Construct · 1 fields · 1 citations

vanishing gradient problem: a standalone construct

One name. One construct. A landmark on the map.

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vanishinggradient problem1 CONSTRUCTVanishing gradientBENGIO · MACHINE LEARNING

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Machine learning

error gradients shrink exponentially as they are propagated back through many time steps or layers, so long-range dependencies become very hard to learn by gradient descent.

In machine learning, vanishing gradient problem refers to error gradients shrink exponentially as they are propagated back through many time steps or layers, so long-range dependencies become very hard to learn by gradient descent. This meaning comes from Bengio (1994) in IEEE Transactions on Neural Networks.[1]

Unit
Recovery means
Measured by

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Nearby constructs

vanish2 fields · 2 citationsjingle · one word, two constructsdescent3 fields · 4 citationsjingle · one word, three constructserror4 fields · 8 citationsjingle · one word, four constructs

References

  1. Bengio, Y., Simard, P., & Frasconi, P. (1994). Learning long-term dependencies with gradient descent is difficult. IEEE Transactions on Neural Networks, 5(2), 157-166. https://doi.org/10.1109/72.279181

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