7 citations · 17 across the 4 of their papers we have counts for
5 papers
Learning to Design Convex Relaxations for Nonconvex Optimization
Jinrun Liu, Bai Yan, Tengfei Liu +5
Convex relaxations make nonconvex optimization tractable by replacing hard nonconvex problems with convex surrogates that give valid bounds. Yet their design is still largely manua…
Automated Design of Metaheuristic Algorithms: A Survey
Qi Zhao, Qiqi Duan, Bai Yan +2
Metaheuristics have gained great success in academia and practice because their search logic can be applied to any problem with available solution representation, solution quality…
AutoOpt: A General Framework for Automatically Designing Metaheuristic Optimization Algorithms with Diverse Structures
Qi Zhao, Bai Yan, Taiwei Hu +4
Metaheuristics are widely recognized gradient-free solvers to hard problems that do not meet the rigorous mathematical assumptions of conventional solvers. The automated design of…
Student's t Distribution based Estimation of Distribution Algorithms for Derivative-free Global Optimization
Bin Liu, Shi Cheng, Yuhui Shi
In this paper, we are concerned with a branch of evolutionary algorithms termed estimation of distribution (EDA), which has been successfully used to tackle derivative-free global…
State Space Model based Trust Evaluation over Wireless Sensor Networks: An Iterative Particle Filter Approach
Bin Liu, Shi Cheng
In this paper we propose a state space modeling approach for trust evaluation in wireless sensor networks. In our state space trust model (SSTM), each sensor node is associated wit…