attention
7
7.2
- noun
- /əˈtɛnʃən/
- Specialized
:
mecanismo de atención
- In machine learning, attention allows the model to increase focus on the most relevant data points.
- self-attention
- manipulation of self-attention
And so there's different schools of thought on training attention, for instance.
- And so there's different schools of thought on training attention, for instance.
Examples
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With attention in neural networks, unimportant details are downplayed while crucial inputs are emphasized.
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The attention mechanism assigns different weights to input features, highlighting the key information.
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And Ed did a lot of research on managing human attention and search.
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But at the moment, of course, all attention is focused on the pandemic.
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These assign a higher weight or increased attention to words that are more important.
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The Filter Theory suggests that attention to input is selective because only some messages were able to get through.
Academic text (2012) -
Through the World Bank and other mechanisms, we must devote more attention and resources to developing strong social safety nets.
Academic text (1998) -
As a result, academics directed their attention toward explaining the mechanisms that Arab states had developed to weather popular dissent.
Academic text (2011) -
Whereas Deng's economic reforms attracted worldwide attention, his political reforms deserved more credit than they have received.
Academic text (1998) -
His research addresses the development of attention, inhibition, working memory, and comprehension processes, especially among children diagnosed with ADHD.
Academic text (2011)
Compounds
- Specialized
11
3.6
A condition that makes it hard to pay attention and sometimes makes people very active or act without thinking
- Specialized
4
3.8
A condition often in children causing trouble paying attention, being very active and acting without thinking
1
3.6
Immediate care or action needed because a problem is serious and may get worse
How Focused
Surface Forms
Morphology
Etymology
Attention comes from Latin parts ad- 'to' and tendere 'to stretch', so it means 'stretching toward'. A useful image for computers is a model that 'stretches' its focus to the most useful words or parts of the input, which is exactly what the machine-learning attention tool does.