Weizhong Zhang
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Publications (*equal contribution，#corresponding author)

My Google Scholar.

  • Low Precision Local Training is Enough for Federated Learning.
    Zhiwei Li*, Yiqiu Li*, Binbin Lin, Zhongming Jin, Weizhong Zhang#.
    The 38th Annual Conference on Neural Information Processing Systems, 2024. (NeurIPS 2024)

  • Efficient Denoising Diffusion via Probabilistic Masking
    Weizhong Zhang#, Zhiwei Zhang, Renjie Pi, Zhongming Jin, Yuan Gao, Jieping Ye, Kaini Chen.
    International Conference on Machine Learning, 2024. (ICML 2024)

  • PoseIRM: Enhance 3D Human Pose Estimation on Unseen Camera Settings via Invariant Risk Minimization.
    Yanlu Cai, Weizhong Zhang#, Yuan Wu, Cheng Jin#.
    IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 2124-2133. 2024. (CVPR 2024)

  • High Fidelity Person-centric Subject-to-Image Synthesis.
    Yibin Wang*, Weizhong Zhang*, Jianwei Zheng, Cheng Jin.
    IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 7675-7684. 2024. (CVPR 2024)

  • FusionFormer: A Concise Unified Feature Fusion Transformer for 3D Pose Estimation.
    Yanlu Cai, Weizhong Zhang#, Yuan Wu, Cheng Jin#..
    AAAI Conference on Artificial Intelligence, vol. 38, no. 2, pp. 900-908. 2024. (AAAI 2024)

  • Future Motion Dynamic Modeling via Hybrid Supervision for Multi-Person Motion Prediction Uncertainty Reduction.
    Yan Zhuang, Yanlu Cai, Weizhong Zhang#, Cheng Jin#.
    ACM Multimedia 2024 (ACM MM 2024)

  • PrimeComposer: Faster Progressively Combined Diffusion for Image Composition with Attention Steering.
    Yibin Wang, Weizhong Zhang*, Jianwei Zheng Cheng Jin#.
    ACM Multimedia 2024 (ACM MM 2024)

  • Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost.
    Yuan Gao, Weizhong Zhang, Wenhan Luo, Lin Ma, Jin-Gang Yu, Gui-Song Xia, Jiayi Ma.
    International Conference on Learning Representations, 2024. (ICLR 2024)

  • DynaFed: Tackling Client Data Heterogeneity with Global Dynamics.
    Weizhong Zhang*#, Renjie Pi*, Yueqi Xie*, Jiahui Gao, Xiaoyu Wang, Sunghun Kim, Qifeng Chen.
    IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 12177-12186, 2023. (CVPR 2023)

  • Fast adversarial training with adaptive step size.
    Zhichao Huang, Yanbo Fan, Chen Liu, Weizhong Zhang, Yong Zhang, Mathieu Salzmann, Sabine Süsstrunk, Jue Wang.
    IEEE Transactions on Image Processing. 2023. (TIP 2023)

  • Pose-Motion Video Anomaly Detection via Memory-Augmented Reconstruction and Conditional Variational Prediction
    Weilin Wan, Weizhong Zhang, Cheng Jin.
    IEEE International Conference on Multimedia and Expo, pp. 2729-2734, 2023. (ICME 2023)

  • A Holistic View of Noise Transition Matrix in Deep Learning and Beyond.
    Yong Lin, Renjie Pi, Weizhong Zhang, Xiaobo Xia, Jiahui Gao, Xiaozhou, Tongliang Liu, Bo Han.
    International Conference on Learning Representations, 2023.(ICLR 2023)

  • Self-Guided Noise-Free Data Generation For Efficient Zero-Shot Learning.
    Jiahui Gao, Renjie Pi, LIN Yong, Hang Xu, Jiacheng Ye, Zhiyong Wu, Weizhong Zhang, Xiaodan Liang, Zhenguo Li, Lingpeng Kong.
    International Conference on Learning Representations, 2023.(ICLR 2023)

  • Probabilistic Bilevel Coreset Selection.
    Weizhong Zhang*, Xiao Zhou*, Renjie Pi*, Yong Lin, Tong Zhang.
    International Conference on Machine Learning, pp. 27287-27302, 2022. (ICML 2022)

  • Finding Dynamics Preserving Adversarial Winning Tickets.
    Xupeng Shi, Pengfei Zheng, A. Adam Ding, Yuan Gao, Weizhong Zhang#.
    International Conference on Artificial Intelligence and Statistics, pp. 510-528, 2022. (AISTATS 2022)

