Cubic Regularization with Momentum for Nonconvex Optimization

9 Oct 2018Zhe WangYi ZhouYingbin LiangGuanghui Lan

Momentum is a popular technique to accelerate the convergence in practical training, and its impact on convergence guarantee has been well-studied for first-order algorithms. However, such a successful acceleration technique has not yet been proposed for second-order algorithms in nonconvex optimization.In this paper, we apply the momentum scheme to cubic regularized (CR) Newton's method and explore the potential for acceleration... (read more)

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