4 papers
Towards Scalable Semidefinite Programming: Optimal Metric ADMM with A Worst-case Performance Guarantee
Yifan Ran, Stefan Vlaski, Wei Dai
Despite the numerous uses of semidefinite programming (SDP) and its universal solvability via interior point methods (IPMs), it is rarely applied to practical large-scale problems.…
Equilibrate Parametrization: Optimal Metric Selection with Provable One-iteration Convergence for -minimization
Yifan Ran
Incorporating a non-Euclidean variable metric to first-order algorithms is known to bring enhancement. However, due to the lack of an optimal choice, such an enhancement appears si…
General Optimal Step-size for ADMM-type Algorithms: Domain Parametrization and Optimal Rates
Yifan Ran
In this work, we solve a 49-year open problem, the general optimal step-size for ADMM-type algorithms. For a convex program: , $\text{s.t.}\, {A}{…
A Generic Closed-form Optimal Step-size for ADMM
Yifan Ran, Wei Dai
In this work, we present a generic step-size choice for the ADMM type proximal algorithms. It admits a closed-form expression and is theoretically optimal with respect to a worst-c…