Yanan Sun

Yanan Sun

Professor, Sichuan University

Publications

*indicating the corresponding author

Authored Book/Chapter

  1. Yanan Sun, Gary G. Yen, Mengjie Zhang, “Evolutionary Deep Neural Architecture Search: Fundamentals, Methods, and Recent Advances” Springer, Hardcover ISBN: 978-3-031-16867-3, Published: 09 November 2022. DOI:https://doi.org/10.1007/978-3-031-16868-0 (XVI + 331 pages, the first book on evolutionary neural architecture search) Buy from Amazon
  2. Zeqiong Lv, Xiaotian Song, Yuqi Feng, Yuwei Ou, Yanan Sun*, Mengjie Zhang. “Evolutionary Neural Network Architecture Search”. In Handbook of Evolutionary Machine Learning, pp. 247-281, 2023. Singapore: Springer Nature Singapore. [http]

Journal Papers

  1. Zhanao Huang, Yongsheng Sang, Yanan Sun, Jiancheng Lv, “Neural networks learn specified information for imbalanced data classification,” IEEE Transactions on Knowledge and Data Engineering, 2024, DOI:10.1109/TKDE.2024.3392953.
  2. Yuqi Feng, Zeqiong lv, Hongyang Chen, Shangce Gao, Fengping An, Yanan Sun*, “LRNAS: Differentiable searching for adversarially robust lightweight neural architecture”, IEEE Transactions on Neural Networks and Learning Systems, 2024, DOI:10.1109/TNNLS.2024.3382724. [http] source code
  3. Shuchao Deng, Xiaotian Song, Minxiao Zhong, Qing Li, Yanan Sun*, Jiancheng lV, “A dynamic balanced physics-informed neural network for solving partial differential equations,” SCIENCE CHINA Information Sciences, 2024, DOI:10.1360/SSI-2023-0195. (In Chinese) [http] source code
  4. Yu Zhang, Pengxing Cai, Yanan Sun, Zhiming Zhang, Zhenyu Lei, Shangce Gao, “A lightweight multi-dendritic pyramidal neuron model with neural plasticity on image recognition,” IEEE Transactions on Artificial Intelligence, 2024, DOI:10.1109/TAI.2024.3379968. [http]
  5. Zeqiong Lv, Chao Qian, Gary Yen, Yanan Sun*, “Analyzing the expected hitting time of evolutionary computation-based neural architecture search algorithms,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2024, DOI:10.1109/TETCI.2024.3377683. [http]
  6. Yun Liu, Fangfang Zhang, Yanan Sun*, Mengjie Zhang, “Evolutionary trainer-based deep Q-network for dynamic flexible job shop scheduling,” IEEE Transactions on Evolutionary Computation, 2024, DOI:10.1109/TEVC.2024.3367181. [http] source code
  7. Hanyuan Huang, Tao Li, Beibei Li, Wenhao Wang, Yanan Sun, “A bidirectional differential evolution based unknown cyberattack detection system,” IEEE Transactions on Evolutionary Computation, 2024, DOI:10.1109/TEVC.2024.3365101. [http]
  8. Zeqiong Lv, Chao Qian, Yanan Sun*, “Benchmarking analysis of evolutionary neural architecture search,” IEEE Transactions on Evolutionary Computation, 2023, DOI:10.1109/TEVC.2023.3324852. [http]
  9. Rui Zhang, Yanan Sun*, Mengjie Zhang, “GPU based genetic programming for faster feature extraction in binary image classification,” IEEE Transactions on Evolutionary Computation, 2023, DOI:10.1109/TEVC.2023.3294639. [http] source code
  10. Shuchao Deng, Zeqiong Lv, Edgar Galván, Yanan Sun*, “Evolutionary neural architecture search for facial expression recognition,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 7, no. 5, pp. 1405-1419, 2023, DOI:10.1109/TETCI.2023.3289974. [http] source code
  11. Junhao Huang, Bing Xue, Yanan Sun*, Mengjie Zhang, Gary Yen, “Split-level evolutionary neural architecture search with elite weight inheritance,” IEEE Transactions on Neural Networks and Learning Systems, 2023, DOI:10.1109/TNNLS.2023.3269816. [http] source code
