AdaGrad
Machine Learning
An optimization algorithm that adapts the learning rate to the parameters, performing smaller updates for frequently occurring features and larger updates for infrequent ones.
Detailed Explanation
AdaGrad is an optimization algorithm used in machine learning that adjusts the learning rate for each parameter individually. It performs smaller updates on parameters associated with frequently occurring features and larger updates on infrequent features, helping to improve convergence, especially in sparse data scenarios. This adaptive approach enhances training efficiency and model performance.
Use Cases
- •AdaGrad helps train sparse models efficiently by adapting learning rates for each feature during neural network optimization.
Related Terms
Other terms in the Machine Learning category