124 citations · 153 across the 7 of their papers we have counts for
7 papers
Efficiently Tackling Million-Dimensional Multiobjective Problems: A Direction Sampling and Fine-Tuning Approach
Haokai Hong, Min Jiang, Qiuzhen Lin +1
We define very large-scale multiobjective optimization problems as optimizing multiple objectives (VLSMOPs) with more than 100,000 decision variables. These problems hold substanti…
An Evolutionary Multitasking Algorithm with Multiple Filtering for High-Dimensional Feature Selection
Lingjie Li, Manlin Xuan, Qiuzhen Lin +3
Recently, evolutionary multitasking (EMT) has been successfully used in the field of high-dimensional classification. However, the generation of multiple tasks in the existing EMT-…
A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective Optimization
Songbai Liu, Qiuzhen Lin, Jianqiang Li +1
Recent decades have witnessed great advancements in multiobjective evolutionary algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these progressively imp…
Balancing Exploration and Exploitation for Solving Large-scale Multiobjective Optimization via Attention Mechanism
Haokai Hong, Min Jiang, Liang Feng +2
Large-scale multiobjective optimization problems (LSMOPs) refer to optimization problems with multiple conflicting optimization objectives and hundreds or even thousands of decisio…
Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve Optimization
Songbai Liu, Qiuzhen Lin, Kay Chen Tan +1
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…
Review of Single-cell RNA-seq Data Clustering for Cell Type Identification and Characterization
Shixiong Zhang, Xiangtao Li, Qiuzhen Lin +1
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 manne…
Joint Quantization and Diffusion for Compressed Sensing Measurements of Natural Images
Leo Yu Zhang, Kwok-Wo Wong, Yushu Zhang +1
Recent research advances have revealed the computational secrecy of the compressed sensing (CS) paradigm. Perfect secrecy can also be achieved by normalizing the CS measurement vec…