Variable selection problems are typically addressed under a penalized optimization framework. Nonconvex penalties such as the minimax concave plus (MCP) and smoothly clipped absol...
Dictionary learning is a challenging theme in computer vision. The basic goal is to learn a sparse representation from an overcomplete basis set. Most existing approaches employ a...
The selection of the branching variable can greatly affect the speed of the branch and bound solution of a mixed-integer or integer linear program. Traditional approaches to branc...
— In this paper, we propose a path planning method for nonholonomic multi-vehicle system in presence of moving obstacles. The objective is to find multiple fixed length paths f...
Ali Ahmadzadeh, Nader Motee, Ali Jadbabaie, George...
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...