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DaNuoYi: Evolutionary Multi-Task Injection Testing on Web Application Firewalls
Ke Li, Heng Yang+, Willem Visser
CoRR abs/2206.05743 | June 2022
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@article{LiYV22,
author = {Ke Li and
Heng Yang and
Willem Visser},
title = {DaNuoYi: Evolutionary Multi-Task Injection Testing on Web Application Firewalls},
journal = {CoRR},
volume = {abs/2206.05743},
year = {2022},
url = {https://arxiv.org/abs/2206.05743},
doi = {10.48550/arXiv.2206.05743},
eprinttype = {arXiv},
eprint = {2206.05743}
}
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Interactive Evolutionary Multi-Objective Optimization via Learning-to-Rank
Ke Li, Guiyu Lai+, Xin Yao
CoRR abs/2204.02604 | April 2022
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@article{LiLY22,
author = {Ke Li and
Guiyu Lai and
Xin Yao},
title = {Interactive Evolutionary Multi-Objective Optimization via Learning-to-Rank},
journal = {CoRR},
volume = {abs/2204.02604},
year = {2022},
url = {https://doi.org/10.48550/arXiv.2204.02604},
doi = {10.48550/arXiv.2204.02604},
eprinttype = {arXiv},
eprint = {2204.02604},
timestamp = {Tue, 12 Apr 2022 18:42:14 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2204-02604.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Art-Attack: Black-Box Adversarial Attack via Evolutionary Art
Phoenix Williams+, Ke Li
CoRR abs/2203.04405 | March 2022
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@article{WilliamsL22,
author = {Phoenix Neale Williams and
Ke Li},
title = {Art-Attack: Black-Box Adversarial Attack via Evolutionary Art},
journal = {CoRR},
volume = {abs/2203.04405},
year = {2022},
url = {https://doi.org/10.48550/arXiv.2203.04405},
doi = {10.48550/arXiv.2203.04405},
eprinttype = {arXiv},
eprint = {2203.04405},
timestamp = {Thu, 19 May 2022 17:23:34 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2203-04405.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Automated Few-Shot Time Series Forecasting based on Bi-level Programming
Jiangjiao Xu+, Ke Li
CoRR abs/2203.03328 | March 2022
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@article{XuL22,
author = {Jiangjiao Xu and
Ke Li},
title = {Automated Few-Shot Time Series Forecasting based on Bi-level Programming},
journal = {CoRR},
volume = {abs/2203.03328},
year = {2022},
url = {https://doi.org/10.48550/arXiv.2203.03328},
doi = {10.48550/arXiv.2203.03328},
eprinttype = {arXiv},
eprint = {2203.03328},
timestamp = {Wed, 16 Mar 2022 16:39:52 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2203-03328.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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LONViZ: Unboxing the Black-Box of Configurable Software Systems from a Complex Networks Perspective
Ke Li, Peili Mao+, Tao Chen
CoRR abs/2201.01429 | January 2022
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@article{LiMC22,
author = {Ke Li and
Peili Mao and
Tao Chen},
title = {LONViZ: Unboxing the black-box of Configurable Software Systems from
a Complex Networks Perspective},
journal = {CoRR},
volume = {abs/2201.01429},
year = {2022},
url = {https://arxiv.org/abs/2201.01429},
eprinttype = {arXiv},
eprint = {2201.01429},
timestamp = {Mon, 10 Jan 2022 13:39:01 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2201-01429.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Decomposition Multi-Objective Evolutionary Optimization: From State-of-the-Art to Future Opportunities
Ke Li
CoRR abs/2108.09588 | August 2021
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@article{Li22,
author = {Ke Li},
title = {Decomposition Multi-Objective Evolutionary Optimization: From State-of-the-Art
to Future Opportunities},
journal = {CoRR},
volume = {abs/2108.09588},
year = {2021},
url = {https://arxiv.org/abs/2108.09588},
eprinttype = {arXiv},
eprint = {2108.09588},
timestamp = {Fri, 27 Aug 2021 15:02:29 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2108-09588.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Evolutionary Multi-Objective Virtual Network Function Placement: A Formal Model and Effective Algorithms
Joseph Billingsley+, Ke Li, Wang Miao, Geyong Min, Nektarios Georgalas
CoRR abs/2106.14727 | May 2021
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@article{BillingsleyLMMG22,
author = {Joseph Billingsley and
Ke Li and
Wang Miao and
Geyong Min and
Nektarios Georgalas},
title = {Evolutionary Multi-Objective Virtual Network Function Placement: {A}
Formal Model and Effective Algorithms},
journal = {CoRR},
volume = {abs/2106.14727},
year = {2021},
url = {https://arxiv.org/abs/2106.14727},
eprinttype = {arXiv},
eprint = {2106.14727},
timestamp = {Thu, 19 May 2022 17:23:34 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2106-14727.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Batched Data-Driven Evolutionary Multi-Objective Optimization Based on Manifold Interpolation
Ke Li, Renzhi Chen+
IEEE Trans. Evolutionary Computation (TEVC)
10.1109/TEVC.2022.3162993
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Multi-objective optimization problems are ubiquitous in real-world science, engineering and design optimization problems. It is not uncommon that the objective functions are as a black box, the evaluation of which usually involve time-consuming and/or costly physical experiments. Data-driven evolutionary optimization can be used to search for a set of non-dominated trade-off solutions, where the expensive objective functions are approximated as a surrogate model. In this paper, we propose a framework for implementing batched data-driven evolutionary multi-objective optimization. It is so general that any off-the-shelf evolutionary multi-objective optimization algorithms can be applied in a plug-in manner. There are two unique components: 1) based on the Karush-Kuhn-Tucker conditions, a manifold interpolation approach that explores more diversified solutions with a convergence guarantee along the manifold of the approximated Pareto-optimal set; and 2) a batch recommendation approach that reduces the computational time of the data-driven evolutionary optimization process by evaluating multiple samples at a time in parallel. Comparing against 7 state-of-the-art surrogate-assisted evolutionary algorithms, experiments on 168 benchmark test problem instances with various properties and a real-world application on hyper-parameter optimization fully demonstrate the effectiveness and superiority of our proposed framework, which is featured with a faster convergence and a stronger resilience to various PF shapes.
@ARTICLE{LiC22,
author = {Li, Ke and
Chen, Renzhi},
journal = {IEEE Transactions on Evolutionary Computation},
title = {Batched Data-Driven Evolutionary Multi-Objective Optimization Based on Manifold Interpolation},
year = {2022},
doi = {10.1109/TEVC.2022.3162993}}
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Distributed UAV Swarm Formation and Collision Avoidance Strategies Over Fixed and Switching Topologies
Jia Wu, Chunbo Luo, Yang Luo, Ke Li
IEEE Trans. Cybernetics (TCYB)
10.1109/TCYB.2021.3132587
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This article proposes a controlling framework for multiple unmanned aerial vehicles (UAVs) to integrate the modes of formation flight and swarm deployment over fixed and switching topologies. Formation strategies enable UAVs to enjoy key collective benefits including reduced energy consumption, but the shape of the formation and each UAV's freedom are significantly restrained. Swarm strategies are thus proposed to maximize each UAV's freedom following simple yet powerful rules. This article investigates the integration and switch between these two strategies, considering the deployment environment factors, such as poor network conditions and unknown and often highly mobile obstacles. We design a distributed formation controller to guide multiple UAVs in orderless states to swiftly reach an intended formation. Inspired by starling birds and similar biological creatures, a distributed collision avoidance controller is proposed to avoid unknown and mobile obstacles. We further illustrated the stability of the controllers over both fixed and switching topologies. The experimental results confirm the effectiveness of the framework.
@article{WuLLL22,
author = {Wu, Jia and
Luo, Chunbo and
Luo, Yang and
Li, Ke},
journal = {IEEE Transactions on Cybernetics},
title = {Distributed UAV Swarm Formation and Collision Avoidance Strategies Over Fixed and Switching Topologies},
year = {2021},
publisher = {IEEE}
}
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Posterior Decision-Making Based on Decomposition-Driven Knee Point Identification
Ke Li, Haifeng Nie+, Huiru Gao+, Xin Yao
IEEE Trans. Evolutionary Computation (TEVC)
10.1109/TEVC.2021.3116121
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Knee points, characterized as a small improvement on one objective can lead to a significant degradation on at least one of the other objectives, are attractive to decision makers in multi-criterion decision-making. This paper presents a simple and effective knee point identification method to help decision makers identify solution(s) of interest from a given set of trade-off solutions thus facilitating posterior decision-making. Our basic idea is to sequentially validate whether a solution is a knee point or not by comparing its localized trade-off utility with others within its neighborhood characterized from a decomposition perspective. In particular, a solution is a knee point if and only if it has the best localized trade-off utility among its neighbors. We implement a GPU version that carries out the knee point identification in a parallel manner. This GPU version reduces the worst-case complexity from quadratic to linear. The performance of our proposed method is compared with five state-of-the-art knee point identification methods on 134 test problem instances and two real-world engineering design problems. Empirical results demonstrate its outstanding performance especially on problems with many local knee points. We further validate the usefulness of our proposed method for guiding evolutionary multi-objective optimization algorithms to search for knee points on the fly during the evolutionary process.
