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Found 6 papers, 2 papers with code
Efficiently Tackling Million-Dimensional Multiobjective Problems: A Direction Sampling and Fine-Tuning Approach
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.
An Evolutionary Multitasking Algorithm with Multiple Filtering for High-Dimensional Feature Selection
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.
A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective Optimization
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.
Balancing Exploration and Exploitation for Solving Large-scale Multiobjective Optimization via Attention Mechanism
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.
Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve Optimization
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.
Review of Single-cell RNA-seq Data Clustering for Cell Type Identification and Characterization
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.
