9 citations · 15 across the 8 of their papers we have counts for
4 papers · 1 filter
Anderson acceleration of gradient methods with energy for optimization problems
Hailiang Liu, Jia-Hao He, Xuping Tian
Anderson acceleration (AA) as an efficient technique for speeding up the convergence of fixed-point iterations may be designed for accelerating an optimization method. We propose a…
SGEM: stochastic gradient with energy and momentum
Hailiang Liu, Xuping Tian
In this paper, we propose SGEM, Stochastic Gradient with Energy and Momentum, to solve a large class of general non-convex stochastic optimization problems, based on the AEGD metho…
An Adaptive Gradient Method with Energy and Momentum
Hailiang Liu, Xuping Tian
We introduce a novel algorithm for gradient-based optimization of stochastic objective functions. The method may be seen as a variant of SGD with momentum equipped with an adaptive…
Dynamic behavior for a gradient algorithm with energy and momentum
Hailiang Liu, Xuping Tian
This paper investigates a novel gradient algorithm, AGEM, using both energy and momentum, for addressing general non-convex optimization problems. The solution properties of the AG…