@article{LiNGY22,
author = {Li, Ke and
Nie, Haifeng and
Gao, Huiru and
Yao, Xin},
journal = {IEEE Transactions on Evolutionary Computation},
title = {Posterior Decision-Making Based on Decomposition-Driven Knee Point Identification},
year = {2021},
publisher = {IEEE}
}
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Neural Architecture Search for Portrait Parsing
Bo Lyu, Yin Yang, Shiping Wen, Tingwen Huang, Ke Li
IEEE Trans. Neural Networks and Learning Systems (TNNLS)
10.1109/TNNLS.2021.3104872
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This work proposes a neural architecture search (NAS) method for portrait parsing, which is a novel up-level task based on portrait segmentation and face labeling. Recently, NAS has become an effective method in terms of automatic machine learning. However, remarkable achievements have been made only in image classification and natural language processing (NLP) areas. Meanwhile, state-of-the-art portrait segmentation and face labeling approaches are all manually designed, but few models reach a tradeoff between efficiency and performance. Thus, we are extremely interested in improving existing NAS methods for dense-per-pixel prediction tasks on portrait datasets. To achieve that, we resort to a cell-based encoder-decoder architecture with an elaborate design of connectivity structure and searching space. As a result, we achieve state-of-the-art performance on three portrait tasks, including 96.8% MIOU on EG1800 (portrait segmentation), 91.2% overall F1-score on HELEN (face labeling), and 95.1% overall F1-score on CelebAMask-HQ (portrait parsing) with only 2.29M model parameters. That is, our approach compares favorably with all previous works on portrait datasets. More crucially, we empirically prove that even a fundamental encoder-decoder architecture may reach an outstanding result on the aforementioned tasks with the help of the innovative approach of NAS. To the best of our knowledge, our work is also the first to report the success of applying NAS on these portrait tasks.
@ARTICLE{LyuYWHL22,
author = {Lyu, Bo and
Yang, Yin and
Wen, Shiping and
Huang, Tingwen and
Li, Ke},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
title = {Neural Architecture Search for Portrait Parsing},
year = {2021},
doi = {10.1109/TNNLS.2021.3104872}
}
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Vertical Distance-based Clonal Selection Mechanism for the Multiobjective Immune Algorithm
Lingjie Li+, Qiuzhen Lin, Ke Li, Zhong Ming
Swarm and Evolutionary Computation (SWEVO), 106: 107299, 2021
10.1016/j.swevo.2021.100886
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@article{LiLLM21,
author = {Lingjie Li and
Qiuzhen Lin and
Ke Li and
Zhong Ming},
title = {Vertical distance-based clonal selection mechanism for the multiobjective
immune algorithm},
journal = {Swarm Evol. Comput.},
volume = {63},
pages = {100886},
year = {2021},
url = {https://doi.org/10.1016/j.swevo.2021.100886},
doi = {10.1016/j.swevo.2021.100886},
timestamp = {Tue, 15 Jun 2021 09:16:57 +0200},
biburl = {https://dblp.org/rec/journals/swevo/LiLLM21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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A Vector Angles-Based Many-Objective Particle Swarm Optimization Algorithm Using Archive
Lei Yang+, Xin Hu, Ke Li
Applied Soft Computing (ASOC), 63: 100886, 2021
10.1016/j.asoc.2021.107299
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@article{YangHL21,
author = {Lei Yang and
Xin Hu and
Ke Li},
title = {A vector angles-based many-objective particle swarm optimization algorithm
using archive},
journal = {Appl. Soft Comput.},
volume = {106},
pages = {107299},
year = {2021},
url = {https://doi.org/10.1016/j.asoc.2021.107299},
doi = {10.1016/j.asoc.2021.107299},
timestamp = {Fri, 03 Dec 2021 13:16:58 +0100},
biburl = {https://dblp.org/rec/journals/asc/YangHL21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Bayesian Network Based Label Correlation Analysis For Multi-label Classifier Chain
Ran Wang, Suhe Ye, Ke Li, Sam Kwong
Information Sciences (INS), 554: 256–275, 2021
10.1016/j.ins.2020.12.010
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@article{WangYLK21,
author = {Ran Wang and
Suhe Ye and
Ke Li and
Sam Kwong},
title = {Bayesian network based label correlation analysis for multi-label
classifier chain},
journal = {Inf. Sci.},
volume = {554},
pages = {256--275},
year = {2021},
url = {https://doi.org/10.1016/j.ins.2020.12.010},
doi = {10.1016/j.ins.2020.12.010},
timestamp = {Fri, 09 Apr 2021 18:25:48 +0200},
biburl = {https://dblp.org/rec/journals/isci/WangYLK21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Knee Point Identification Based on the Geometric Characteristic
Renzhi Chen+, Ke Li
Proc. of the 2021 IEEE International Conference on Systems, Man, and Cybernetics
(SMC'21), IEEE, p. 764–769, October, 2021
10.1109/SMC52423.2021.9658848
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@inproceedings{Chen021,
author = {Renzhi Chen and
Ke Li},
title = {Knee Point Identification Based on the Geometric Characteristic},
booktitle = {2021 {IEEE} International Conference on Systems, Man, and Cybernetics,
{SMC} 2021, Melbourne, Australia, October 17-20, 2021},
pages = {764--769},
publisher = {{IEEE}},
year = {2021},
url = {https://doi.org/10.1109/SMC52423.2021.9658848},
doi = {10.1109/SMC52423.2021.9658848},
timestamp = {Tue, 11 Jan 2022 10:00:39 +0100},
biburl = {https://dblp.org/rec/conf/smc/Chen021.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Large-Scale Evolutionary Optimization via Multi-Task Random Grouping
Phoenix Williams+, Ke Li
Proc. of the 2021 IEEE International Conference on Systems, Man, and Cybernetics
(SMC'21), IEEE, p. 778–783, October, 2021
10.1109/SMC52423.2021.9659276
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@inproceedings{WilliamsLM21,
author = {Phoenix Neale Williams and
Ke Li and
Geyong Min},
title = {Large-Scale Evolutionary Optimization via Multi-Task Random Grouping},
booktitle = {2021 {IEEE} International Conference on Systems, Man, and Cybernetics,
{SMC} 2021, Melbourne, Australia, October 17-20, 2021},
pages = {778--783},
publisher = {{IEEE}},
year = {2021},
url = {https://doi.org/10.1109/SMC52423.2021.9659276},
doi = {10.1109/SMC52423.2021.9659276},
timestamp = {Thu, 19 May 2022 17:23:34 +0200},
biburl = {https://dblp.org/rec/conf/smc/WilliamsLM21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Transfer Bayesian Optimization for Expensive Black-Box Optimization in Dynamic Environment
Renzhi Chen+, Ke Li
Proc. of the 2021 IEEE International Conference on Systems, Man, and Cybernetics
(SMC'21), IEEE, p. 1374–1379, October, 2021
10.1109/SMC52423.2021.9659200
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@inproceedings{ChenL21,
author = {Renzhi Chen and
Ke Li},
title = {Transfer Bayesian Optimization for Expensive Black-Box Optimization
in Dynamic Environment},
booktitle = {2021 {IEEE} International Conference on Systems, Man, and Cybernetics,
{SMC} 2021, Melbourne, Australia, October 17-20, 2021},
pages = {1374--1379},
publisher = {{IEEE}},
year = {2021},
url = {https://doi.org/10.1109/SMC52423.2021.9659200},
doi = {10.1109/SMC52423.2021.9659200},
timestamp = {Tue, 11 Jan 2022 10:00:39 +0100},
biburl = {https://dblp.org/rec/conf/smc/Chen021a.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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ADMM-based OPF Problem Against Cyber Attacks in Smart Grid
Jiangjiao Xu+, Ke Li, Mohammad Abusara, Yan Zhang
Proc. of the 2021 IEEE International Conference on Systems, Man, and Cybernetics
(SMC'21), IEEE, p. 1418–1423, October, 2021
10.1109/SMC52423.2021.9658699
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@inproceedings{XuLA021,
author = {Jiangjiao Xu and
Ke Li and
Mohammad Abusara and
Yan Zhang},
title = {ADMM-based {OPF} Problem Against Cyber Attacks in Smart Grid},
booktitle = {2021 {IEEE} International Conference on Systems, Man, and Cybernetics,
{SMC} 2021, Melbourne, Australia, October 17-20, 2021},
pages = {1418--1423},
publisher = {{IEEE}},
year = {2021},
url = {https://doi.org/10.1109/SMC52423.2021.9658699},
doi = {10.1109/SMC52423.2021.9658699},
timestamp = {Thu, 10 Mar 2022 11:05:49 +0100},
biburl = {https://dblp.org/rec/conf/smc/XuLA021.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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An Enhancement of the NSGA-II Reliability Optimization using Extended Kalman Filter Based Initialization
Savas Yuec+, Ke Li
Proc. of the 2021 20th UK Workshop on Computational Intelligence
(UKCI'21), Springer, p. 121–128, September, 2021
10.1007/978-3-030-87094-2_11
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@inproceedings{YuceL21,
author = {Savas Yuce and
Ke Li},
title = {An Enhancement of the {NSGA-II} Reliability Optimization Using Extended
Kalman Filter Based Initialization},
booktitle = {Advances in Computational Intelligence Systems - Contributions Presented
at the 20th {UK} Workshop on Computational Intelligence, September
8-10, 2021, Aberystwyth, Wales, {UK}},
series = {Advances in Intelligent Systems and Computing},
volume = {1409},
pages = {121--128},
publisher = {Springer},
year = {2021},
url = {https://doi.org/10.1007/978-3-030-87094-2\_11},
doi = {10.1007/978-3-030-87094-2\_11},
timestamp = {Thu, 16 Dec 2021 15:07:27 +0100},
biburl = {https://dblp.org/rec/conf/ukci/YuceL21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Empirical Studies on the Role of the Decision Maker in Interactive Evolutionary Multi-Objective Optimization
Guiyu Lai+, Minhui Liao, Ke Li
Proc. of the 2021 IEEE Congress on Evolutionary Computation
(CEC'21), IEEE, p. 1–8, June, 2021
10.1109/CEC45853.2021.9504980
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@inproceedings{LaiL021,
author = {Guiyu Lai and
Minhui Liao and
Ke Li},
title = {Empirical Studies on the Role of the Decision Maker in Interactive
Evolutionary Multi-Objective Optimization},
booktitle = {{IEEE} Congress on Evolutionary Computation, {CEC} 2021, Krak{\'{o}}w,
Poland, June 28 - July 1, 2021},
pages = {185--192},
publisher = {{IEEE}},
year = {2021},
url = {https://doi.org/10.1109/CEC45853.2021.9504980},
doi = {10.1109/CEC45853.2021.9504980},
timestamp = {Thu, 12 Aug 2021 16:39:59 +0200},
biburl = {https://dblp.org/rec/conf/cec/LaiL021.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Empirical Study of Correlations in the Fitness Landscapes of Combinatorial Optimization Problems
Longfei Zhang+, Ke Li, Shi Gu
Proc. of the 23th Annual Conference on Genetic and Evolutionary Computation
(GECCO’21), ACM, p. 247–248, July, 2021.