  12. Xiangning Xie, Yanan Sun*, Yuqiao Liu, Mengjie Zhang, Kay Chen Tan, “Architecture augmentation for performance predictor via graph isomorphism,” IEEE Transactions on Cybernetics, vol. 54, no. 3, pp. 1828-1840, 2024, DOI:10.1109/TCYB.2023.3267109. [http] Source code
  13. Zhanao Huang, Yongsheng Sang, Yanan Sun, Jiancheng Lv, “Neural network with a preference sampling paradigm for imbalanced data classification,” IEEE Transactions on Neural Networks and Learning Systems, 2022, DOI:10.1109/TNNLS.2022.3231917. [http]
  14. Junhao Huang, Bing Xue, Yanan Sun*, Mengjie Zhang, Gary Yen, “Particle swarm optimization for compact neural architecture search for image classification,” IEEE Transactions on Evolutionary Computation, vol. 27, no. 5, pp. 1298-1312, 2023, DOI:10.1109/TEVC.2022.3217290. [http] Source code
  15. Qing Ye, Yuhao Zhou, Mingjia Shi, Yanan Sun, Jiancheng Lv, “DLB: A dynamic load balance strategy for distributed training of deep neural networks,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 7, no. 4, pp. 1217-1227, 2023, DOI:10.1109/TETCI.2022.3220224. [http] Source code
  16. Zhanao Huang, Yongsheng Sang, Yanan Sun, Jiancheng Lv, “A neural network learning algorithm for highly imbalanced data classification,” Information Sciences, vol. 612, pp. 496-513, 2022, DOI:10.1016/j.ins.2022.08.074. [http] Source code
  17. Xiangning Xie, Yuqiao Liu, Yanan Sun*, Gary G. Yen, Bing Xue, Mengjie Zhang, “BenchENAS: A benchmarking platform for evolutionary neural architecture search,” IEEE Transactions on Evolutionary Computation, vol. 26, no. 6, pp. 1473-1485, 2022, DOI:10.1109/TEVC.2022.3147526. [http] Source code
  18. Yanan Sun, Gary G. Yen, Bing Xue, Mengjie Zhang, Jiancheng Lv, “ArcText: A unified text approach to describing convolutional neural network architectures,” IEEE Transactions on Artificial Intelligence, vol. 3, no. 4, pp. 526-540, 2022, DOI:10.1109/TAI.2021.3128502. [http] Source code  Research Frontier Paper (ONLY one per issue)
  19. Siyi Li, Yanan Sun*, Gary G. Yen, Mengjie Zhang, “Automatic design of convolutional neural network architectures under resource constraints”, IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 8, pp. 3832-3846, 2023. DOI:10.1109/TNNLS.2021.3123105. [http] Source code
  20. Yunhong Gong, Yanan Sun*, Dezhong Peng, Peng Chen, Zhongtai Yan, Ke Yang, “Analyze COVID-19 CT images based on evolutionary algorithm with dynamic searching space”, Complex & Intelligent Systems, vol. 7. pp. 3195-3209, 2021. DOI:10.1007/s40747-021-00513-8. [http] Source code
  21. Yuqiao Liu, Yanan Sun*, Bing Xue, Mengjie Zhang, Gary Yen, Kay Chen Tan, “A survey on evolutionary neural architecture search,” IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 2, pp. 550-570, 2023. DOI:10.1109/TNNLS.2021.3100554. [http]  Highly Cited Paper (TOP 1% worldwide) and also  Research Frontier Paper (ONLY one per issue)
  22. Yanan Sun, Xian Sun, Yuhan Fang, Gary G. Yen, Yuqiao Liu, “A novel training protocol for performance predictors of evolutionary neural architecture search algorithms,” IEEE Transactions on Evolutionary Computation, vol. 25, no. 3, pp. 524-536, 2021. DOI:10.1109/TEVC.2021.3055076. [http] Experimental Data
