Accelerating ADMM for Efficient Simulation and Optimization JUYONG ZHANG

It is interesting to remark that, while the undecidability of the Diophantine decision and similar problems can be proved by reducing the Turing machine (or universal register

Aware of the grave consequences of substance abuse, the United Nations system, including the World Health Organization, has been deeply involved in many aspects of prevention,

Let X be a n-dimensional compact Alexandrov space satisfying the Perel’man conjecture. Let X be a compact n-dimensional Alexan- drov space of curvature bounded from below by

Of course, we cannot say anything about weak quasi-Miura transfor- mations, since it is even not clear in which class of functions we have to look for its deformations, but we still

First introduced by Faddeev and Kashaev [7, 9], the quantum dilogarithm G b (x) and its variants S b (x) and g b (x) play a crucial role in the study of positive representations

This section first establishes the linear convergence rate of the ADMM in decentralized consensus optimization with strongly convex local objective functions (see Section III-A);

Wang, F., Xu, Z., Xu, H.K.: Convergence of Bregman alternating direction method with multipliers for nonconvex composite problems. Wang, X., Hong, M., Ma, S., Luo, Z.Q.:

A second scheme is associated with a decentered shock-capturing–type space discretization: the II scheme for the viscous linearized Euler–Poisson (LVEP) system (see section 3.3)..