10.1145/3449726.3459528
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@inproceedings{ZhangLG21,
author = {Longfei Zhang and
Ke Li and
Shi Gu},
title = {Empirical study of correlations in the fitness landscapes of combinatorial
optimization problems},
booktitle = {{GECCO} '21: Genetic and Evolutionary Computation Conference, Companion
Volume, Lille, France, July 10-14, 2021},
pages = {247--248},
publisher = {{ACM}},
year = {2021},
url = {https://doi.org/10.1145/3449726.3459528},
doi = {10.1145/3449726.3459528},
timestamp = {Thu, 19 May 2022 17:23:34 +0200},
biburl = {https://dblp.org/rec/conf/gecco/ZhangLG21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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An Improved Two-Archive Evolutionary Algorithm for Constrained Multi-Objective Optimization
Xinyu Shan+, Ke Li
Proc. of the 11th International Conference on Evolutionary Multi-Criterion Optimization
(EMO'21), Springer LNCS, volume 12654, p. 235–247, March, 2021
10.1007/978-3-030-72062-9_19
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@inproceedings{ShanL21,
author = {Xinyu Shan and
Ke Li},
title = {An Improved Two-Archive Evolutionary Algorithm for Constrained Multi-objective
Optimization},
booktitle = {Evolutionary Multi-Criterion Optimization - 11th International Conference,
{EMO} 2021, Shenzhen, China, March 28-31, 2021, Proceedings},
series = {Lecture Notes in Computer Science},
volume = {12654},
pages = {235--247},
publisher = {Springer},
year = {2021},
url = {https://doi.org/10.1007/978-3-030-72062-9\_19},
doi = {10.1007/978-3-030-72062-9\_19},
timestamp = {Thu, 08 Apr 2021 15:51:58 +0200},
biburl = {https://dblp.org/rec/conf/emo/ShanL21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Multi-Objective Reinforcement Learning based Multi-Microgrid System Optimisation Problem
Jiangjiao Xu+, Ke Li, Mohammad Abusara
Proc. of the 11th International Conference on Evolutionary Multi-Criterion Optimization
(EMO'21), Springer LNCS, volume 12654, p. 684–696, March, 2021
10.1007/978-3-030-72062-9_54
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@inproceedings{XuLA21,
author = {Jiangjiao Xu and
Ke Li and
Mohammad Abusara},
title = {Multi-objective Reinforcement Learning Based Multi-microgrid System
Optimisation Problem},
booktitle = {Evolutionary Multi-Criterion Optimization - 11th International Conference,
{EMO} 2021, Shenzhen, China, March 28-31, 2021, Proceedings},
series = {Lecture Notes in Computer Science},
volume = {12654},
pages = {684--696},
publisher = {Springer},
year = {2021},
url = {https://doi.org/10.1007/978-3-030-72062-9\_54},
doi = {10.1007/978-3-030-72062-9\_54},
timestamp = {Mon, 12 Apr 2021 14:42:37 +0200},
biburl = {https://dblp.org/rec/conf/emo/XuLA21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Parallel Algorithms for Multiobjective Virtual Network Function Placement Problem
Joseph Billingsley+, Ke Li, Wang Miao, Geyong Min, Nektarios Georgalas
Proc. of the 11th International Conference on Evolutionary Multi-Criterion Optimization
(EMO'21), Springer LNCS, volume 12654, p. 708–720, March, 2021
10.1007/978-3-030-72062-9_56
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@inproceedings{BillingsleyLMMG21,
author = {Joseph Billingsley and
Ke Li and
Wang Miao and
Geyong Min and
Nektarios Georgalas},
title = {Parallel Algorithms for the Multiobjective Virtual Network Function
Placement Problem},
booktitle = {Evolutionary Multi-Criterion Optimization - 11th International Conference,
{EMO} 2021, Shenzhen, China, March 28-31, 2021, Proceedings},
series = {Lecture Notes in Computer Science},
volume = {12654},
pages = {708--720},
publisher = {Springer},
year = {2021},EDITOR
url = {https://doi.org/10.1007/978-3-030-72062-9\_56},
doi = {10.1007/978-3-030-72062-9\_56},
timestamp = {Thu, 19 May 2022 17:23:34 +0200},
biburl = {https://dblp.org/rec/conf/emo/BillingsleyLMMG21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Does Preference Always Help? A Holistic Study on Preference-Based Evolutionary Multi-Objective Optimisation Using Reference Points
Ke Li, Minhui Liao+, Kalyanmoy Deb, Geyong Min, Xin Yao
IEEE Trans. Evolutionary Computation (TEVC), 24(6): 1078–1096, 2020.
10.1109/TEVC.2020.2987559
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Code
| BiB
@article{LiLDMY20,
author = {Ke Li and
Minhui Liao and
Kalyanmoy Deb and
Geyong Min and
Xin Yao},
title = {Does Preference Always Help? {A} Holistic Study on Preference-Based
Evolutionary Multiobjective Optimization Using Reference Points},
journal = {{IEEE} Trans. Evol. Comput.},
volume = {24},
number = {6},
pages = {1078--1096},
year = {2020},
url = {https://doi.org/10.1109/TEVC.2020.2987559},
doi = {10.1109/TEVC.2020.2987559},
timestamp = {Thu, 17 Dec 2020 18:29:03 +0100},
biburl = {https://dblp.org/rec/journals/tec/LiLDMY20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Reference Point Based Multi-Objective Optimization of Reservoir Operation: a Comparison of Three Algorithms
Rong Tang, Ke Li, Wei Ding, Yuntao Wang, Huicheng Zhou, Guangtao Fu
Water Resources Management, 34: 1005–1020, 2020.
10.1007/s11269-020-02485-9
PDF
| BiB
@article{tangLDWZF20,
title = {Reference point based multi-objective optimization of reservoir operation: a comparison of three algorithms},
author = {Tang, Rong and
Li, Ke and
Ding, Wei and
Wang, Yuntao and
Zhou, Huicheng and
Fu, Guangtao},
journal = {Water Resources Management},
volume = {34},
number = {3},
pages = {1005--1020},
year = {2020},
publisher = {Springer}
}
-
Evolutionary Many-Objective Optimization Based on Adversarial Decomposition
Mengyuan Wu+, Ke Li, Sam Kwong, Qingfu Zhang
IEEE Trans. Cybernetics (TCYB), 50(2): 753–764, 2020.
