深度神经网络优化，终身学习

   

081201-计算机系统结构

​深度神经网络优化, 终身学习

2006-09--2010-08   中国科学院计算技术研究所   工学博士
2003-09--2006-07   合肥工业大学计算机与信息学院   工学硕士
1999-09--2003-07   合肥工业大学计算机与信息学院   工学学士

   

2023-09~现在, 中国科学院计算技术研究所, 副研究员
2014-09~2023-09,中国科学院计算技术研究所, 高级工程师
2013-01~2014-09,中国科学院计算技术研究所, 助理研究员
2010-09~2013-01,中国科学院计算技术研究所, 博士后

2024-07-26-今,中国计算机学会分布式计算与系统专业委员会, 执行委员
2024-05-17-今,中国指挥与控制学会大模型与决策智能专业委员会, 委员
2013-08-01-今,中国计算机学会, 高级会员

[1] CN202010937149.8，一种基于局部关系指导的图像分割方法，安竹林; 许开强; 程坦; 徐勇军

[2] CN202010162181.3，一种深度神经网络的可解释生成方法，安竹林; 胡小龙; 程坦; 徐勇军

[3] CN202010059647.7，一种相似特征测试数据集生成方法，安竹林; 孙涛; 程坦; 徐勇军

[4] CN202010937140.7，一种基于增强特征表示的图像分割方法，安竹林; 许开强; 程坦; 徐勇军

[5] CN202110918571.3，一种多特征融合计算识别胶质瘤复发与坏死的方法，蔡小红; 张勤; 安竹林

[6] CN202110598353.6，一种实体标准化方法，曾志贤; 马涛; 倪斌; 汪姿如; 庄福振; 安竹林

[7] CN202011186817.4，一种基于主动学习的样本标注方法，陈能; 安竹林; 徐勇军; 程坦

[8] CN202110623005.X，一种基于视频的行人垃圾扔投次数统计方法，何森勖; 程坦; 徐勇军; 安竹林

[9] CN202011086121.4，一种多图片集曝光分布差异的衡量方法，何森勖; 程坦; 徐勇军; 安竹林

[10] CN202011182517.9，一种基于结构光摄像头的3D人脸识别方法，胡雨; 安竹林; 张章斌; 徐勇军; 程坦

[11] CN202011099237.1，一种基于BERT与先验知识特征的关系五元组抽取方法，马涛; 倪斌; 童逸琦; 汪姿如; 庄福振; 安竹林; 等

[12] CN202011182518.3，一种融合知识的对话生成方法，倪斌; 庄福振; 安竹林; 程坦; 徐勇军; 陆晓蕾; 马涛; 童逸琦

[13] CN202011186818.9，一种基于元学习的领域增量方法，王杰龙; 安竹林; 程坦; 徐勇军

[14] CN202110521364.4，一种基于数据转换和知识蒸馏的域增量学习方法，王杰龙; 安竹林; 程坦; 徐勇军

[15] CN202110571011.5，一种在方舱类建筑中生成动线规划的方法，余孟达; 安竹林

[16] CN202010186717.5，一种基于不同粒度特征匹配一致性的物体重识别方法，钟剑斌; 安竹林; 程坦; 徐勇军

[17] CN202011182514.5，一种乳腺钼靶图像中胸肌和乳头区域的分割预标注方法，钟剑斌; 徐勇军; 程坦; 安竹林

[18] CN202111157928.7，一种基于运动增强特征的水流测速方法，钟剑斌; 徐勇军; 程坦; 安竹林

会议论文： 

[1] Han Yang, Chuanguang Yang*, Qiuli Wang, Zhulin An*, Weilun Feng, Libo Huang, Yongjun Xu. Multi-party Collaborative Attention Control for Image Customization. The Thirty-Fifth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025. (CCF-A) 

[2] Chuanguang Yang, Xinqiang Yu, Han Yang, Zhulin An*, Chengqing Yu, Libo Huang, Yongjun Xu. Multi-Teacher Knowledge Distillation with Reinforcement Learning for Visual Recognition. The 39th AAAI Conference on Artificial Intelligence (AAAI), 2025. (CCF-A) 

[3] Weilun Feng, Haotong Qin, Chuanguang Yang*, Zhulin An*, Libo Huang, Boyu Diao, Fei Wang, Renshuai Tao, Yongjun Xu, Michele Magno. MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models. The 39th AAAI Conference on Artificial Intelligence (AAAI), 2025. (CCF-A) 

[4] Han Yang, Chuanguang Yang*, Zhulin An*, Libo Huang, Yongjun Xu. HSRDiff: A Hierarchical Self-Regulation Diffusion Model for Stochastic Semantic Segmentation. The 39th AAAI Conference on Artificial Intelligence (AAAI), 2025. (CCF-A) 

[5] Haonan Mai, Libo Huang*, Zhulin An*, Jiarui Zhao, Chuanguang Yang, Erhu Zhao, Yongjun Xu. OLN++: Improved Object Localization Network for Open-world Object Detection. 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025. (CCF-B) 