  • Convex Formulation of Overparameterized Deep Neural Networks.
    Cong Fang, Yihong Gu, Weizhong Zhang, and Tong Zhang.
    IEEE Transactions on Information Theory,68(8): 5340-5352, 2022(IEEE TIT 2022)

  • Model Agnostic Sample Reweighting for Out-of-Distribution Learning.
    Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang.
    International Conference on Machine Learning, pp. 27203-27221, 2022. (ICML 2022)

  • Content-aware recommendation via Dynamic Heterogeneous Graph Convolutional Network.
    Tingting Liang, Lin Ma, Weizhong Zhang, Haoran Xu, Congying Xia, and Yuyu Yin.
    Knowledge-Based Systems (2022): 109185.

  • Effective Sparsification of Neural Networks with Global Sparsity Constraint.
    Weizhong Zhang*, Xiao Zhou*, Hang Xu, Tong Zhang.
    IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 3599-3608, 2021. (CVPR 2021)

  • Efficient Neural Network Training via Forward and Backward Propagation Sparsification.
    Weizhong Zhang*, Xiao Zhou*, Zonghao Chen, Shizhe Diao, Tong Zhang.
    The 32nd Annual Conference on Neural Information Processing Systems 34(2021). (Neurips 2021)

  • How to Characterize The Landscape of Overparameterized Convolutional Neural Networks.
    Weizhong Zhang*, Yihong Gu*, Cong Fang, Jason Lee, Tong Zhang.
    The 32nd Annual Conference on Neural Information Processing Systems,33 (2020): 3797-3807. (NeurIPS 2020)

  • Scaling Up Sparse Support Vector Machine by Simultaneous Feature and Sample Reduction.
    Weizhong Zhang*, Bin Hong*, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang.
    Journal of Machine Learning Research, 20 (2019): 121-1. (JMLR 2019)

  • A Sufficient Condition for Convergences of Adam and RMSProp.
    Fangyu Zou, Li Shen, Zequn Jie, Weizhong Zhang, Wei Liu.
    IEEE Conference on Computer Vision and Pattern Recognition, pp. 11127-11135, 2019. (CVPR 2019)

  • Identifying Genetic Risk Factors for Alzheimer's Disease via Shared Tree-guided Feature Learning across Multiple Tasks.
    Weizhong Zhang, Tingjin Luo, Shuang Qiu, Jieping Ye, Dengcai, Xiaofei He, Jie Wang.
    IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 11, 2018. (TKDE 2018)

  • Safe Element Screening for Submodular Function Minimization.
    Weizhong Zhang, Bin Hong, Lin Ma, Wei Liu, Tong Zhang.
    International Conference on Machine Learning, pp. 5786-5795, 2018. (ICML 2018)

  • Parsimonious Quantile Regression of Asymmetrically Heavy-tailed Financial Return Series.
    Xing Yan, Weizhong Zhang, Lin Ma, Wei Liu, and Qi Wu.
    The 32nd Annual Conference on Neural Information Processing Systems, 31(2018). (NeurIPS 2018)

  • Sparse Learning with Stochastic Composite Optimization.
    Weizhong Zhang, Lijun Zhang, Zhongming Jin, Rong Jin, Deng Cai, Xuelong Li, Ronghua Liang, Xiaofei He.
    IEEE Transduction on Pattern Analysis and Machine Intelligence, 39(6):1223-1236, 2017. (TPAMI 2017)

  • Scaling Up Sparse Support Vector Machine by Simultaneous Feature and Sample Reduction.
    Weizhong Zhang*, Bin Hong*, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang.
    International Conference on Machine Learning, pp. 4016-4025, 2017. (ICML 2017)

  • Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning.
    Tingjin Luo, Weizhong Zhang, Shuang Qiu, Yang Yang, Dongyun Yi, Guangtao Wang, Jieping Ye, Jie Wang.
    ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 345-354, 2017. (KDD 2017)

  • Accelerated Sparse Linear Regression via Random Projection.
    Weizhong Zhang, Lijun Zhang, Rong Jin, Deng Cai, Xiaofei He.
    AAAI Conference on Artificial Intelligence, pp. 2337-2343, 2016. (AAAI 2016)

  • Sparse Learning for Stochastic Composite Optimization.
    Weizhong Zhang, Lijun Zhang, Yao Hu, Rong Jin, Deng Cai, Xiaofei He.
    AAAI Conference on Artificial Intelligence, pp. 893-899, 2014. (AAAI 2014）