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AAAI
2011
12 years 4 months ago
A Feasible Nonconvex Relaxation Approach to Feature Selection
Variable selection problems are typically addressed under a penalized optimization framework. Nonconvex penalties such as the minimax concave plus (MCP) and smoothly clipped absol...
Cuixia Gao, Naiyan Wang, Qi Yu, Zhihua Zhang
CVPR
2011
IEEE
12 years 8 months ago
A Non-convex Relaxation Approach to Sparse Dictionary Learning
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...
Jianping Shi, Xiang Ren, Jingdong Wang, Guang Dai,...
MP
2007
142views more  MP 2007»
13 years 4 months ago
Active-constraint variable ordering for faster feasibility of mixed integer linear programs
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...
Jagat Patel, John W. Chinneck
ICRA
2009
IEEE
161views Robotics» more  ICRA 2009»
13 years 11 months ago
Multi-vehicle path planning in dynamically changing environments
— 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...
ACML
2009
Springer
13 years 8 months ago
Max-margin Multiple-Instance Learning via Semidefinite Programming
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...
Yuhong Guo