Hessian-vector product approximation with finite difference method when the 2nd order derivative is unavailable. The closure should return a loss or an iterator with its first element as the loss.

Abstract: This article is concerned with the multiagent optimization problem. A distributed randomized gradient-free mirror descent (DRGFMD) method is developed by introducing a randomized ...

Struggling to understand how logistic regression works with gradient descent? This video breaks ... so you can truly grasp this core machine learning algorithm. Perfect for students and ...

The proposed algorithm is built on our previous framework of the iteratively preconditioned gradient-descent (IPG) algorithm. IPG utilized Richardson iteration to update a preconditioner matrix that ...