Yoshua Bengio
speaker
2,216 appearances
5 recordings
5 series
first heard Oct 2018
last heard 7 May
Yoshua Bengio’s voice in public audio — every appearance, attributed to the second.
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Appearances
where we're saying, this is an actual property of the world.
In the case of latent variables, it would be a hypothesized actual property of the world, and not just what a person would say, but that this is true.
Now, sometimes you don't know that it's true, but you can consider it as a latent variable.
What's a latent variable?
Oh, sorry, sorry, sorry.
This is probabilistic machine learning jargon.
So in probabilistic models, you try to capture the relationship, the probabilistic relationship between many random variables.
Here, the random variables are Boolean, something is true or something is false.
And the something could be any property of the world that can be expressed in natural language.
Now, in the data, what we have, once we've set up this pre-processing that I mentioned, is a bunch of statements that we know are true.
Like we know that somebody wrote those things.
And maybe we know more like where and what venue and so on.
And we know that, for example, that such and such theorems are true or that such program produced such output and such scientific data was observed.
So there's a bunch of random variables for which we know the answer.
It's true or it's false.
And for everything else, we don't know.
And so we call them latent because they're not observed, right?
Or sometimes people use the term hidden variables, right?
And what happens here is because the system is trying to learn the joint distribution, so how every variable is related to every other, not just pairwise, but any subset of
The system is trying to calculate the probability that they're all true or one is true given others.
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