Efficient Bilevel Optimization for Hyperparameter Learning in Data Science Applications

This work proposes an efficient and adaptive first-order method for solving bilevel optimization problems, with a focus on learning hyperparameters in data science applications such as image reconstruction, processing, and machine learning.