7 citations · 11 across the 5 of their papers we have counts for
5 papers
Explaining Genetic Programming Trees using Large Language Models
Paula Maddigan, Andrew Lensen, Bing Xue
Genetic programming (GP) has the potential to generate explainable results, especially when used for dimensionality reduction. In this research, we investigate the potential of lev…
Fast and Efficient Local Search for Genetic Programming Based Loss Function Learning
Christian Raymond, Qi Chen, Bing Xue +1
In this paper, we develop upon the topic of loss function learning, an emergent meta-learning paradigm that aims to learn loss functions that significantly improve the performance…
A Consistent Lebesgue Measure for Multi-label Learning
Kaan Demir, Bach Nguyen, Bing Xue +1
Multi-label loss functions are usually non-differentiable, requiring surrogate loss functions for gradient-based optimisation. The consistency of surrogate loss functions is not pr…
Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications and Open Issues
Nan Li, Lianbo Ma, Guo Yu +3
Over recent years, there has been a rapid development of deep learning (DL) in both industry and academia fields. However, finding the optimal hyperparameters of a DL model often n…
Impacts of Real Hands on 5G Millimeter-Wave Cellphone Antennas: Measurements and Electromagnetic Models
Bing Xue, Pasi Koivumaki, Lauri Vaha-Savo +2
Penetration of cellphones into markets requires their robust operation in time-varying radio environments, especially for millimeter-wave communications. Hands and fingers of a hum…