  23. Yao Chen, Yanan Sun*, Jiancheng Lv, Bijue Jia, Xiaoming Huang, “End-to-end heart sound segmentation using deep convolutional recurrent network,” Complex & Intelligent Systems, vol. 7, pp. 2103–2117, 2021. DOI:10.1007/s40747-021-00325-w. [http] Source code
  24. Xiangru Chen, Yanan Sun*, Mengjie Zhang, Dezhong Peng, “Evolving deep convolutional variational autoencoders for image classification,” IEEE Transactions on Evolutionary Computation, vol. 25, no. 5, pp. 815-829, 2021. DOI:10.1109/TEVC.2020.3047220. [http] Source code
  25. Qing Ye, Yanan Sun*, Jixin Zhang, Jiancheng Lv*, “A distributed framework for EA-based NAS,” IEEE Transactions on Parallel and Distributed Systems, vol. 32, no. 7, pp. 1753-1764, 2021. DOI:10.1109/TPDS.2020.3046774. [http] Source code
  26. Yao Chen, Jiancheng Lv, Yanan Sun, Bijue Jia, “Heart sound segmentation via duration long–short term memory neural network,” Applied Soft Computing, vol. 95, pp. 106540, 2020. DOI:10.1016/j.asoc.2020.106540. [http] Source code
  27. Yanan Sun, Bing Xue, Mengjie Zhang, Gary G. Yen, Jiancheng Lv, “Automatically designing CNN architectures using genetic algorithm for image classification,” IEEE Transactions on Cybernetics, vol. 50, no. 9, pp. 3840-3854, 2020. DOI:10.1109/TCYB.2020.2983860. [http] Source code ESI Hot Paper (TOP 0.1% worldwide) and also Highly Cited Paper (TOP 1% worldwide)
  28. Yanan Sun, Bing Xue, Mengjie Zhang, Gary G. Yen, “Completely automated CNN architecture design based on blocks,” IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 4, pp. 1242-1254, 2020. DOI: 10.1109/TNNLS.2019.2919608. [http] Source code Highly Cited Paper (TOP 1% worldwide) and also  Research Frontier Paper (ONLY one per issue)
  29. Yanan Sun, Bing Xue, Mengjie Zhang, Gary G. Yen, “Evolving deep convolutional neural networks for image classification,” IEEE Transactions on Evolutionary Computation, vol. 24, no. 2, pp. 394-407, 2020. DOI: 10.1109/TEVC.2019.2916183. [http] Source code Highly Cited Paper (TOP 1% worldwide) and also  ESI Hot Paper (TOP 0.1% worldwide) and also  Research Frontier Paper (ONLY one per issue)
  30. Yanan Sun, Handing Wang, Bing Xue, Yaochu Jin, Gary G. Yen, Mengjie Zhang, “Surrogate-assisted evolutionary deep learning using an end-to-end random forest-based performance predictor,” IEEE Transactions on Evolutionary Computation, vol. 24, no. 2, pp. 350-364, 2020. DOI:10.1109/TEVC.2019.2924461. [http] Source code
  31. Yanan Sun, Bing Xue, Mengjie Zhang, Gary G. Yen, “A new two-stage evolutionary algorithm for many-objective optimization,” IEEE Transactions on Evolutionary Computation, vol. 23, no. 5, pp. 748-761, 2019. DOI: 10.1109/TEVC.2018.2882166. [http] The source code has been integrated into the PlatEMO.
  32. Harith Al-Sahaf, Ying Bi, Qi Chen, Yi Mei, Yanan Sun, Binh Tran, Bing Xue, Mengjie Zhang (Alphabetical Order), “A survey on evolutionary machine learning,”Journal of the Royal Society of New Zealand, vol. 49, no. 2, pp. 205-228, 2019. DOI: 10.1080/03036758.2019.1609052. [http]
  33. Yanan Sun, Bing Xue, Mengjie Zhang, Gary G. Yen, “A particle swarm optimization-based flexible convolutional auto-encoder for image classification,” IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 8, pp. 2295-2309, 2019. DOI: 10.1109/TNNLS.2018.2881143. [http] Source code