[6] RuiQi Liu, Boyu Diao*, Libo Huang, Zijia An, Zhulin An, Yongjun Xu. Continual Learning in the Frequency Domain. The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024. (CCF-A) 

[7] Weilun Feng, Chuanguang Yang*, Zhulin An*, Libo Huang, Boyu Diao, Fei Wang, Yongjun Xu. Relational Diffusion Distillation For Efficient Image Generation. ACM Multimedia 2024 (ACM MM), 2024.(CCF-A) 

[8] Yuting Zhang, Zhao Zhang, Yiqing Wu, Ying Sun, Fuzhen Zhuang*, Wenhui Yu, Lantao Hu, Han Li, Kun Gai, Zhulin An*, Yongjun Xu. Tag Tree-Guided Multi-grained Alignment for Multi-Domain Short Video Recommendation. ACM Multimedia 2024 (ACM MM), 2024.(CCF-A) 

[9] Yuting Zhang, Yiqing Wu, ruidong han, Ying Sun, Yongchun Zhu, Xiang Li, Wei Lin, Fuzhen Zhuang*, Zhulin An*, Yongjun Xu. Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation. 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024. (CCF-A, ADS Track)

[10] Chuanguang Yang, Zhulin An*, Libo Huang, Junyu Bi, XinQiang Yu, Han Yang, Boyu Diao, Yongjun Xu*. CLIP-KD: A Comprehensive Study of Distilling CLIP Models. The Thirty-Fourth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024. (CCF-A) 

[11] Libo Huang, Yan Zeng, Chuanguang Yang, Zhulin An*, Boyu Diao, Yongjun Xu. eTag: Class-Incremental Learning via Embedding Distillation and Task-Oriented Generation. 36th AAAI Conference on Artificial Intelligence (AAAI), 2024. (CCF-A) 

[12] Libo Huang, Zhulin An*, Yan Zeng, Xiang Zhi, Yongjun Xu. KFC: Knowledge Reconstruction and Feedback Consolidation Enable Efficient and Effective Continual Generative Learning. The Twelfth International Conference on Learning Representations (ICLR), 2024. (Tiny paper, Invite to present (notable)) 

[13] Yuting Zhang, Yiqing Wu, Ran Le, Yongchun Zhu, Fuzhen Zhuang*, Ruidong Han, Xiang Li, Wei Lin, Zhulin An*, Yongjun Xu. Modeling Dual Period-Varying Preferences for Takeaway Recommendation. 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (CCF-A, ADS Track) 

[14] Zhao Zhang, Zhanpeng Guan, Fuwei Zhang, Fuzhen Zhuang*, Zhulin An*, Fei Wang, Yongjun Xu. Weighted Knowledge Graph Embedding. 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023. (CCF-A) 

[15] Chuanguang Yang, Zhulin An*, Helong Zhou, Linhang Cai, Xiang Zhi, Jiwen Wu, Yongjun Xu, Qian Zhang. MixSKD: Self-Knowledge Distillation from Mixup for Image Recognition. European Conference on Computer Vision (ECCV), 2022. (CCF-B) 

[16] Chuanguang Yang, Helong Zhou, Zhulin An*, Xue Jiang, Yongjun Xu, Qian Zhang. Cross-Image Relational Knowledge Distillation for Semantic Segmentation. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. (CCF-A) 

[17] Chuanguang Yang, Zhulin An*, Yongjun Xu. Localizing Semantic Patches for Accelerating Image Classification. IEEE International Conference on Multimedia and Expo (ICME), 2022. (CCF-B) 

[18] Yanming Chen, Mingrui Shuai, Shubin Lou, Zhulin An*, Yiwen Zhang. FPAR: Filter Pruning via Attention and Rank Enhancement. IEEE International Conference on Multimedia and Expo (ICME), 2022. (CCF-B) 

[19] Chuanguang Yang, Zhulin An*, Linhang Cai, Yongjun Xu. Mutual Contrastive Learning for Visual Representation Learning. 36th AAAI Conference on Artificial Intelligence (AAAI), 2022. (CCF-A) 

[20] Linhang Cai, Zhulin An*, Chuanguang Yang, Yangchun Yan, Yongjun Xu. Prior Gradient Mask Guided Pruning-aware Fine-tuning. 36th AAAI Conference on Artificial Intelligence (AAAI), 2022. (CCF-A) 

[21] Chuanguang Yang, Zhulin An*, Linhang Cai, Yongjun Xu. Hierarchical Self-supervised Augmented Knowledge Distillation. 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021. (CCF-A) 

[22] Chuanguang Yang, Zhulin An*, Yongjun Xu. Multi-view Contrastive Learning for Online Knowledge Distillation. 46th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021. (CCF-B) 

[23] Linhang Cai, Zhulin An*, Yongjun Xu. GHFP: Gradually Hard Filter Pruning. International Joint Conference on Neural Networks (IJCNN), 2021. (CCF-C) 

