Accelerated Non-Euclidean Steepest Descent Method for Convex Optimization
The proposed Hyper-Accelerated Steepest Descent (HASD) algorithm provides an iteration complexity improvement of up to O(d^(1-2/p)) over previous accelerated non-Euclidean steepest descent methods, where d is the problem dimension and p is the norm parameter.
