no code implementations • 8 Apr 2023 • Haokai Hong, Min Jiang, Qiuzhen Lin, Kay Chen Tan
To sample the most suitable evolutionary directions for different solutions, Thompson sampling is adopted for its effectiveness in recommending from a very large number of items within limited historical evaluations.
1 code implementation • 17 Dec 2022 • Lingjie Li, Manlin Xuan, Qiuzhen Lin, Min Jiang, Zhong Ming, Kay Chen Tan
Thus, this paper devises a new EMT algorithm for FS in high-dimensional classification, which first adopts different filtering methods to produce multiple tasks and then modifies a competitive swarm optimizer to efficiently solve these related tasks via knowledge transfer.
no code implementations • 23 Jun 2022 • Songbai Liu, Qiuzhen Lin, Jianqiang Li, Kay Chen Tan
This paper begins with a general taxonomy of scaling-up MOPs and learnable MOEAs, followed by an analysis of the challenges that these MOPs pose to traditional MOEAs.
no code implementations • 20 May 2022 • Haokai Hong, Min Jiang, Liang Feng, Qiuzhen Lin, Kay Chen Tan
However, these algorithms ignore the significance of tackling this issue from the perspective of decision variables, which makes the algorithm lack the ability to search from different dimensions and limits the performance of the algorithm.
1 code implementation • 15 Oct 2021 • Songbai Liu, Qiuzhen Lin, Kay Chen Tan, Qing Li
Evolutionary transfer multiobjective optimization (ETMO) has been becoming a hot research topic in the field of evolutionary computation, which is based on the fact that knowledge learning and transfer across the related optimization exercises can improve the efficiency of others.
no code implementations • 3 Jan 2020 • Shi-Xiong Zhang, Xiangtao Li, Qiuzhen Lin, Ka-Chun Wong
In recent years, the advances in single-cell RNA-seq techniques have enabled us to perform large-scale transcriptomic profiling at single-cell resolution in a high-throughput manner.