9 citations · 10 across the 4 of their papers we have counts for
5 papers · 1 filter
Adaptive Preconditioned Gradient Descent with Energy
Hailiang Liu, Levon Nurbekyan, Xuping Tian +1
We propose an adaptive step size with an energy approach for a suitable class of preconditioned gradient descent methods. We focus on settings where the preconditioning is applied…
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…
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…
Data-driven optimal control of a SEIR model for COVID-19
Hailiang Liu, Xuping Tian
We present a data-driven optimal control approach which integrates the reported partial data with the epidemic dynamics for COVID-19. We use a basic Susceptible-Exposed-Infectious-…
AEGD: Adaptive Gradient Descent with Energy
Hailiang Liu, Xuping Tian
We propose AEGD, a new algorithm for first-order gradient-based optimization of non-convex objective functions, based on a dynamically updated energy variable. The method is shown…