This paper presents a novel distributed active set method for model predictive control of linear systems. The combines primal strategy with decentralized conjugate gradient to solve convex quadratic programs. An advantage the proposed compared existing algorithms is feasibility iterates. Numerical results show that can compete alternating direction multipliers in terms communication requirement...

This paper addresses the problem of object recognition given a set images as input (e.g., multiple camera sources and video frames). Convolutional neural network (CNN)-based frameworks do not exploit these sets effectively, processing pattern observed, capturing underlying feature distribution it does consider variance in set. To address this issue, we propose Grassmannian learning mutual subsp...