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The researchers now have access to a vast amount of training and testing data.
A limiting factor in OFC-LD is the dynamics learning using local methods, which on the one hand is an important precondition for the availability of heteroscedastic variances but on the other hand suffers from the curse of dimensionality, in that the learner has to produce a vast amount of training data to cover the whole state-action space.
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Here, we feed the neural network vast amounts of training data, labeled by humans so that a neural network can essentially fact-check itself as it's learning.
Humans should be able to use devices in a way that does not demand vast amounts of training and specialization, needless to say, most of what it is on offer today in the areas of AmI and SmE fall short of this expectation.
The majority of PAL articles found (12/19) reported on Peer Teaching, with a vast amount of variation in teacher training being provided within, or as an extension of the implemented program [ 4, 17, 19- 26, 28, 28, 30, 31].
It is hoped that this report will initiate new collaborative efforts that harness the vast amount of knowledge embedded in disparate data sets and promote training of more multidisciplinary scientists better positioned in the science of omics integration (integromics).
The vast amount of discretion vested in NSA analysts is also demonstrated by the training and briefings given to them by the agency.
"They bring a vast amount of experience to the team and it was clear from our training sessions they are in great form and ready".
The students should be trained to assess and analyze the vast amount of information available online by inclusion of basic education in utilization of information and communication technology in current curriculum.
Web technologies for e-learning have been adopted to provide ubiquitous training and serve as structured repositories for the vast amount of laparoscopic video sources available.
The main advantage of co-training is the fact that we can use the vast amount of unlabeled data (pairs of microarrays for which we do not know if they are similar or not) to improve our classifiers.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com