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    陈军

    • 讲师
    • 性别 : 男
    • 毕业院校 : 浙江大学
    • 学历 : 博士研究生毕业
    • 学位 : 博士学位
    • 在职信息 : 在岗
    • 所在单位 : 儿童发展与教育学院
    • 入职时间 : 2024-06-12
    • 办公地点 : 浙江师范大学萧山校区
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    个人简介

    陈军,博士,浙江师范大学“双龙学者”特聘教授。主要研究方向为神经网络压缩、流形优化和分布式优化,在JMLR、TPAMI、TNNLS、TOG等计算机领域权威期刊,以及ICCV、ECCV、AAAI、ICLR、NeurIPS等计算机领域顶级会议发表论文30余篇,其中一作/共同一作9篇,通讯作者5篇。相关成果于2021年获得浙江省科技进步奖一等奖。更多内容请关注Google Scholar主页:https://scholar.google.com/citations?user=YKc2O78AAAAJ&hl=en


    1.1期刊论文

    [1] Jun Chen, Hanwen Chen, Mengmeng Wang, Guang Dai, Ivor W. Tsang, and Yong Liu. “Learning Discretized Neural Networks under Ricci Flow.” Journal of Machine Learning Research, 2024, 25(386): 1-44.

    [2] Jun Chen*, Jingyang Xiang, Tianxin Huang, Xiangrui Zhao, and Yong Liu. “Hyperbolic Binary Neural Network.” IEEE Transactions on Neural Networks and Learning Systems, 2024.

    [3] Tianyi Zhu, Lina Liu, Yibo Sun, Zhi Lu, Yuanlong Zhang, Chao Xu, and Jun Chen*. "Semi-supervised noise-resilient anomaly detection with feature autoencoder." Knowledge-Based Systems, 2024, 304: 112445.

    [4] Siqi Li, Jun Chen, Shanqi Liu, Chengrui Zhu, Guanzhong Tian, and Yong Liu. “MCMC: Multi-Constrained Model Compression via One-Stage Envelope Reinforcement Learning.” IEEE Transactions on Neural Networks and Learning Systems, 2024.

    [5] Shanqi Liu, Weiwei Liu, Wenzhou Chen, Guanzhong Tian, Jun Chen, Yao Tong, Junjie Cao, and Yong Liu. "Learning multi-agent cooperation via considering actions of teammates." IEEE Transactions on Neural Networks and Learning Systems, 2023, 35(8): 11553-11564.

    [6] Yuang Liu1, Jun Chen1, and Yong Liu. "DCCD: Reducing Neural Network Redundancy via Distillation." IEEE Transactions on Neural Networks and Learning Systems, 2023, 35(7): 10006-10017.

    [7] Tianxin Huang, Jiangning Zhang, Jun Chen, Zhonggan Ding, Ying Tai, Zhenyu Zhang, Chengjie Wang, and Yong Liu. "3qnet: 3d point cloud geometry quantization compression network." ACM Transactions on Graphics (TOG), 2022, 41(6): 1-13.

    [8] Mengmeng Wang, Jiazheng Xing, Jing Su, Jun Chen, and Yong Liu. "Learning spatiotemporal and motion features in a unified 2d network for action recognition." IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 45(3): 3347-3362.

    [9] Jun Chen, Liang Liu, Yong Liu, and Xianfang Zeng. "A learning framework for n-bit quantized neural networks toward FPGAs." IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(3): 1067-1081.

    [10] Guanzhong Tian, Yiran Sun, Yuang Liu, Xianfang Zeng, Mengmeng Wang, Yong Liu, Jiangning Zhang, and Jun Chen. "Adding before pruning: Sparse filter fusion for deep convolutional neural networks via auxiliary attention." IEEE Transactions on Neural Networks and Learning Systems, 2021.

    [11] Jun Chen, Yong Liu, Hao Zhang, Shengnan Hou, and Jian Yang. "Propagating asymptotic-estimated gradients for low bitwidth quantized neural networks." IEEE Journal of Selected Topics in Signal Processing, 2020, 14(4): 848-859.

     

    1.2 会议论文

    [1] Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor W Tsang, and Yong Liu. "Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold. " International Conference on Learning Representations (ICLR), 2024.

    [2] Yuzhe Yao, Feng Tian, Jun Chen*, Haonan Lin, Guang Dai, Yong Liu, and Jingdong Wang. " Timestep-Aware Correction for Quantized Diffusion Models." In European Conference on Computer Vision (ECCV), pp. 215-232. Cham: Springer Nature Switzerland, 2024.

    [3] Jiateng Wei, Quan Lu, Ning Jiang, Siqi Li, Jingyang Xiang, Jun Chen*, and Yong Liu. "Structured Optimal Brain Pruning for Large Language Models." Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 13991-14007. 2024.

    [4] Jingyang Xiang, Siqi Li, Jun Chen, Guang Dai, Shipeng Bai, Yukai Ma, and Yong Liu. "SUBP: Soft Uniform Block Pruning for 1xN Sparse CNNs Multithreading Acceleration." In Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 36, 2024.

    [5] Mengmeng Wang, Jiazheng Xing, Boyuan Jiang, Jun Chen, Jianbiao Mei, Xingxing Zuo, Guang Dai, Jingdong Wang, and Yong Liu. "A Multimodal, Multi-Task Adapting Framework for Video Action Recognition." In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), vol. 38, no. 6, pp. 5517-5525. 2024.

    [6] Xintian Shen, Jiangning Zhang, Jun Chen, Shipeng Bai, Yue Han, Yabiao Wang, Chengjie Wang, and Yong Liu. "Learning Global-aware Kernel for Image Harmonization." In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 7535-7544. 2023.

    [7] Tianxin Huang, Xuemeng Yang, Jiangning Zhang, Jinhao Cui, Hao Zou, Jun Chen, Xiangrui Zhao, and Yong Liu. "Learning to train a point cloud reconstruction network without matching." In European Conference on Computer Vision (ECCV), pp. 179-194. Cham: Springer Nature Switzerland, 2022.

    [8] Tianxin Huang, Jiangning Zhang, Jun Chen, Yuang Liu, and Yong Liu. "Resolution-free point cloud sampling network with data distillation." In European Conference on Computer Vision (ECCV), pp. 54-70. Cham: Springer Nature Switzerland, 2022.

    [9] Xiangrui Zhao, Sheng Yang, Tianxin Huang, Jun Chen, Teng Ma, Mingyang Li, and Yong Liu. "Superline3d: Self-supervised line segmentation and description for lidar point cloud." In European Conference on Computer Vision (ECCV), pp. 263-279. Cham: Springer Nature Switzerland, 2022.

    教育经历

    2012.9 -- 2016.6
    中国计量大学       机电工程       大学本科毕业       学士学位

    2017.9 -- 2020.3
    浙江大学       控制工程       硕士研究生毕业       硕士学位

    2020.9 -- 2024.3
    浙江大学       控制科学与工程       博士研究生毕业       博士学位

    研究方向

  • 机器学习,模型压缩,分布式优化,流形学习