AdaDelta
Machine Learning
An extension of AdaGrad that adapts learning rates based on a moving window of gradient updates to prevent learning rate decay.
Detailed Explanation
AdaDelta is an optimization algorithm in machine learning that improves upon AdaGrad by adapting learning rates dynamically. It maintains a moving window of past gradients and updates, allowing for more consistent learning. This approach prevents the learning rate from diminishing too rapidly, enabling models to train efficiently over time without manual adjustments. It enhances convergence speed and stability in training neural networks.
Use Cases
- •AdaDelta optimizes neural networks by dynamically adjusting learning rates, ensuring faster convergence and improved stability during training.
Related Terms
Other terms in the Machine Learning category