Two-loop recursion is a method used in certain optimization algorithms to compute gradients or Hessians more efficiently by iterating over two different sets of values. This technique allows for the reuse of previously computed information, reducing the overall computational cost and memory requirements. It is particularly relevant in limited-memory methods like L-BFGS, where the goal is to minimize memory usage while maintaining convergence speed.
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