A common problem in training deep neural networks, where the gradients tend to become extremely small, is known as the _______ problem.
- Overfitting
- Vanishing Gradient
- Exploding Gradient
- Underfitting
The vanishing gradient problem is a common issue in deep neural networks, especially in recurrent neural networks. It occurs when gradients become extremely small during training, making it challenging for the network to learn long-range dependencies. This can hinder the training process and result in poor performance.
Loading...
Related Quiz
- Considering the evolution of data privacy, which technology allows computation on encrypted data without decrypting it?
- Which algorithm is commonly used for predicting a continuous target variable?
- Which type of filtering is often used to reduce the amount of noise in an image?
- The process of organizing data to minimize redundancy and avoid undesirable characteristics like insertion, update, and deletion anomalies is called _______.
- In L2 regularization, the penalty is proportional to the _______ of the magnitude of the coefficients.