10.1109/TCYB.2018.2872803
PDF
|
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| Code
| BiB
@article{WuLKZ20,
author = {Mengyuan Wu and
Ke Li and
Sam Kwong and
Qingfu Zhang},
title = {Evolutionary Many-Objective Optimization Based on Adversarial Decomposition},
journal = {{IEEE} Trans. Cybern.},
volume = {50},
number = {2},
pages = {753--764},
year = {2020},
url = {https://doi.org/10.1109/TCYB.2018.2872803},
doi = {10.1109/TCYB.2018.2872803},
timestamp = {Sat, 30 May 2020 19:51:36 +0200},
biburl = {https://dblp.org/rec/journals/tcyb/WuLKZ20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Performance Analysis of SDN and NFV enabled Mobile Cloud Computing
Joseph Billingsley+, Ke Li, Wang Miao, Geyong Min, Nektarios Georgalas
Proc. of the 2020 IEEE Global Communications Conference
(GLOBECOM'20), IEEE Press: p. 1–6, December, 2020
10.1109/GLOBECOM42002.2020.9322530
PDF
| BiB
@inproceedings{BillingsleyMLMG20,
author = {Joseph Billingsley and
Wang Miao and
Ke Li and
Geyong Min and
Nektarios Georgalas},
title = {Performance Analysis of {SDN} and {NFV} enabled Mobile Cloud Computing},
booktitle = {{IEEE} Global Communications Conference, {GLOBECOM} 2020, Virtual
Event, Taiwan, December 7-11, 2020},
pages = {1--6},
publisher = {{IEEE}},
year = {2020},
url = {https://doi.org/10.1109/GLOBECOM42002.2020.9322530},
doi = {10.1109/GLOBECOM42002.2020.9322530},
timestamp = {Thu, 19 May 2022 17:23:34 +0200},
biburl = {https://dblp.org/rec/conf/globecom/BillingsleyMLMG20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Knee Point Identification Based on Voronoi Diagram
Haifeng Nie+, Huiru Gao+, Ke Li
Proc. of the 2020 IEEE Conference on Systems, Man and Cybernetics
(SMC'20), IEEE Press: p. 1–6, December, 2020
10.1109/SMC42975.2020.9283262
PDF
| BiB
@inproceedings{NieGL20,
author = {Haifeng Nie and
Huiru Gao and
Ke Li},
title = {Knee Point Identification Based on Voronoi Diagram},
booktitle = {2020 {IEEE} International Conference on Systems, Man, and Cybernetics,
{SMC} 2020, Toronto, ON, Canada, October 11-14, 2020},
pages = {1081--1086},
publisher = {{IEEE}},
year = {2020},
url = {https://doi.org/10.1109/SMC42975.2020.9283262},
doi = {10.1109/SMC42975.2020.9283262},
timestamp = {Fri, 08 Jan 2021 11:20:37 +0100},
biburl = {https://dblp.org/rec/conf/smc/NieGL20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
BiLO-CPDP: Bi-Level Programming for Automated Model Discovery in Cross-Project Defect Prediction
Ke Li, Zilin Xiang+, Tao Chen, Kay Chen Tan
Proc. of the 35th IEEE/ACM International Conference on Automated Software Engineering
(ASE'20), IEEE Press: September, 2020
10.1145/3324884.3416617
PDF
| Code
| BiB
@inproceedings{LiXCT20,
author = {Ke Li and
Zilin Xiang and
Tao Chen and
Kay Chen Tan},
title = {BiLO-CPDP: Bi-Level Programming for Automated Model Discovery in Cross-Project
Defect Prediction},
booktitle = {35th {IEEE/ACM} International Conference on Automated Software Engineering,
{ASE} 2020, Melbourne, Australia, September 21-25, 2020},
pages = {573--584},
publisher = {{IEEE}},
year = {2020},
url = {https://doi.org/10.1145/3324884.3416617},
doi = {10.1145/3324884.3416617},
timestamp = {Fri, 12 Feb 2021 13:04:43 +0100},
biburl = {https://dblp.org/rec/conf/kbse/LiXCT20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Adaptive Operator Selection Based on Dynamic Thompson Sampling for MOEA/D
Lei Sun+, Ke Li
Proc. of the 16th International Conference on Parallel Problem Solving from Nature
(PPSN XVI), Springer LNCS, volume 12270, p. 271–284, Septermber, 2020.
10.1007/978-3-030-58115-2_19
PDF
| BiB
@inproceedings{SunL20,
author = {Lei Sun and
Ke Li},
title = {Adaptive Operator Selection Based on Dynamic Thompson Sampling for
{MOEA/D}},
booktitle = {Parallel Problem Solving from Nature - {PPSN} {XVI} - 16th International
Conference, {PPSN} 2020, Leiden, The Netherlands, September 5-9, 2020,
Proceedings, Part {II}},
series = {Lecture Notes in Computer Science},
volume = {12270},
pages = {271--284},
publisher = {Springer},
year = {2020},
url = {https://doi.org/10.1007/978-3-030-58115-2\_19},
doi = {10.1007/978-3-030-58115-2\_19},
timestamp = {Sat, 19 Sep 2020 13:19:33 +0200},
biburl = {https://dblp.org/rec/conf/ppsn/SunL20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Surrogate Assisted Evolutionary Algorithm for Medium Scale Multi-Objective Optimisation Problems
Xiaoran Ruan+, Ke Li, Bilel Derbel, Arnaud Liefooghe
Proc. of the 22th Annual Conference on Genetic and Evolutionary Computation
(GECCO’20), ACM Press: p. 560–568, July, 2020.
10.1145/3377930.3390191
PDF
| BiB
@inproceedings{RuanLDL20,
author = {Xiaoran Ruan and
Ke Li and
Bilel Derbel and
Arnaud Liefooghe},
title = {Surrogate assisted evolutionary algorithm for medium scale multi-objective
optimisation problems},
booktitle = {{GECCO} '20: Genetic and Evolutionary Computation Conference, Canc{\'{u}}n
Mexico, July 8-12, 2020},
pages = {560--568},
publisher = {{ACM}},
year = {2020},
url = {https://doi.org/10.1145/3377930.3390191},
doi = {10.1145/3377930.3390191},
timestamp = {Thu, 19 May 2022 17:23:34 +0200},
biburl = {https://dblp.org/rec/conf/gecco/RuanLDL20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Routing-Led Placement of VNFs in Arbitrary Networks
Joseph Billingsley+, Ke Li, Wang Miao, Geyong Min, Nektarios Georgalas
Proc. of the 2020 World Congress on Computational Intelligence
(WCCI'20), IEEE Press: p. 1–8, July, 2020.
10.1109/CEC48606.2020.9185531
PDF
| BiB
@article{BillingsleyLMMG20,
author = {Joseph Billingsley and
Ke Li and
Wang Miao and
Geyong Min and
Nektarios Georgalas},
title = {Routing-Led Placement of VNFs in Arbitrary Networks},
journal = {CoRR},
volume = {abs/2001.11565},
year = {2020},
url = {https://arxiv.org/abs/2001.11565},
eprinttype = {arXiv},
eprint = {2001.11565},
timestamp = {Mon, 03 Feb 2020 11:21:05 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2001-11565.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Surrogate Assisted Evolutionary Algorithm Based on Transfer Learning for Dynamic Expensive Multi-Objective Optimisation Problems
Xuezhou Fan, Ke Li, Kay Chen Tan
Proc. of the 2020 World Congress on Computational Intelligence
(WCCI'20), IEEE Press: p. 1–8, July, 2020.
10.1109/CEC48606.2020.9185522
PDF
| BiB
@inproceedings{FanLT20,
author = {Xuezhou Fan and
Ke Li and
Kay Chen Tan},
title = {Surrogate Assisted Evolutionary Algorithm Based on Transfer Learning
for Dynamic Expensive Multi-Objective Optimisation Problems},
booktitle = {{IEEE} Congress on Evolutionary Computation, {CEC} 2020, Glasgow,
United Kingdom, July 19-24, 2020},
pages = {1--8},
publisher = {{IEEE}},
year = {2020},
url = {https://doi.org/10.1109/CEC48606.2020.9185522},
doi = {10.1109/CEC48606.2020.9185522},
timestamp = {Fri, 11 Sep 2020 15:04:41 +0200},
biburl = {https://dblp.org/rec/conf/cec/FanLT20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
DeepSQLi: Deep Semantic Learning for Testing SQL Injection
Muyang Liu+, Ke Li, Tao Chen
Proc. of the ACM SIGSOFT 2020 International Symposium on Software Testing and Analysis
(ISSTA'20), ACM Press: p. 286–297, July, 2020.
