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of 82
pro vyhledávání: '"Duan, Qiqi"'
Automated design of metaheuristic algorithms offers an attractive avenue to reduce human effort and gain enhanced performance beyond human intuition. Current automated methods design algorithms within a fixed structure and operate from scratch. This
Externí odkaz:
http://arxiv.org/abs/2405.03419
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems ( Volume: 35, Issue: 11, November 2024)
In the post-Moore era, main performance gains of black-box optimizers are increasingly depending on parallelism, especially for large-scale optimization (LSO). Here we propose to parallelize the well-established covariance matrix adaptation evolution
Externí odkaz:
http://arxiv.org/abs/2310.05377
Publikováno v:
Applied Soft Computing, Volume 166, 2024, 112232
Given the ubiquity of non-separable optimization problems in real worlds, in this paper we analyze and extend the large-scale version of the well-known cooperative coevolution (CC), a divide-and-conquer black-box optimization framework, on non-separa
Externí odkaz:
http://arxiv.org/abs/2304.05020
Metaheuristics are prominent gradient-free optimizers for solving hard problems that do not meet the rigorous mathematical assumptions of analytical solvers. The canonical manual optimizer design could be laborious, untraceable and error-prone, let a
Externí odkaz:
http://arxiv.org/abs/2303.06536
Publikováno v:
Transactions on Machine Learning Research, 2024, https://openreview.net/forum?id=qhtHsvF5zj
Metaheuristics have gained great success in academia and practice because their search logic can be applied to any problem with available solution representation, solution quality evaluation, and certain notions of locality. Manually designing metahe
Externí odkaz:
http://arxiv.org/abs/2303.06532
Autor:
Duan, Qiqi, Zhou, Guochen, Shao, Chang, Wang, Zhuowei, Feng, Mingyang, Huang, Yuwei, Tan, Yajing, Yang, Yijun, Zhao, Qi, Shi, Yuhui
In this paper, we present an open-source pure-Python library called PyPop7 for black-box optimization (BBO). As population-based methods (e.g., evolutionary algorithms, swarm intelligence, and pattern search) become increasingly popular for BBO, the
Externí odkaz:
http://arxiv.org/abs/2212.05652
Publikováno v:
In Applied Soft Computing November 2024 166
Akademický článek
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Network representation learning (NRL) has been widely used to help analyze large-scale networks through mapping original networks into a low-dimensional vector space. However, existing NRL methods ignore the impact of properties of relations on the o
Externí odkaz:
http://arxiv.org/abs/1901.10234
Autor:
Liu, Meng, Zhang, Guanfei, Wang, Ziyang, Liu, Xinyi, He, Ke, Luo, Ruiting, Duan, Qiqi, Bai, Ruimin, Wang, Yuqian, Du, Wenqian, Zheng, Yan, Shao, Yongping
Publikováno v:
In Journal of Investigative Dermatology April 2023