  34. Yanan Sun, Gary G. Yen, Zhang Yi, “IGD indicator-based evolutionary algorithm for many-objective optimization problems,” IEEE Transactions on Evolutionary Computation, vol. 23, no. 2, pp.173-187, 2019. DOI: 10.1109/TEVC.2018.2791283. [http] The source code has been integrated into the PlatEMO. Highly Cited Paper (TOP 1% worldwide) and also ESI Hot Paper (TOP 0.1% worldwide)
  35. Yanan Sun, Gary G. Yen, Zhang Yi, “Evolving unsupervised deep neural networks for learning meaningful representations,” IEEE Transactions on Evolutionary Computation, vol. 23, no. 1, pp. 89-103, 2019. DOI: 10.1109/TEVC.2018.2808689. [http] Source code
  36. Yanan Sun, Gary G. Yen, Zhang Yi, “Improved regularity model-based EDA for many-objective optimization,” IEEE Transactions on Evolutionary Computation, vol. 22, no. 5, pp. 662-678, 2018. DOI: 10.1109/TEVC.2018.2794319. [http]
  37. Yanan Sun, Gary G. Yen, Zhang Yi, “Reference line-based estimation of distribution algorithm for many-objective optimization,” Knowledge-Based Systems, vol. 132, pp. 129-143, 2017. DOI: 10.1016/J.KNOSYS.2017.06.021. [http]
  38. Yanan Sun, Hua Mao, Yongsheng Sang, Zhang Yi, “Explicit guiding auto-encoders for learning meaningful representation,” Neural Computing and Applications, vol. 28, no. 3, pp. 429-436, 2017. DOI: 10.1007/S00521-015-2082-X. [http]
  39. Yanan Sun, Hua Mao, Quan Guo, Zhang Yi, “Learning a good representation with unsymmetrical auto-encoder,” Neural Computing and Applications, vol. 27, no. 5, pp. 1361-1367, 2016. DOI: 10.1007/S00521-015-1939-3. [http]

Conference Papers

  1. Han Ji, Yuqi Feng, Yanan Sun*, “CAP: A context-aware neural predictor for NAS,” The 33rd International Joint Conference on Artificial Intelligence (IJCAI2024), August 3-8, 2024, Jeju, South Korea.
  2. Aojun Lu, Tao Feng, Hangjie Yuan, Xiaotian Song, Yanan Sun*, “Revisiting neural networks for continual learning: an architectural perspective,” The 33rd International Joint Conference on Artificial Intelligence (IJCAI2024), August 3-8, 2024, Jeju, South Korea. source code
  3. Xiaotian Song, Andy Song, Rong Xiao, Yanan Sun*, “One-step spiking transformer with a linear complexity,” The 33rd International Joint Conference on Artificial Intelligence (IJCAI2024), August 3-8, 2024, Jeju, South Korea.source code
  4. Shasha Zhou, Mingyu Huang, Ke Li, Yanan Sun, “Evolutionary multi-objective optimization for contextual adversarial example generation,” The ACM International Conference on the Foundations of Software Engineering (FSE) 2024, July 17-19, 2024, Porto de Galinhas, Brazil.
  5. Zeqiong Lv, Chao Bian, Chao Qian, Yanan Sun*, “Runtime analysis of population-based evolutionary neural architecture search for a binary classification problem,” The Genetic and Evolutionary Computation Conference 2024 (GECCO2024), July 14-18, 2024, Melbourne, Australia.
  6. Yuwei Ou, Yuqi Feng, Yanan Sun*, “Towards accurate and robust architectures via neural architecture search,” The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 (CVPR2024), June 17-21, 2024, Seattle, USA. source code
  7. Yuqi Feng, Jian Zhang, Yanan Sun*, “Robust neural architecture search under long-tailed distribution,” International Joint Conference on Neural Networks 2024 (IJCNN2024), June 30-July 5, 2024, Yokohama, Japan.
  8. Xiao Yang, Yun Liu, Jiyuan Liu, Yanan Sun*, “HZS-NAS: Neural architecture search with hybrid zero-shot proxy for facial expression recognition,” International Joint Conference on Neural Networks 2024 (IJCNN2024), June 30-July 5, 2024, Yokohama, Japan.
