Unanswered Questions
1,684 questions with no upvoted or accepted answers
14
votes
1answer
876 views
Are information processing rules from Gestalt psychology still used in computer vision today?
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 ...
11
votes
3answers
978 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 ...
11
votes
6answers
429 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 ...
9
votes
1answer
86 views
Will parameter sweeping on one split of data followed by cross validation discover the right hyperparameters?
Let's call our dataset splits train/test/evaluate. We're in a situation where we require months of data so we prefer to use the evaluation dataset as infrequently as possible to avoid polluting our ...
9
votes
1answer
233 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 ...
9
votes
3answers
278 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, ...
9
votes
5answers
5k 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 ...
7
votes
0answers
239 views
Why would you implement the position-wise feed-forward network of the transformer with convolution layers?
The Transformer model introduced in "Attention is all you need" by Vaswani et al. incorporates a so-called position-wise feed-forward network (FFN):
In addition to attention sub-layers, each of the ...
7
votes
1answer
605 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 ...
7
votes
2answers
459 views
Reinforcement Learning with asynchronous feedback
I want suggestions on literature on Reinforcement Learning algorithms that perform well with asynchronous feedback from the environment. What I mean by asynchronous ...
6
votes
2answers
68 views
Why do very deep non resnet architectures perform worse compared to shallower ones for the same iteration? Shouldn't they just train slower?
My understanding of the vanishing gradient problem in deep networks is that as backprop progresses through the layers the gradients become small, and thus training progresses slower. I'm having a hard ...
6
votes
1answer
204 views
What's the advantage of log_softmax over softmax?
Previously I have learned that the softmax as the output layer coupled with the log-likelihood cost function (the same as the ...
6
votes
3answers
887 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
2answers
104 views
Why are documents kept separated when training a text classifier?
Most of bibliography consider text classification as the classification of documents. When using bag of words and bayesian classification, they usually use the statistic TFIDF, where TF normalizes the ...
6
votes
0answers
275 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) ...