10.1145/3395363.3397375
PDF
|
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| BiB
@inproceedings{LiuLC20,
author = {Muyang Liu and
Ke Li and
Tao Chen},
title = {DeepSQLi: deep semantic learning for testing {SQL} injection},
booktitle = {{ISSTA} '20: 29th {ACM} {SIGSOFT} International Symposium on Software
Testing and Analysis, Virtual Event, USA, July 18-22, 2020},
pages = {286--297},
publisher = {{ACM}},
year = {2020},
url = {https://doi.org/10.1145/3395363.3397375},
doi = {10.1145/3395363.3397375},
timestamp = {Wed, 15 Jul 2020 16:06:56 +0200},
biburl = {https://dblp.org/rec/conf/issta/Liu0020.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Understanding the Automated Parameter Optimization on Transfer Learning for Cross-Project Defect Prediction: An Empirical Study
Ke Li*, Zilin Xiang+*, Tao Chen*, Shuo Wang, Kay Chen Tan
Proc. of the 42nd International Conference on Software Engineering
(ICSE'20), ACM Press: p. 566–577, June, 2020.
10.1145/3377811.3380360
PDF
|
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| BiB
@inproceedings{LiX0WT20,
author = {Ke Li and
Zilin Xiang and
Tao Chen and
Shuo Wang and
Kay Chen Tan},
title = {Understanding the automated parameter optimization on transfer learning
for cross-project defect prediction: an empirical study},
booktitle = {{ICSE} '20: 42nd International Conference on Software Engineering,
Seoul, South Korea, 27 June - 19 July, 2020},
pages = {566--577},
publisher = {{ACM}},
year = {2020},
url = {https://doi.org/10.1145/3377811.3380360},
doi = {10.1145/3377811.3380360},
timestamp = {Tue, 12 Jan 2021 14:44:41 +0100},
biburl = {https://dblp.org/rec/conf/icse/LiX0WT20.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
On the Combined Impact of Population Size and Sub-problem Selection in MOEA/D
Geoffrey Pruvost, Bilel Derbel, Arnaud Liefooghe, Ke Li, Qingfu Zhang
Proc. of the 20th European Conference on Evolutionary Computation in Combinatorial Optimisation
(EvoCOP'20), Springer LNCS, volume 12102, p. 131–147, April, 2020.
10.1007/978-3-030-43680-3_9
PDF
| BiB
@inproceedings{PruvostDLL020,
author = {Geoffrey Pruvost and
Bilel Derbel and
Arnaud Liefooghe and
Ke Li and
Qingfu Zhang},
title = {On the Combined Impact of Population Size and Sub-problem Selection
in {MOEA/D}},
booktitle = {Evolutionary Computation in Combinatorial Optimization - 20th European
Conference, EvoCOP 2020, Held as Part of EvoStar 2020, Seville, Spain,
April 15-17, 2020, Proceedings},
series = {Lecture Notes in Computer Science},
volume = {12102},
pages = {131--147},
publisher = {Springer},
year = {2020},
url = {https://doi.org/10.1007/978-3-030-43680-3\_9},
doi = {10.1007/978-3-030-43680-3\_9},
timestamp = {Sun, 25 Jul 2021 11:53:08 +0200},
biburl = {https://dblp.org/rec/conf/evoW/PruvostDLL020.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Learning to Decompose: A Paradigm for Decomposition-Based Multi-Objective Optimization
Mengyuan Wu+, Ke Li, Sam Kwong, Qingfu Zhang, Jun Zhang
IEEE Trans. Evolutionary Computation (TEVC), 23(3): 376–390, 2019.
10.1109/TEVC.2018.2865931
PDF
| Supp
| Code
| BiB
@article{WuLKZZ19,
author = {Mengyuan Wu and
Ke Li and
Sam Kwong and
Qingfu Zhang and
Jun Zhang},
title = {Learning to Decompose: {A} Paradigm for Decomposition-Based Multiobjective
Optimization},
journal = {{IEEE} Trans. Evol. Comput.},
volume = {23},
number = {3},
pages = {376--390},
year = {2019},
url = {https://doi.org/10.1109/TEVC.2018.2865931},
doi = {10.1109/TEVC.2018.2865931},
timestamp = {Tue, 12 May 2020 16:51:10 +0200},
biburl = {https://dblp.org/rec/journals/tec/WuLKZZ19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Interactive Decomposition Multi-Objective Optimization via Progressively Learned Value Functions
Ke Li*, Renzhi Chen*+, Dragan Savic, Xin Yao
IEEE Trans. Fuzzy Systems (TFS), 27(5): 845–860, 2019.
10.1109/TFUZZ.2018.2880700
PDF
|
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| BiB
@article{LiCSY19,
author = {Ke Li and
Renzhi Chen and
Dragan A. Savic and
Xin Yao},
title = {Interactive Decomposition Multiobjective Optimization Via Progressively
Learned Value Functions},
journal = {{IEEE} Trans. Fuzzy Syst.},
volume = {27},
number = {5},
pages = {849--860},
year = {2019},
url = {https://doi.org/10.1109/TFUZZ.2018.2880700},
doi = {10.1109/TFUZZ.2018.2880700},
timestamp = {Tue, 12 May 2020 16:52:42 +0200},
biburl = {https://dblp.org/rec/journals/tfs/LiCSY19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Two-Archive Evolutionary Algorithm for Constrained Multi-Objective Optimization
Ke Li*, Renzhi Chen*+, Guangtao Fu, Xin Yao
IEEE Trans. Evolutionary Computation (TEVC), 23(2): 303–315, 2019.
10.1109/TEVC.2018.2855411
PDF
|
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|
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| BiB
@article{LiCFY19,
author = {Ke Li and
Renzhi Chen and
Guangtao Fu and
Xin Yao},
title = {Two-Archive Evolutionary Algorithm for Constrained Multiobjective
Optimization},
journal = {{IEEE} Trans. Evol. Comput.},
volume = {23},
number = {2},
pages = {303--315},
year = {2019},
url = {https://doi.org/10.1109/TEVC.2018.2855411},
doi = {10.1109/TEVC.2018.2855411},
timestamp = {Tue, 12 May 2020 16:51:04 +0200},
biburl = {https://dblp.org/rec/journals/tec/LiCFY19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
A Knee-Point-Based Evolutionary Algorithm Using Weighted Subpopulation for Many-Objective Optimization
Juan Zou, Chunhui Ji, Shengxiang Yang, Yuping Zhang, Jinhua Zheng, Ke Li
Swarm and Evolutionary Computation, 47: 33–43, 2019.
10.1016/j.swevo.2019.02.001
PDF
| BiB
@article{ZouJYZZL19,
author = {Juan Zou and
Chunhui Ji and
Shengxiang Yang and
Yuping Zhang and
Jinhua Zheng and
Ke Li},
title = {A Knee-Point-Based Evolutionary Algorithm Using Weighted Subpopulation for Many-Objective Optimization},
journal = {Swarm and Evolutionary Computation},
year = {2019},
note = {accepted for publication}
}
-
Which Surrogate Works for Empirical Performance Modelling? A Case Study with Differential Evolution
Ke Li, Zilin Xiang+, Kay Chen Tan
Proc. of the 2019 IEEE Congress on Evolutionary Computation (CEC'19), IEEE Press: p. 1988–1995, June, 2019.
10.1109/CEC.2019.8789984
PDF
| Supp
| BiB
@article{LiXT19,
author = {Ke Li and
Zilin Xiang and
Kay Chen Tan},
title = {Which Surrogate Works for Empirical Performance Modelling? {A} Case
Study with Differential Evolution},
journal = {CoRR},
volume = {abs/1901.11120},
year = {2019},
url = {http://arxiv.org/abs/1901.11120},
eprinttype = {arXiv},
eprint = {1901.11120},
timestamp = {Mon, 16 Mar 2020 17:55:51 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-1901-11120.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Visualisation of Pareto Front Approximation: A Short Survey and Empirical Comparisons
Huiru Gao+, Haifeng Nie+, Ke Li
Proc. of the 2019 IEEE Congress on Evolutionary Computation (CEC'19), IEEE Press: p. 1750–1757, June, 2019.
10.1109/CEC.2019.8790298
PDF
| Supp
| BiB
@article{GaoNL19,
author = {Huiru Gao and
Haifeng Nie and
Ke Li},
title = {Visualisation of Pareto Front Approximation: {A} Short Survey and
Empirical Comparisons},
journal = {CoRR},
volume = {abs/1903.01768},
year = {2019},
url = {http://arxiv.org/abs/1903.01768},
eprinttype = {arXiv},
eprint = {1903.01768},
timestamp = {Fri, 08 Jan 2021 11:20:34 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-1903-01768.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Decomposition Multi-Objective Optimisation: Current Developments and Future Opportunities
Ke Li, Qingfu Zhang
Proc. of the 21th Annual Conference on Genetic and Evolutionary Computation (GECCO’19): ACM Press: p. 1002–1031, July 2019.
