LM optimization outperforms other methods in deep learning tasks but at high computational cost.
problem Finding efficient optimization methods for deep learning models.
method Comparing first-order (CG, SGD, LM, L-BFGS) and higher-order optimization functions.
result Levemberg-Marquardt (LM) optimization significantly improves convergence but at a high computational cost.