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L15 Exploding and Vanishing Gradients by ANAMIKA DAS is a document available to read on EtoBox.

Lecture 15 discusses the challenges of exploding and vanishing gradients in RNNs, highlighting the difficulties in learning long-distance dependencies during training. It introduces techniques to mitigate these issues, including gradient clipping, input reversal, identity initialization, and the LSTM architecture, which is designed to maintain stable gradients and effectively remember information over time. The lecture emphasizes the importance of understanding the mechanics of backpropagation and the behav

Author

ANAMIKA DAS

Language

EN