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Results tagged with machine-learning
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For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.
1
vote
Accepted
What's done towards AI learning new ways of learning?
A few weeks ago, I've come across this paper Learning to learn by gradient descent by gradient descent by Marcin Andrychowicz, Misha Denil, Sergio Gomez, Matthew W. Hoffman, David Pfau, Tom Schaul, Br …
- 41.4k
1
vote
What is the role of convex optimisation in AI systems?
Is there any role of convex optimization in AI?
Yes, of course!
If so, in what algorithms or problem settings or systems?
The problem of finding the parameters of a support vector machine …
- 41.4k
1
vote
What are the differences in testing between traditional software and artificial intelligence?
Testing machine learning programs is quite different than testing traditional software.
The main reason why this is the case is quite simple, if you're familiar with machine learning.
ML programs are …
- 41.4k
10
votes
What is the "Hello World" problem of Reinforcement Learning?
MNIST (along with CIFAR) may be the "Hello World" of supervised learning for image classification, but it is definitely not the "Hello World" of all machine learning techniques, given that RL is also …
- 41.4k
2
votes
Why they use KL divergence in Natural gradient?
The KL divergence has slightly different interpretations depending on the context. The related Wikipedia article contains a section dedicated to these interpretations. Independently of the interpretat …
- 41.4k
2
votes
Accepted
What does "at inference time" on Tesla's cars mean?
"At inference time" means "when you perform inference". If "inference" is a synonym for "forward pass" (aka "forward propagation") (which is not always the case in ML), then "at inference time", again …
- 41.4k
33
votes
How can an AI train itself if no one is telling it if its answer is correct or wrong?
By "company A has a large human face database so that it can train its facial recognition program more efficiently" the article probably means that there is a training dataset $S$ of the form
$$
S = …
- 41.4k
6
votes
Accepted
When should we use algorithms like Adam as opposed to SGD?
Empirically, I observed that algorithms like Adam and RMSProp tended to give me a final higher performance (in my case, the accuracy) on (the validation dataset) with respect to SGD. However, I also o …
- 41.4k
2
votes
Why is dialogue a hard problem in natural language processing?
First of all, I am not very familiar with details of NLP and NLU systems and concepts, so I will provide an answer based on the slides entitled Natural language understanding in dialogue systems (2013 …
- 41.4k
1
vote
Accepted
If the normal equation works, why do we need gradient descent?
That normal equation is sometimes called the closed-form solution.
The short answer to your question is that the closed-form solution may be impractical or unavailable in certain cases or the iterativ …
- 41.4k
1
vote
Is pre-processing used in deep learning?
Yes, sure, data pre-processing is also done in deep learning. For example, we often normalize (or scale) the inputs to neural networks. If the inputs are images, we often resize them so that they all …
- 41.4k
1
vote
How to predict human future location?
Your problem is often called (in the literature) human mobility prediction. There has been some research in this area. Have a look at it on the web.
In general, you might want to use any statistical …
- 41.4k
2
votes
Can machine learning be used to pass the Turing test?
Jobst Landgrebe and Barry Smith, in the paper Making AI meaningful again (2019), argue that machine learning is not sufficient to build an AI that is able to fully (like humans) understand language. T …
- 41.4k
2
votes
How do I plot a matrix of ratings?
You're looking for a heatmap. Check out e.g. https://stackoverflow.com/q/33282368/3924118 (if you like Python more than the others). See also this documentation.
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3
votes
Accepted
Being confused of distribution notations in Deep Learning book
At page 130 of the same book, the author states that $\hat{p}_\text{data}$ is an empirical distribution defined by the training data. Similarly, at page 129, he states that $p_\text{data}$ is the true …
- 41.4k