Neural networks are learning algorithms that approximate the solution to a task by training with available data. However, it is usually unclear how exactly they accomplish this. Two young Basel physicists have now derived mathematical expressions that allow one to calculate the optimal solution without training a network. Their results not only give insight into how those learning algorithms work, but could also help to detect unknown phase transitions in physical systems in the future.
from News on Artificial Intelligence and Machine Learning https://ift.tt/GX6Q1tI
Home
machine-learning-ai-news
News on Artificial Intelligence and Machine Learning
A computational shortcut for neural networks
- Blogger Comment
- Facebook Comment
Subscribe to:
Post Comments
(
Atom
)
0 comments:
Post a Comment