The alternating direction method of multipliers (ADMM) is one of the most widely used first-order optimisation methods in the literature owing to its simplicity, flexibility and efficiency. Over the years, numerous efforts are made to improve the performance of the method, such as the inertial technique. By studying the geometric properties of ADMM, we discuss the limitations of current inertial accelerated ADMM and then present and analyze an adaptive acceleration scheme for the method. Numerical experiments on problems arising from image processing, statistics and machine learning demonstrate the advantages of the proposed acceleration approach.
Clarice Poon (University of Bath)
Jingwei Liang (University of Cambridge)
Related Events (a corresponding poster, oral, or spotlight)
2019 Poster: Trajectory of Alternating Direction Method of Multipliers and Adaptive Acceleration »
Tue Dec 10th 05:30 -- 07:30 PM Room East Exhibition Hall B + C