[24] Chuanguang Yang, Zhulin An*, Hui Zhu, Xiaolong Hu, Kun Zhang, Kaiqiang Xu, Chao Li, Yongjun Xu. Gated Convolutional Networks with Hybrid Connectivity for Image Classification. 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. (CCF-A) 

[25] Xiaolong Hu, Zhulin An*, Chuanguang Yang, Hui Zhu, Kaiqiang Xu and Yongjun Xu. DRNet: Dissect and Reconstruct the Convolutional Neural Network via Interpretable Manners. 24th European Conference on Artificial Intelligence (ECAI), 2020. (CCF-B) 

期刊论文： 

[1] Longji Zhu, Yunan Yang, Fei Xu, Xinyu Lu, Mingrui Shuai, Zhulin An, et al. Open-set deep learning–enabled single-cell Raman spectroscopy for rapid identification of airborne pathogens in real-world environments. Science Advances. 11(2), 2025. (CCF-C, SCI Q1 IF:11.7) 

[2] Wenyu Mi, Jianji Wang, Fuzhen Zhuang, Zhulin An, Wei Guo. Open-category referring expression comprehension via multi-modal knowledge transfer. Neurocomputing. 598, 2024. (SCI Q1 IF:5.5) 

[3] LiRong Dai, Luqi Gong, Zhulin An, Yongjun Xu, Boyu Diao. Sketch-fusion: A gradient compression method with multi-layer fusion for communication-efficient distributed training. Journal of Parallel and Distributed Computing. 185, 2024. (SCI Q1 IF:3.4) 

[4] Huishi Luo, Fuzhen Zhuang*, Ruobing Xie, Hengshu Zhu, Deqing Wang, Zhulin An, Yongjun Xu. A survey on causal inference for recommendation. The Innovation. 5(2), 2024. (SCI Q1 IF:32.1) 

[5] Chuanguang Yang, Zhulin An*, Linhang Cai, and Yongjun Xu. Knowledge Distillation Using Hierarchical Self-Supervision Augmented Distribution. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 35(2), 2024. (CCF-B, SCI Q1 IF:10.4) 

[6] Yanming Chen, Jiahao Xu, Zhulin An*, Fuzhen Zhuang. Multi-scale Conditional Reconstruction Generative Adversarial Network, Image and Vision Computing. 141, 2024. (CCF-C, SCI Q3 IF:4.7) 

[7] Yanming Chen, Gang Wu, Mingrui Shuai, Shubin Lou, Yiwen Zhang, Zhulin An*. FPAR: Flter Pruning via Atention and Rank Enhancement for Deep Convolutional Neural Networks Acceleration, International Journal of Machine Learning and Cybernetics, 15, 2024. (SCI Q3 IF:5.6) 

[8] Han Yang, Qiuli Wang, Yue Zhang, Zhulin An, Liu Chen, Xiaohong Zhang, and S. Kevin Zhou*. Lung Nodule Segmentation and Uncertain Region Prediction with an Uncertainty-Aware Attention Mechanism. IEEE Transactions on Medical Imaging (TMI), 43(4), 2024. (SCI Q1 IF:6.812) 

[9] Chuanguang Yang, Zhulin An*, Helong Zhou, Fuzhen Zhuang, Yongjun Xu, Qian Zhang. Online Knowledge Distillation via Mutual Contrastive Learning for Visual Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(8), 2023. (CCF-A, SCI Q1 IF:24.314) 

[10] Yuting Zhang, Ying Sun, Fuzhen Zhuang*, Yongchun Zhu, Zhulin An*, Yongjun Xu. Triple Dual Learning for Opinion-Based Explainable Recommendation. ACM Transactions on Information Systems (TOIS), 42(3), 2023. (CCF-A, SCI Q1 IF:5.6) 

[11] Y Xu, X Liu, X Cao, et al. Artificial intelligence: A powerful paradigm for scientific research. The Innovation. 2(4), 2021. 

[12] Chuanguang Yang, Xinqiang Yu, Zhulin An, Yongjun Xu. Categories of Response-Based, Feature-Based, and Relation-Based Knowledge Distillation. Chapter in Springer Book《Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems》, 2023.

   

（ 1 ） 基于知识蒸馏的扩散模型训练和推理优化方法研究, 负责人, 国家任务, 2025-01--2028-12

已指导学生

许开强  硕士研究生  085211-计算机技术  

朱徽  硕士研究生  085211-计算机技术  

胡小龙  硕士研究生  085211-计算机技术  

蔡林航  硕士研究生  085211-计算机技术  

支相  硕士研究生  085404-计算机技术  

王军凯  硕士研究生  085404-计算机技术  

王劲  硕士研究生  085400-电子信息  

董世超  硕士研究生  081201-计算机系统结构  

章玉婷  硕士研究生  081202-计算机软件与理论  

现指导学生

杨晗  硕士研究生  081200-计算机科学与技术  

王煜  硕士研究生  081200-计算机科学与技术  

李祥琦  硕士研究生  081200-计算机科学与技术