10.1145/3319619.3323369
Slides
| BiB
@inproceedings{LiZ19,
author = {Ke Li and
Qingfu Zhang},
title = {Decomposition multi-objective optimisation: current developments and
future opportunities},
booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference
Companion, {GECCO} 2019, Prague, Czech Republic, July 13-17, 2019},
pages = {1002--1031},
publisher = {{ACM}},
year = {2019},
url = {https://doi.org/10.1145/3319619.3323369},
doi = {10.1145/3319619.3323369},
timestamp = {Mon, 15 Jul 2019 16:26:46 +0200},
biburl = {https://dblp.org/rec/conf/gecco/LiZ19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Security Testing of Web Applications: A Search-Based Approach for Detecting SQL Injection Vulnerabilities
Muyang Liu+, Ke Li, Tao Chen
Proc. of the 21th Annual Conference on Genetic and Evolutionary Computation (GECCO’19), ACM Press: p. 417–418, July 2019.
10.1145/3319619.3322026
PDF
| BiB
@inproceedings{LiuLC19,
author = {Muyang Liu and
Ke Li and
Tao Chen},
title = {Security testing of web applications: a search-based approach for
detecting {SQL} injection vulnerabilities},
booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference
Companion, {GECCO} 2019, Prague, Czech Republic, July 13-17, 2019},
pages = {417--418},
publisher = {{ACM}},
year = {2019},
url = {https://doi.org/10.1145/3319619.3322026},
doi = {10.1145/3319619.3322026},
timestamp = {Wed, 08 Jan 2020 08:56:46 +0100},
biburl = {https://dblp.org/rec/conf/gecco/LiuLC19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Progressive Preference Learning: Proof-of-Principle Results in MOEA/D
Ke Li
Proc. of the 10th International Conference on Evolutionary Multi-Criterion Optimization (EMO’19), Springer LNCS, volume 11411, p. 631–643, March 2019.
10.1007/978-3-030-12598-1_50
PDF
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@inproceedings{Li19,
author = {Ke Li},
title = {Progressive Preference Learning: Proof-of-Principle Results in {MOEA/D}},
booktitle = {EMO'19: Proc. of the 10th International Conference Evolutionary Multi-Criterion Optimization},
pages = {631--643},
year = {2019},
url = {https://doi.org/10.1007/978-3-030-12598-1\_50},
doi = {10.1007/978-3-030-12598-1\_50},
timestamp = {Thu, 28 Feb 2019 14:53:34 +0100},
biburl = {https://dblp.org/rec/bib/conf/emo/Li19},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
A Formal Model for Multi-objective Optimisation of NFV Placement
Joseph Billingsley, Ke Li, Wang Miao, Geyong Min, N. Georgalas
Proc. of the 10th International Conference on Evolutionary Multi-Criterion Optimization (EMO’19), Springer LNCS, volume 11411, p. 529–540, March 2019.
10.1007/978-3-030-12598-1_42
PDF
| BiB
@inproceedings{BillingsleyLMMG19,
author = {Joseph Billingsley and
Ke Li and
Wang Miao and
Geyong Min and
Nektarios Georgalas},
title = {A Formal Model for Multi-objective Optimisation of Network Function
Virtualisation Placement},
booktitle = {Evolutionary Multi-Criterion Optimization - 10th International Conference,
{EMO} 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings},
series = {Lecture Notes in Computer Science},
volume = {11411},
pages = {529--540},
publisher = {Springer},
year = {2019},
url = {https://doi.org/10.1007/978-3-030-12598-1\_42},
doi = {10.1007/978-3-030-12598-1\_42},
timestamp = {Fri, 26 Feb 2021 09:21:56 +0100},
biburl = {https://dblp.org/rec/conf/emo/BillingsleyLMMG19.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
R-Metric: Evaluating the Performance of Preference-Based Evolutionary Multi-Objective Optimization Using Reference Points
Ke Li, Kalyanmoy Deb, Xin Yao
IEEE Trans. Evolutionary Computation (TEVC), 22(6): 821–835, 2018.
10.1109/TEVC.2017.2737781
PDF
|
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|
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| BiB
@article{LiDY18,
author = {Ke Li and
Kalyanmoy Deb and
Xin Yao},
title = {R-Metric: Evaluating the Performance of Preference-Based Evolutionary
Multiobjective Optimization Using Reference Points},
journal = {{IEEE} Trans. Evol. Comput.},
volume = {22},
number = {6},
pages = {821--835},
year = {2018},
url = {https://doi.org/10.1109/TEVC.2017.2737781},
doi = {10.1109/TEVC.2017.2737781},
timestamp = {Tue, 12 May 2020 16:50:45 +0200},
biburl = {https://dblp.org/rec/journals/tec/LiDY18.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Integration of Preferences in Decomposition Multiobjective Optimization
Ke Li*, Renzhi Chen*+, Geyong Min, Xin Yao
IEEE Trans. Cybernetics (TCYB), 48(12): 3359–3370, 2018.
10.1109/TCYB.2018.2859363
PDF
|
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|
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| BiB
@article{LiCMY18,
author = {Ke Li and
Renzhi Chen and
Geyong Min and
Xin Yao},
title = {Integration of Preferences in Decomposition Multiobjective Optimization},
journal = {{IEEE} Trans. Cybernetics},
volume = {48},
number = {12},
pages = {3359--3370},
year = {2018},
url = {https://doi.org/10.1109/TCYB.2018.2859363},
doi = {10.1109/TCYB.2018.2859363},
timestamp = {Sun, 23 Dec 2018 17:21:04 +0100},
biburl = {https://dblp.org/rec/bib/journals/tcyb/LiCMY18},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Evolutionary Multiobjective Optimization-Based Multimodal Optimization: Fitness Landscape Approximation and Peak Detection
Ran Cheng, Miqing Li, Ke Li, Xin Yao
IEEE Trans. Evolutionary Computation (TEVC), 22(5): 692–706, 2018.
10.1109/TEVC.2017.2744328
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@article{ChengLLY18,
author = {Ran Cheng and
Miqing Li and
Ke Li and
Xin Yao},
title = {Evolutionary Multiobjective Optimization-Based Multimodal Optimization:
Fitness Landscape Approximation and Peak Detection},
journal = {{IEEE} Trans. Evolutionary Computation},
volume = {22},
number = {5},
pages = {692--706},
year = {2018},
url = {https://doi.org/10.1109/TEVC.2017.2744328},
doi = {10.1109/TEVC.2017.2744328},
timestamp = {Sun, 23 Dec 2018 17:21:04 +0100},
biburl = {https://dblp.org/rec/bib/journals/tec/ChengLLY18},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
FEMOSAA: Feature Guided and Knee Driven Multi-Objective Optimization for Self-Adaptive Software at Runtime
Tao Chen, Ke Li, Rami Bahsoon, Xin Yao
ACM Trans. Software Engineering and Methodology (TOSEM), 27(2): 1–50, 2018.
10.1145/3204459
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@article{ChenLBY18,
author = {Tao Chen and
Ke Li and
Rami Bahsoon and
Xin Yao},
title = {{FEMOSAA:} Feature-Guided and Knee-Driven Multi-Objective Optimization
for Self-Adaptive Software},
journal = {{ACM} Trans. Softw. Eng. Methodol.},
volume = {27},
number = {2},
pages = {5:1--5:50},
year = {2018},
url = {https://doi.org/10.1145/3204459},
doi = {10.1145/3204459},
timestamp = {Wed, 21 Nov 2018 12:44:28 +0100},
biburl = {https://dblp.org/rec/bib/journals/tosem/ChenLBY18},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Dynamic Multi-Objectives Optimization with a Changing Number of Objectives
Ke Li*, Renzhi Chen*+, Xin Yao,
IEEE Trans. Evolutionary Computation (TEVC), 21(1): 157–171, 2018.
10.1109/TEVC.2017.2669638
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@article{ChenLY18,
author = {Renzhi Chen and
Ke Li and
Xin Yao},
title = {Dynamic Multiobjectives Optimization With a Changing Number of Objectives},
journal = {{IEEE} Trans. Evolutionary Computation},
volume = {22},
number = {1},
pages = {157--171},
year = {2018},
url = {https://doi.org/10.1109/TEVC.2017.2669638},
doi = {10.1109/TEVC.2017.2669638},
timestamp = {Wed, 04 Jul 2018 13:22:50 +0200},
biburl = {https://dblp.org/rec/bib/journals/tec/ChenLY18},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Efficient Non-domination Level Update Method for Steady-State Evolutionary Multiobjective Optimization
Ke Li, Kalyanmoy Deb, Qingfu Zhang, Qiang Zhang
IEEE Trans. Cybernetics (TCYB), 47(9): 2838–2849, 2017.
