Robot Kinematics
Machine Learning
An adaptive learning rate optimization algorithm that divides the learning rate by an exponentially decaying average of squared gradients.
Detailed Explanation
RMSprop is an optimization algorithm used in machine learning to improve training efficiency. It adjusts the learning rate for each parameter individually by dividing the initial learning rate by an exponentially decaying average of recent squared gradients. This helps stabilize training, especially in non-convex problems, by preventing the learning rate from becoming too large or too small, leading to faster convergence.
Use Cases
- •Optimizing neural network training for non-convex functions to ensure faster convergence and stable updates.
Related Terms
Other terms in the Machine Learning category