Analysis of Closed-Loop Inertial Gradient Dynamics

In this paper, we analyse the performance of the closed-loop Whiplash gradient descent algorithm [1] for L-smooth convex cost functions. Using numerical experiments, we study the algorithm's performance for convex cost functions, for different condition numbers. We analyse the convergence of the momentum sequence using symplectic integration and introduce the concept of relaxation sequences which analyses the non-classical character of the whiplash method. Under the additional assumption of invexity, we establish a momentum-driven adaptive convergence rate. Furthermore, we introduce an energy method for predicting the convergence rate with convex cost functions for closed-loop inertial gradient dynamics, using an integral anchored energy function and a novel lower bound asymptotic notation, by exploiting the bounded nature of the solutions. Using this, we establish a polynomial convergence rate for the whiplash inertial gradient system, for a family of scalar quadratic cost functions and an exponential rate for a quadratic scalar cost function.