10.1109/TCYB.2016.2621008
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@article{LiDZZ17,
author = {Ke Li and
Kalyanmoy Deb and
Qingfu Zhang and
Qiang Zhang},
title = {Efficient Nondomination Level Update Method for Steady-State Evolutionary
Multiobjective Optimization},
journal = {{IEEE} Trans. Cybernetics},
volume = {47},
number = {9},
pages = {2838--2849},
year = {2017},
url = {https://doi.org/10.1109/TCYB.2016.2621008},
doi = {10.1109/TCYB.2016.2621008},
timestamp = {Wed, 14 Nov 2018 10:31:31 +0100},
biburl = {https://dblp.org/rec/bib/journals/tcyb/LiDZZ17},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Matching-Based Selection with Incomplete Lists for Decomposition Multi-Objective Optimization
Mengyuan Wu+, Ke Li, Sam Kwong, Yu Zhou, Qingfu Zhang
IEEE Trans. Evolutionary Computation (TEVC), 21(4): 554–568, 2017.
10.1109/TEVC.2017.2656922
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@article{WuLKZZ17,
author = {Mengyuan Wu and
Ke Li and
Sam Kwong and
Yu Zhou and
Qingfu Zhang},
title = {Matching-Based Selection With Incomplete Lists for Decomposition Multiobjective
Optimization},
journal = {{IEEE} Trans. Evolutionary Computation},
volume = {21},
number = {4},
pages = {554--568},
year = {2017},
url = {https://doi.org/10.1109/TEVC.2017.2656922},
doi = {10.1109/TEVC.2017.2656922},
timestamp = {Sun, 23 Sep 2018 19:44:31 +0200},
biburl = {https://dblp.org/rec/bib/journals/tec/WuLKZZ17},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Recent advances in semantic computing and personalization
Haoran Xie, Fu Lee Wang, Xudong Mao, Ke Li, Qing Li, Handing Wang
Neurocomputing (NEUCOM). 254: 1–2, 2017.
10.1016/j.neucom.2017.02.073
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@article{XieWMLLW17,
author = {Haoran Xie and
Fu Lee Wang and
Xudong Mao and
Ke Li and
Qing Li and
Handing Wang},
title = {Recent advances in semantic computing and personalization},
journal = {Neurocomputing},
volume = {254},
pages = {1--2},
year = {2017},
url = {https://doi.org/10.1016/j.neucom.2017.02.073},
doi = {10.1016/j.neucom.2017.02.073},
timestamp = {Fri, 30 Nov 2018 13:23:21 +0100},
biburl = {https://dblp.org/rec/bib/journals/ijon/XieWMLLW17},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition
Ke Li, Kalyanmoy Deb, Qingfu Zhang, Sam Kwong
IEEE Trans. Evolutionary Computation (TEVC), 19(5): 694–716, 2015.
10.1109/TEVC.2014.2373386
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@article{LiDZK15,
author = {Ke Li and
Kalyanmoy Deb and
Qingfu Zhang and
Sam Kwong},
title = {An Evolutionary Many-Objective Optimization Algorithm Based on Dominance
and Decomposition},
journal = {{IEEE} Trans. Evolutionary Computation},
volume = {19},
number = {5},
pages = {694--716},
year = {2015},
url = {https://doi.org/10.1109/TEVC.2014.2373386},
doi = {10.1109/TEVC.2014.2373386},
timestamp = {Sun, 23 Sep 2018 19:44:31 +0200},
biburl = {https://dblp.org/rec/bib/journals/tec/LiDZK15},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Interrelationship-Based Selection for Decomposition Multiobjective Optimization
Ke Li, Sam Kwong, Qingfu Zhang, Kalyanmoy Deb
IEEE Trans. Cybernetics (TCYB), 45(10): 2076–2088, 2015
10.1109/TCYB.2014.2365354
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@article{LiKZD15,
author = {Ke Li and
Sam Kwong and
Qingfu Zhang and
Kalyanmoy Deb},
title = {Interrelationship-Based Selection for Decomposition Multiobjective
Optimization},
journal = {{IEEE} Trans. Cybernetics},
volume = {45},
number = {10},
pages = {2076--2088},
year = {2015},
url = {https://doi.org/10.1109/TCYB.2014.2365354},
doi = {10.1109/TCYB.2014.2365354},
timestamp = {Wed, 14 Nov 2018 10:31:35 +0100},
biburl = {https://dblp.org/rec/bib/journals/tcyb/LiKZD15},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
A Dual-Population Paradigm for Evolutionary Multiobjective Optimization
Ke Li, Sam Kwong, Kalyanmoy Deb
Information Sciences (INS), 309: 50–72, 2015.
10.1016/j.ins.2015.03.002
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@article{LiKD15,
author = {Ke Li and
Sam Kwong and
Kalyanmoy Deb},
title = {A dual-population paradigm for evolutionary multiobjective optimization},
journal = {Inf. Sci.},
volume = {309},
pages = {50--72},
year = {2015},
url = {https://doi.org/10.1016/j.ins.2015.03.002},
doi = {10.1016/j.ins.2015.03.002},
timestamp = {Wed, 14 Nov 2018 10:27:37 +0100},
biburl = {https://dblp.org/rec/bib/journals/isci/LiKD15},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Class-Specific Soft Voting based Multiple Extreme Learning Machines Ensemble
Jingjing Cao, Sam Kwong, Ran Wang, Xiaodong Li, Ke Li, Xiangfei Kong
Neurocomputing (NEUCOM). 149: 275–284, 2015.
10.1016/j.neucom.2014.02.072
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@article{CaoKWLLK15,
author = {Jingjing Cao and
Sam Kwong and
Ran Wang and
Xiaodong Li and
Ke Li and
Xiangfei Kong},
title = {Class-specific soft voting based multiple extreme learning machines
ensemble},
journal = {Neurocomputing},
volume = {149},
pages = {275--284},
year = {2015},
url = {https://doi.org/10.1016/j.neucom.2014.02.072},
doi = {10.1016/j.neucom.2014.02.072},
timestamp = {Wed, 14 Nov 2018 10:26:17 +0100},
biburl = {https://dblp.org/rec/bib/journals/ijon/CaoKWLLK15},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Stable Matching Based Selection in Evolutionary Multiobjective Optimization
Ke Li, Qingfu Zhang, Sam Kwong, Miqing Li, Ran Wang
IEEE Trans. Evolutionary Computation (TEVC). 18(6): 909–923, 2014.
10.1109/TEVC.2013.2293776
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@article{LiZKLW14,
author = {Ke Li and
Qingfu Zhang and
Sam Kwong and
Miqing Li and
Ran Wang},
title = {Stable Matching-Based Selection in Evolutionary Multiobjective Optimization},
journal = {{IEEE} Trans. Evolutionary Computation},
volume = {18},
number = {6},
pages = {909--923},
year = {2014},
url = {https://doi.org/10.1109/TEVC.2013.2293776},
doi = {10.1109/TEVC.2013.2293776},
timestamp = {Sun, 23 Sep 2018 19:44:31 +0200},
biburl = {https://dblp.org/rec/bib/journals/tec/LiZKLW14},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Adaptive Operator Selection with Bandits for Multiobjective Evolutionary Algorithm Based on Decomposition
Ke Li, Álvaro Fialho, Sam Kwong, Qingfu Zhang
IEEE Trans. Evolutionary Computation (TEVC). 18(1): 114–130, 2014.
10.1109/TEVC.2013.2239648
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@article{LiFKZ14,
author = {Ke Li and
{\'{A}}lvaro Fialho and
Sam Kwong and
Qingfu Zhang},
title = {Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary
Algorithm Based on Decomposition},
journal = {{IEEE} Trans. Evolutionary Computation},
volume = {18},
number = {1},
pages = {114--130},
year = {2014},
url = {https://doi.org/10.1109/TEVC.2013.2239648},
doi = {10.1109/TEVC.2013.2239648},
timestamp = {Sun, 23 Sep 2018 19:44:31 +0200},
biburl = {https://dblp.org/rec/bib/journals/tec/LiFKZ14},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
A General Framework for Evolutionary Multiobjective Optimization via Manifold Learning
Ke Li, Sam Kwong
Neurocomputing (NEUCOM). 146: 65–74, 2014.
10.1016/j.neucom.2014.03.070
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@article{LiK14,
author = {Ke Li and
Sam Kwong},
title = {A general framework for evolutionary multiobjective optimization via
manifold learning},
journal = {Neurocomputing},
volume = {146},
pages = {65--74},
year = {2014},
url = {https://doi.org/10.1016/j.neucom.2014.03.070},
doi = {10.1016/j.neucom.2014.03.070},
timestamp = {Wed, 14 Nov 2018 10:26:16 +0100},
biburl = {https://dblp.org/rec/bib/journals/ijon/LiK14},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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Evolutionary Algorithms with Segment-based Search for Multiobjective Optimization Problems
Miqing Li, Shengxiang Yang, Ke Li, Xiaohui Liu
IEEE Trans. Cybernetics (TCYB). 44(8): 1295–1313, 2014.
