A team of researchers from the Shanghai Institute of Applied Physics, Chinese Academy of Sciences, has developed an ...
In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...
ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
Large language models (LLMs) leverage unsupervised learning to capture statistical patterns within vast amounts of text data. At the core of these models lies the Transformer architecture, which ...
Abstract: Dynamic constrained multiobjective optimization problems (DCMOPs) are widely existed in real-world applications and emerged as a prominent research focus in the evolutionary computation ...
1 State Key Laboratory of Intelligent Mining Equipment Technology, Taiyuan, China 2 School of Computer Science and Technology, Anhui University, Hefei, China In the manufacturing process of electric ...
Abstract: Large-scale constrained multiobjective optimization problems (LSCMOPs) exist widely in science and technology. LSCMOPs pose great challenges to algorithms due to the need to optimize ...
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