Let's say I have a total of 10 features. Suppose I start the optimisation process using ...
