Accelerated differential inclusion for convex optimization

This paper introduces a second-order differential inclusion for unconstrained convex optimization. In continuous level, solution existence in proper sense is obtained and exponential decay of novel Lyapunov function along with the trajectory derived as well. Then discrete based on numerical discretizations model, two inexact proximal point algorithms are proposed, some new convergence rates established via function.