10.1109/TCYB.2013.2282503
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@article{LiYLL14,
author = {Miqing Li and
Shengxiang Yang and
Ke Li and
Xiaohui Liu},
title = {Evolutionary Algorithms With Segment-Based Search for Multiobjective
Optimization Problems},
journal = {{IEEE} Trans. Cybernetics},
volume = {44},
number = {8},
pages = {1295--1313},
year = {2014},
url = {https://doi.org/10.1109/TCYB.2013.2282503},
doi = {10.1109/TCYB.2013.2282503},
timestamp = {Wed, 14 Nov 2018 10:31:34 +0100},
biburl = {https://dblp.org/rec/bib/journals/tcyb/LiYLL14},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Combining Interpretable Fuzzy Rule-based Classifiers via Multi-Objective Hierarchical Evolutionary Algorithm
Jingjing Cao, Hanli Wang, Sam Kwong, Ke Li
Proc. of 2011 IEEE International Conference on Systems, Mans and Cybernetics (SMC’11), IEEE Press: p. 1771–1776, October 2011.
10.1109/ICSMC.2011.6083928
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@inproceedings{CaoWKL11,
author = {Jingjing Cao and
Hanli Wang and
Sam Kwong and
Ke Li},
title = {Combining interpretable fuzzy rule-based classifiers via multi-objective
hierarchical evolutionary algorithm},
booktitle = {ICMLC'11: Proc. of the 2011 {IEEE} International Conference on Systems, Man
and Cybernetics},
pages = {1771--1776},
year = {2011},
url = {https://doi.org/10.1109/ICSMC.2011.6083928},
doi = {10.1109/ICSMC.2011.6083928},
timestamp = {Mon, 27 Nov 2017 16:55:26 +0100},
biburl = {https://dblp.org/rec/bib/conf/smc/CaoWKL11},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
JGBL paradigm: A Novel Strategy to Enhance the Exploration Ability of NSGA-II
Ke Li, Sam Kwong, Kim-Fung Man
Proc. of the 13th Annual Conference on Genetic and Evolutionary Computation (GECCO’11), ACM Press: p. 99–100, July 2011.
10.1145/2001858.2001915
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@inproceedings{LiKM11,
author = {Ke Li and
Sam Kwong and
Kim{-}Fung Man},
title = {{JGBL} paradigm: a novel strategy to enhance the exploration ability
of nsga-ii},
booktitle = {GECCO'11: Proc. of the 13th Annual Genetic and Evolutionary Computation Conference},
pages = {99--100},
year = {2011},
url = {https://doi.org/10.1145/2001858.2001915},
doi = {10.1145/2001858.2001915},
timestamp = {Tue, 06 Nov 2018 11:06:35 +0100},
biburl = {https://dblp.org/rec/bib/conf/gecco/LiKM11},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Multi-Objective Differential Evolution with Adaptive Control of Parameters and Operators
Ke Li, Álvaro Fialho, Sam Kwong
Proc. of the 5th International Conference on Learning and Intelligent OptimizatioN (LION’11), Springer Verlag, LNCS, p. 473–487, January 2011.
10.1007/978-3-642-25566-3_37
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@inproceedings{LiFK11,
author = {Ke Li and
{\'{A}}lvaro Fialho and
Sam Kwong},
title = {Multi-Objective Differential Evolution with Adaptive Control of Parameters
and Operators},
booktitle = {Learning and Intelligent Optimization - 5th International Conference,
{LION} 5, Rome, Italy, January 17-21, 2011. Selected Papers},
series = {Lecture Notes in Computer Science},
volume = {6683},
pages = {473--487},
publisher = {Springer},
year = {2011},
url = {https://doi.org/10.1007/978-3-642-25566-3\_37},
doi = {10.1007/978-3-642-25566-3\_37},
timestamp = {Tue, 14 May 2019 10:00:51 +0200},
biburl = {https://dblp.org/rec/conf/lion/LiFK11.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
A Novel Algorithm for Non-dominated Hypervolume-based Multiobjective Optimization
Ke Li, Jinhua Zheng, Miqing Li, Cong Zhou, Hui Lv
Proc. of 2009 IEEE International Conference on Systems, Mans and Cybernetics (SMC’09), IEEE Press: p. 5220–5226, December 2009.
10.1109/ICSMC.2009.5345983
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@inproceedings{LiZLZL09,
author = {Ke Li and
Jinhua Zheng and
Miqing Li and
Cong Zhou and
Hui Lv},
title = {A Novel Algorithm for Non-dominated Hypervolume-based Multiobjective
Optimization},
booktitle = {SMC'09: Proc. of the 2009 {IEEE} International Conference on Systems, Man
and Cybernetics},
pages = {5220--5226},
year = {2009},
url = {https://doi.org/10.1109/ICSMC.2009.5345983},
doi = {10.1109/ICSMC.2009.5345983},
timestamp = {Tue, 28 Nov 2017 16:18:09 +0100},
biburl = {https://dblp.org/rec/bib/conf/smc/LiZLZL09},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
An Spanning Tree Based Method For Pruning Non-Dominated Solutions in Multi- Objective Optimization Problems
Miqing Li, Jinhua Zheng, Ke Li, Jun Wu, Guixia Xiao
Proc. of 2009 IEEE International Conference on Systems, Mans and Cybernetics (SMC’09), IEEE Press: p. 4882–4887, December 2009.
10.1109/ICSMC.2009.5346322
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@inproceedings{LiZLWX09,
author = {Miqing Li and
Jinhua Zheng and
Ke Li and
Jun Wu and
Guixia Xiao},
title = {An Spanning Tree Based Method For Pruning Non-Dominated Solutions
in Multi-Objective Optimization Problems},
booktitle = {SMC'09: Proc. of the 2009 {IEEE} International Conference on Systems, Man
and Cybernetics},
pages = {4882--4887},
year = {2009},
url = {https://doi.org/10.1109/ICSMC.2009.5346322},
doi = {10.1109/ICSMC.2009.5346322},
timestamp = {Tue, 28 Nov 2017 16:18:09 +0100},
biburl = {https://dblp.org/rec/bib/conf/smc/LiZLWX09},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
Objective Reduction based on the Least Square Method for Large-dimensional Multiobjective Optimization Problem
Cong Zhou, Jinhua Zheng, Ke Li, Hui Lv
Proc. of the 5th International Conference on Natural Computation (ICNC’09), IEEE Press: p. 350–354, August 2009.
10.1109/ICNC.2009.40
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@inproceedings{ZhouZLL09,
author = {Cong Zhou and
Jinhua Zheng and
Ke Li and
Hui Lv},
title = {Objective Reduction Based on the Least Square Method for Large-Dimensional
Multi-objective Optimization Problem},
booktitle = {ICNC'09: Proc. of the 5th International Conference on Natural Computation},
pages = {350--354},
year = {2009},
url = {https://doi.org/10.1109/ICNC.2009.40},
doi = {10.1109/ICNC.2009.40},
timestamp = {Tue, 28 Nov 2017 16:18:09 +0100},
biburl = {https://dblp.org/rec/bib/conf/icnc/ZhouZLL09},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
The Convergence Analysis of Genetic Algorithm based on Space Mating
Hui Lv, Jinhua Zheng, Jun Wu, Cong Zhou, Ke Li
Proc. of the 5th International Conference on Natural Computation (ICNC’09), IEEE Press: p. 557–562, August 2009.
10.1109/ICNC.2009.39
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@inproceedings{LvZWZL09,
author = {Hui Lv and
Jinhua Zheng and
Jun Wu and
Cong Zhou and
Ke Li},
title = {The Convergence Analysis of Genetic Algorithm Based on Space Mating},
booktitle = {ICNC'09: Proc. of 5th International Conference on Natural Computation},
pages = {557--562},
year = {2009},
url = {https://doi.org/10.1109/ICNC.2009.39},
doi = {10.1109/ICNC.2009.39},
timestamp = {Tue, 28 Nov 2017 16:18:09 +0100},
biburl = {https://dblp.org/rec/bib/conf/icnc/LvZWZL09},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
-
An Improved Multi-objective Evolutionary Algorithm based on Differential Evolution
Ke Li, Jinhua Zheng
Proc. of 2009 WRI World Congress on Computer Science and Information Engineering (CSIE’09), IEEE Press: p. 825–830, March 2009.
10.1109/CSIE.2009.181
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@inproceedings{LiZZL09,
author = {Ke Li and
Jinhua Zheng and
Cong Zhou and
Hui Lv},
title = {An Improved Differential Evolution for Multi-objective Optimization},
booktitle = {CSIE'09: Proc. of the 2009 {WRI} World Congress on Computer Science and Information Engineering},
pages = {825--830},
year = {2009},
url = {https://doi.org/10.1109/CSIE.2009.181},
doi = {10.1109/CSIE.2009.181},
timestamp = {Tue, 28 Nov 2017 16:18:09 +0100},
biburl = {https://dblp.org/rec/bib/conf/csie/LiZZL09},
bibsource = {dblp computer science bibliography, https://dblp.org}
}