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1500 questions
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Training and inference for highly-context-sensitive information
What is the best way to train / do inference when the context matters highly as to what the inferred result should be?
For example in the image below all people are standing upright, but because of the perspective of the camera, their location…
g491
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Are neurons in layer $l$ only affected by neurons in the previous layer?
Are artificial neurons in layer $l$ only affected by those in layer $l-1$ (providing inputs) or are they also affected by neurons in layer $l$ (and maybe by neurons in other layers)?
George White
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How can we prove that an autoassociator network will continue to perform if we zero the diagonal elements of a weight matrix?
How can we prove that an auto-associator network will continue to perform if we zero the diagonal elements of a weight matrix that has been determined by the Hebb rule? In other words, suppose that the weight matrix is determined from $W = PP^T-…
estamos
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When exactly is a model considered over-parameterized?
When exactly is a model considered over-parameterized?
There are some recent researches in Deep Learning about the role of over-parameterization toward generalization, so it would be nice if I can know what exactly can be considered as such.
A…
Phúc Lê
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What is Statistical relational learning?
I have gone through the wikipedia explanation of SRL. But, it only confused me more:
Statistical relational learning (SRL) is a subdiscipline of artificial intelligence and machine learning that is concerned with domain models that exhibit both…
Dawny33
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Are most things generally discovered because they work empirically and later justified mathematically, or vice-versa?
In the original GloVe paper, the authors discuss group theory when coming up with the equation (4). Is it possible that the authors came up with this model, figured out it was good, and then later found out various group theory justifications that…
Damien
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How to make convnets aware what the image actually is, not what is depicted on it?
I've uploaded a picture to Wolfram's ImageIdentify of graffiti on the wall, but it recognized it as 'monocle'. Secondary guesses were 'primate', 'hominid', and 'person', so not even close to 'graffiti' or 'painting'.
Is it by design, or there are…
kenorb
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1 answer
Could AI kill the joy of competitive sports and games?
Lee Sedol, former world champion, and legendary Go player today announced his retirement with the quote "Even if I become the No. 1, there is an entity that cannot be defeated".
Is it possible that AIs could kill the joy of competitive games(Go,…
Vildemort
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Can CNNs be applied to non-image data, given that the convolution and pooling operations are mainly applied to imagery?
When using CNNs for non-image (times series) data prediction, what are some constraints or things to look out for as compared to image data?
To be more precise, I notice there are different types of layers in a CNN model, as described below, which…
nilsinelabore
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How does Wit.ai convert sentences into structured data?
The Wit.ai is a Siri-like voice interface which can can parse messages and predict the actions to perform.
Here is the demo site powered by Wit.ai.
How does it understand the spoken sentences and convert them into structured actionable data?…
kenorb
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5
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1 answer
Should I train different models for detecting subsets of objects?
Suppose we have $1000$ products that we want to detect. For each of these products, we have $500$ training images/annotations. Thus we have $500,000$ training images/associated annotations. If we want to train a good object detection algorithm to…
NebulousReveal
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Concrete example of latent variables and observables plugged into the Bayes' rule
In the context of the variational auto-encoder, can someone give me a concrete example of the application of the Bayes' rule
$$p_{\theta}(z|x)=\frac{p_{\theta}(x|z)p(z)}{p(x)}$$
for a given latent variable and observable?
I understand with VAE's…
user8714896
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Does MMD-VAE solve the problem of blurred images of vanilla VAEs?
I understand that with vanilla VAEs, there are a few reasons justifying the production of blurred out images. The InfoVAE paper describes the case when the decoder is flexible enough to ignore the latent attributes and generate an averaged out image…
Ananda
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How could decision tree learning algorithms cope with imbalanced classes?
Decision trees and random forests may or not be more suited to solve supervised learning problems with imbalanced labels (or classes) in datasets. For example, see the article Using Random Forest to Learn Imbalanced Data, this Stats SE question and…
jennifer ruurs
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What is the "semantic level"?
I am reading the paper Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction (2018) by Yunzhe Tao et al.
In this paper, they use several times the expression "semantic levels". Some examples:
HRHN can adaptively select…
MikelBa
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