Unanswered Questions
1,972 questions with no upvoted or accepted answers
14
votes
1answer
901 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
6answers
490 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
92 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
273 views
Can layers of deep neural networks be seen as Hopfield networks?
Hopfield networks are able to store a vector and retrieve it starting from a noisy version of it. They do so setting weights in order to minimize the energy function when all neurons are set equal to ...
9
votes
3answers
297 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
6k views
Which machine learning algorithm can be used to identify patterns in a dataset of the cache performance of a CPU?
I need a machine learning algorithm to identify patterns in a dataset (saved in a CSV file) that contains details of the cache performance of a CPU. More specifically, the dataset contains columns ...
8
votes
2answers
719 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
704 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
507 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
73 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
113 views
How do I compute the variance of the return of an evaluation policy using two behaviour policies?
Suppose there is an evaluation policy called $\pi_{e}$ and there are two behavior policies $\pi_{b1}$ and $\pi_{b2}$. I know that it is possible to estimate the return of policy $\pi_{e}$ through ...
6
votes
2answers
105 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
295 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
1answer
300 views
How come that the addition of features can decrease the performance of a neural network?
I have a Remaining Useful Life (RUL) prediction problem that I want to solve. When I added two or more features as inputs to my ANN, the accuracy of my ANN has been decreased. More precisely, I've ...
5
votes
1answer
71 views
Aren't all discrete convolutions (not just 2D) linear transforms?
The image above, a screenshot from this article, describes discrete 2D convolutions as linear transforms. The idea used, as far as I understand, is to represent the 2 dimensional $n$x$n$ input grid as ...