  9. Jingrong Xie, Yuqi Feng, Yanan Sun*, “A sampling method for performance predictor based on contrastive learning,” AI 2023: Advances in Artificial Intelligence, pp, 215–226, Brisbane, Australia, 28th November-1st December, 2023. [http] Spotlight Paper
  10. Yuhao Zhou, Mingjia Shi, Yuanxi Li, Qing Ye, Yanan Sun, Jiancheng Lv, “Communication-efficient federated learning with single-step synthetic features compressor for faster convergence,” Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV2023), Paris, France, 2-6th October, 2023. [http]
  11. Junhao Huang, Bing Xue, Yanan Sun, Mengjie Zhang, “Multi-objective evolutionary search of compact convolutional neural networks with training-free estimation,” The Genetic and Evolutionary Computation Conference 2023 (GECCO2023), pp. 655–658, July 15-19, 2023, Lisbon (hybrid), Portuguese. [http]
  12. Yuqiao Liu, Yehui Tang, Zeqiong Lv, Yunhe Wang, Yanan Sun*, “Bridge the gap between architecture spaces via a cross-domain predictor,” The 36th Conference on Neural Information Processing Systems (NeurIPS2022), Hybrid Conference in New Orleans,USA, 28th November-9th December, 2022. [http] source code
  13. Junhao Huang, Bing Xue, Yanan Sun, Mengjie Zhang, “EDE-NAS: An eclectic differential evolution approach to single-path neural architecture search,” AI 2022: AI 2022: Advances in Artificial Intelligence, pp. 116-130, Perth, Western Australia, 5-8th December, 2022. [http] source code
  14. Jie Wu, Ben Feng, Yanan Sun*, “Genetic algorithm-based transformer architecture design for neural machine translation,” The 5th International Conference on Machine Learning and Machine Intelligence (MLMI2022), Hangzhou, China, 23-25th September, 2022. [http] Best Paper
  15. Rui Zhang, Andrew Lensen, Yanan Sun*, “Speeding up genetic programming based symbolic regression using GPUs,” PRICAI 2022: Trends in Artificial Intelligence, pp. 519-533, Shanghai, China, 10-13th November, 2022. [http] Source code
  16. Jie Wu, Yanan Sun*, “Adaptively joint pixel-wise semantic correlation in surface normal estimation,” International Joint Conference on Neural Networks (IJCNN 2022), Padua, Italy, 18-23th July, 2022. [http]
  17. Zilin Xiao, Yanan Sun*, “Exploring the effectiveness of appearance descriptor in DeepSORT,” International Joint Conference on Neural Networks (IJCNN 2022), Padua, Italy, 18-23th July, 2022. [http] Source code
  18. Shuchao Deng, Yanan Sun*, Galvan Edgar, “Neural architecture search using genetic algorithm for facial expression recognition,” The Genetic and Evolutionary Computation Conference 2022 (GECCO2022), pp. 423-426, July 9-13, 2022, Boston (hybrid), USA. [http] Source code
  19. Peng Zeng, Andrew Lensen, Yanan Sun*, “Large scale image classification using GPU-based genetic programming,” The Genetic and Evolutionary Computation Conference 2022 (GECCO2022), pp. 619–622, July 9-13, 2022, Boston (hybrid), USA. [http] source code
  20. Jie Wu, Yanan Sun*, “Evolving deep parallel neural networks for multi-task learning,” ICA3PP 2021: Algorithms and Architectures for Parallel Processing, pp. 517–531, 3-5 December, 2021, Xiamen, China. [http] Source code
  21. Yuhan Fang, Yuqiao Liu, Yanan Sun*, “Evolving deep neural networks for collaborative filtering,” ICONIP 2021: Neural Information Processing, pp. 230–238, 8-12 December, 2021, BALI, Indonesia. [http] Source code
  22. Yuqiao Liu, Yehui Tang, Yanan Sun*, “Homogeneous architecture augmentation for neural predictor,” Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV2021), pp. 12249-12258, 2021. [http] Source code
  23. Ben Feng, Dayiheng Liu, Yanan Sun*, “Evolving transformer architecture for neural machine translation,” Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO2021), pp. 273-274, 2021. DOI:10.1145/3449726.3459441. [http]
  24. Junhao Huang, Bing Xue, Yanan Sun, Mengjie Zhang, “A flexible variable-length particle swarm optimization approach to convolutional neural network architecture design,” Accepted by IEEE Congress on Evolutionary Computation 2021 (CEC2021), 28 June-1 July, Kraków, Poland (VIRTUAL), 2021. DOI: 10.1109/CEC45853.2021.9504716. [http] Source code Best Student Paper Nomination (ONLY four among >400 accepted papers)
