Line Search

Line search is a fundamental optimization technique used to find the optimal step size in iterative algorithms, aiming to accelerate convergence and improve solution quality. Current research focuses on enhancing existing methods like Armijo and backtracking line search, exploring adaptive step size adjustments, and extending the concept to higher-dimensional hyperplane searches. These advancements are improving the efficiency and robustness of optimization algorithms across diverse applications, including neural network training, camera calibration, and portfolio optimization, by reducing computational cost and eliminating the need for hyperparameter tuning. The development of more efficient and adaptable line search methods continues to be a significant area of research with broad implications for various fields.