Affine Model

Affine models, which represent data through piecewise linear transformations, are a cornerstone of various fields, including image registration and machine learning. Current research focuses on improving the efficiency and accuracy of affine model fitting, particularly through gradient descent and stochastic gradient descent algorithms, and exploring their application in complex scenarios like deep network analysis and transfer learning. These advancements are driving progress in areas such as medical image analysis, where fast and accurate registration is crucial, and improving the efficiency and theoretical understanding of machine learning models.