3 citations · 3 across the 9 of their papers we have counts for
8 papers · 1 filter
AutoPSO: A Meta-framework for Automated Particle Swarm Optimization
Xinmeng Yu, Jiaxin Gao, Jianguo Zhang +2
Particle swarm optimization (PSO) is a widely used metaheuristic, prized for its simplicity and small parameter set. Although decades of research have produced numerous PSO variant…
EvoGM: Learning to Merge LLMs via Evolutionary Generative Optimization
Tao Jiang, Xinmeng Yu, Chenhao Yi +5
Evolutionary model merging provides a powerful framework for the automated, training-free composition of LLMs through parameter-space search. However, existing methods predominantl…
A Multi-objective Evolutionary Algorithm Based on Bi-population with Uniform Sampling for Neural Architecture Search
Yu Xue, Pengcheng Jiang, Chenchen Zhu +4
Neural architecture search (NAS) automates neural network design, improving efficiency over manual approaches. However, efficiently discovering high-performance neural network arch…
Unleashing the Potential of Differential Evolution through Individual-Level Strategy Diversity
Chenchen Feng, Minyang Chen, Zhuozhao Li +1
Since Differential Evolution (DE) is sensitive to strategy choice, most existing variants pursue performance through adaptive mechanisms or intricate designs. While these approache…
TensorNEAT: A GPU-accelerated Library for NeuroEvolution of Augmenting Topologies
Lishuang Wang, Mengfei Zhao, Enyu Liu +2
The NeuroEvolution of Augmenting Topologies (NEAT) algorithm has received considerable recognition in the field of neuroevolution. Its effectiveness is derived from initiating with…
GPU-accelerated Evolutionary Many-objective Optimization Using Tensorized NSGA-III
Hao Li, Zhenyu Liang, Ran Cheng
NSGA-III is one of the most widely adopted algorithms for tackling many-objective optimization problems. However, its CPU-based design severely limits scalability and computational…