  25. Xun Zhou, A.K. Qin, Yanan Sun, Kay Chen Tan, “A survey of advances in evolutionary neural architecture search,” Accepted by IEEE Congress on Evolutionary Computation 2021 (CEC2021), 28 June-1 July, Kraków, Poland (VIRTUAL), 2021, DOI:10.1109/CEC45853.2021.9504890. [http]
  26. Jindi Lv, Qing Ye, Yanan Sun, Juan Zhao, Jiancheng Lv, “Heart-Darts: Classification of heartbeats using differentiable architecture search,” Accepted by International Joint Conference on Neural Networks (IJCNN 2021), Virtual Event, 18-22th July, 2021, DOI:10.1109/IJCNN52387.2021.9534184. [http] Source code
  27. Wenxin Zhao, Yanan Sun, Bing Xue, “Improved bianry particle swarm optimization with evolutionary population dynamic for key oncogene selection,” Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI 2020), Canberra Australia, 1-4 December, 2020, PP. 897-904. DOI: 10.1109/SSCI47803.2020.9308540. [http]
  28. Yuqiao Liu, Yanan Sun, Bing Xue, Mengjie Zhang, “Evolving deep convolutional neural networks for hyperspectral image denoising,” Proceedings of International Joint Conference on Neural Networks (IJCNN 2020), Glasgow (UK), 19-24th July, 2020, DOI: 10.1109/IJCNN48605.2020.9207509. [http] Source code
  29. Qing Ye, Yuxuan Han, Yanan Sun, Jiancheng Lv, “PSO-PS:Parameter synchronization with particle swarm optimization for distributed training of deep neural networks,” Proceedings of International Joint Conference on Neural Networks (IJCNN 2020), Glasgow (UK), 19-24th July, 2020, DOI: 10.1109/IJCNN48605.2020.9207698. [http]
  30. William Irwin-Harris, Yanan Sun, Bing Xue, Mengjie Zhang, “A graph-based encoding for evolutionary convolutional neural network architecture design,” Proceedings of IEEE Congress on Evolutionary Computation 2019 (CEC2019), Wellington, New Zealand, 2019, pp. 546-553. DOI: 10.1109/CEC.2019.8790093. [http]
  31. Bin Wang, Yanan Sun, Bing Xue, Mengjie Zhang, “Evolving deep neural networks by multi-objective particle swarm optimization for image classification,” Proceedings of the Genetic and Evolutionary Computation Conference 2019 (GECCO2019), Prague, Czech Republic, 2019, PP. 490-498. DOI: 10.1145/3321707.3321735. [http]
  32. Bin Wang, Yanan Sun, Bing Xue, Mengjie Zhang, “A hybrid GA-PSO method for evolving architecture and short connections of deep convolutional neural networks,” PRICAI 2019: Trends in Artificial Intelligence, Yanuca Island, Cuvu, Fiji, 2019, pp. 650-663. DOI: 10.1007/978-3-030-29894-4_52. [http]
  33. Bin Wang, Yanan Sun, Bing Xue, Mengjie Zhang, “A hybrid differential evolution approach to designing deep convolutional neural networks for image classification,” AI 2018: Advances in Artificial Intelligence, Wellington, New Zealand, 2018, pp. 237-250. DOI: 10.1007/978-3-030-03991-2_24. [http]
  34. Yanan Sun, Bing Xue, Mengjie Zhang, Gary G. Yen, “An experimental study on hyper-parameter optimization for stacked auto-encoders,” Proceedings of IEEE Congress on Evolutionary Computation 2018 (CEC2018), Rio de Janeiro, Brazil, 2018, pp. 638-645. DOI: 10.1109/CEC.2018.8477921. [http]
  35. Bin Wang, Yanan Sun, Bing Xue, Mengjie Zhang, “Evolving deep convolutional neural networks by variable-length particle swarm optimization for image classification,” Proceedings of IEEE Congress on Evolutionary Computation 2018 (CEC2018), Rio de Janeiro, Brazil, 2018, pp. 1514-1521. DOI: 10.1109/CEC.2018.8477735. [http]
  36. Yanan Sun, Gary G. Yen, Zhang Yi, “Global View-based selection mechanism for many-objective evolutionary algorithm,” Proceedings of IEEE Congress on Evolutionary Computation 2017 (CEC2017), Donostia-San Sebastián, Spain, 2017, pp. 427-434. DOI: 10.1109/CEC.2017.7969343. [http]
  37. Yanan Sun, Gary G. Yen, Hua Mao, Zhang Yi, “Manifold dimension reduction based clustering for multi-objective evolutionary algorithm,” Proceedings of IEEE Congress on Evolutionary Computation 2016 (CEC2016), Vancouver, Canada, 2016, pp. 3785-3792. DOI: 10.1109/CEC.2016.7744269. [http]