Yanan Sun

Yanan Sun

Professor, Sichuan University

Conference Publications

*indicating the corresponding author

  1. Xiaotian Song, Peng Zeng, Yanan Sun*, Andy Song, “Generalizable symbolic optimizer learning,” The 18th European Conference on Computer Vision (ECCV2024), September 29-October 4, 2024, MiCo Milano, Italy. source code
  2. Xiaotian Song, Shuchao Deng, Jiahao Fan, Yanan Sun*, “Physics-informed neural networks with generalized residual-based adaptive sampling,” 2024 International Conference on Intelligent Computing (ICIC2024), August 5-8, 2024, Tianjin, China. [http]
  3. Minxiao Zhong, Yuqi Feng, Qing Li, Yanan Sun*, “Precisely Predicting neutronics parameters of nuclear reactor,” 2024 International Conference on Intelligent Computing (ICIC2024), August 5-8, 2024, Tianjin, China. [http]
  4. Lin Lu, Chenxi Dai, Wangcheng Tao, Binhang Yuan, Yanan Sun, Pan Zhou, “Exploring the robustness of pipeline-parallelism-based decentralized training,” The Forty-first International Conference on Machine Learning (ICML2024), vol. 235, pp. 32978–32989, July 21-27, 2024, Vienna, Austria. [http] source code
  5. Han Ji, Yuqi Feng, Yanan Sun*, “CAP: A context-aware neural predictor for NAS,” The 33rd International Joint Conference on Artificial Intelligence (IJCAI2024), pp. 4219-4227, August 3-8, 2024, Jeju, South Korea. [http] source code
  6. 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), pp. 4651-4659, August 3-8, 2024, Jeju, South Korea. [http] source code
  7. 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), pp. 3142-3150, August 3-8, 2024, Jeju, South Korea. [http] source code
  8. 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. [http] source code
  9. 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.
  10. 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), pp. 5967-5976, June 17-21, 2024, Seattle, USA. [http] source code
  11. 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.
  12. 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.
  13. 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
  14. 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]
  15. 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]
  16. 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
  17. 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
  18. 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
  19. 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
  20. 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]
  21. 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
  22. 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
  23. 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
  24. 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
  25. 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
  26. 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
  27. 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]
  28. 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)
  29. 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]
  30. 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
  31. 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]
  32. 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
  33. 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]
  34. 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]
  35. 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]
  36. 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]
  37. 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]
  38. 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]
  39. 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]
  40. 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]
  41. 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]