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1500 questions
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What is "conditioning" on a feature?
On page 98 of Jet Substructure at the Large Hadron Collider: A Review of Recent Advances in Theory and Machine Learning the author writes;
Redacted phase space: Studying the distribution of inputs and the
network performance after conditioning on…
Clumsy cat
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Is the Mask Needed for Masked Self-Attention During Inference with GPT-2
My understanding is that masked self-attention is necessary during training of GPT-2, as otherwise it would be able to directly see the correct next output at each iteration. My question is whether the attention mask is necessary, or even possible,…
D_s
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Why would the application of boosting prevent underfitting?
"Why would the application of boosting prevent underfitting?"
I read in some paper that applying boosting would prevent you from underfitting. Why is that?
Source:
https://www.cs.cornell.edu/courses/cs4780/2015fa/web/lecturenotes/lecturenote13.html
jennifer ruurs
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Context-based gap-fill face posture-mapper GAN
These images are handmade, not auto-generated like they will be in production. Apologies for inaccuracies in the graph overlay.
I am trying to build an AI like that displayed in the diagram: when given a training set of images with their…
Geza Kerecsenyi
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Isn't deep fake detection bound to fail?
Deep fakes are a growing concern: the ability to credibly alter a video may have great (negative) impacts on our society. It is so much of a concern, that the biggest tech companies launched a specific challenge:…
Lucas Morin
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How do I combine models trained on different data to increase classification accuracy?
I have two trained models. One is using a LinearSVC algorithm and is trained on numerical data from medical examination from patients with diabetic retinopathy. The second one is a neural network trained on images of retina scans from patients with…
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Why does a Lipschitz continuous discriminator in GANs assure statistical boundedness?
I have been reading the paper which introduced spectral normalization in GANs.
At some point the paper mentions the following:
The machine learning community has been pointing out recently that the
function space from which the discriminators are…
MattSt
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Why is the Jensen-Shannon divergence preferred over the KL divergence in measuring the performance of a generative network?
I have read articles on how Jensen-Shannon divergence is preferred over Kullback-Leibler in measuring how good a distribution mapping is learned in a generative network because of the fact that JS-divergence better measures distribution similarity…
ashenoy
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How to create an AI to solve a word search?
This at first sounds ridiculous. Of course there is an easy way to write a program to solve a wordsearch.
But what I would like to do is write a program that solves a word-search like a human.
That is, use or invent different strategies. e.g.…
zooby
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Are deep learning models more prone to overfitting than machine learning ones?
In my opinion, deep learning algorithms and models (that is, multi-layer neural networks) are more sensitive to overfitting than machine learning algorithms and models (such as the SVM, random forest, perceptron, Markov models, etc.). They are…
jennifer ruurs
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5
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What are methods human actors use to imitate robots?
Robot technology is usually thought from an engineering perspective. A human programmer writes a software this executed in a robot who is doing a task.
But what would happen, if the project is started with the opposite goal? The idea is, that the…
user11571
5
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3 answers
Given enough computational resources, do we currently have any algorithms which could achieve AI?
Hypothetically, assume that you have access to infinite computing power. Do we have designs for any brute-force algorithms that can find an AI capable of passing traditional tests (e.g. Turing, Chinese Room, MIST, etc.)?
Tim Atkinson
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Which part of "Perceptrons: An Introduction to Computational Geometry" tells that a perceptron cannot solve the XOR problem?
In the book "Perceptrons: An Introduction to Computational Geometry" by Minsky and Papert (1969), which part of this book tells that a single-layer perceptron could not solve the XOR problem?
I have been already scanned it, but I did not find the…
rimbaerl
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Do models train better if the labelling information is more specific (or dense)?
I'm working on a project where there is a limited dataset of videos (about 200). We want to train a model that can detect a single class in the videos. That class can be of multiple different types of shapes (thin wire, a huge area of the screen,…
NateW
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Is it possible to vectorise a CNN?
I am trying to write a CNN from scratch and am wondering if it is possible to vectorize the convolution step.
For example, if I had a dataset of 500 RGB images of size 32x32x3, and wanted the first convolutional layer to have 64 filters, how would I…
FeedMeInformation
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