Zhang, Weizhong

38 publications

AAAI 2025 Achieving Ensemble-like Performance in a Single Model: A Feature Diversification Framework for Image-Text Matching Zhao Zhou, Yiqun Wang, Weizhong Zhang, Yingbin Zheng, Xiangcheng Du, Cheng Jin

NeurIPS 2025 Complete Structure Guided Point Cloud Completion via Cluster- and Instance-Level Contrastive Learning Yang Chen, Yirun Zhou, Weizhong Zhang, Cheng Jin

NeurIPS 2025 Compress Large Language Models via Collaboration Between Learning and Matrix Approximation Yuesen Liao, Zhiwei Li, Binrui Wu, Zihao Cheng, Su Zhao, Shuai Chen, Weizhong Zhang

NeurIPS 2025 Computation and Memory-Efficient Model Compression with Gradient Reweighting Zhiwei Li, Yuesen Liao, Binrui Wu, Yuquan Zhou, Xupeng Shi, Dongsheng Jiang, Yin Li, Weizhong Zhang

NeurIPS 2025 Computational Budget Should Be Considered in Data Selection Weilin Wan, Weizhong Zhang, Cheng Jin

CVPR 2025 DreamText: High Fidelity Scene Text Synthesis Yibin Wang, Weizhong Zhang, Honghui Xu, Cheng Jin

NeurIPS 2025 Efficient Representativeness-Aware Coreset Selection Zihao Cheng, Binrui Wu, Zhiwei Li, Yuesen Liao, Su Zhao, Shuai Chen, Yuan Gao, Weizhong Zhang

AAAI 2025 Expanding the Scope of Negatives: Boosting Image-Text Matching with Negatives Distribution Guided Learning Zhao Zhou, Weizhong Zhang, Xiangcheng Du, Yingbin Zheng, Cheng Jin

AAAI 2025 Optimized Gradient Clipping for Noisy Label Learning Xichen Ye, Yifan Wu, Weizhong Zhang, Xiaoqiang Li, Yifan Chen, Cheng Jin

CVPR 2025 Population Normalization for Federated Learning Zhuoyao Wang, Fan Yi, Peizhu Gong, Caitou He, Cheng Jin, Weizhong Zhang

ICML 2025 Towards Robust Influence Functions with Flat Validation Minima Xichen Ye, Yifan Wu, Weizhong Zhang, Cheng Jin, Yifan Chen

ICLR 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

ICML 2024 Efficient Denoising Diffusion via Probabilistic Masking Weizhong Zhang, Zhiwei Zhang, Renjie Pi, Zhongming Jin, Yuan Gao, Jieping Ye, Kani Chen

AAAI 2024 FusionFormer: A Concise Unified Feature Fusion Transformer for 3D Pose Estimation Yanlu Cai, Weizhong Zhang, Yuan Wu, Cheng Jin

CVPR 2024 High-Fidelity Person-Centric Subject-to-Image Synthesis Yibin Wang, Weizhong Zhang, Jianwei Zheng, Cheng Jin

NeurIPS 2024 Low Precision Local Training Is Enough for Federated Learning Zhiwei Li, Yiqiu Li, Binbin Lin, Zhongming Jin, Weizhong Zhang

AAAI 2024 Point Cloud Part Editing: Segmentation, Generation, Assembly, and Selection Kaiyi Zhang, Yang Chen, Ximing Yang, Weizhong Zhang, Cheng Jin

CVPR 2024 PoseIRM: Enhance 3D Human Pose Estimation on Unseen Camera Settings via Invariant Risk Minimization Yanlu Cai, Weizhong Zhang, Yuan Wu, Cheng Jin

ICLR 2024 Spurious Feature Diversification Improves Out-of-Distribution Generalization Lin Yong, Lu Tan, Yifan Hao, Ho Nam Wong, Hanze Dong, Weizhong Zhang, Yujiu Yang, Tong Zhang

ICLR 2023 A Holistic View of Label Noise Transition Matrix in Deep Learning and Beyond Lin Yong, Renjie Pi, Weizhong Zhang, Xiaobo Xia, Jiahui Gao, Xiao Zhou, Tongliang Liu, Bo Han

CVPR 2023 DynaFed: Tackling Client Data Heterogeneity with Global Dynamics Renjie Pi, Weizhong Zhang, Yueqi Xie, Jiahui Gao, Xiaoyu Wang, Sunghun Kim, Qifeng Chen

ICLR 2023 DynaMS: Dyanmic Margin Selection for Efficient Deep Learning Jiaxing Wang, Yong Li, Jingwei Zhuo, Xupeng Shi, Weizhong Zhang, Lixing Gong, Tong Tao, Pengzhang Liu, Yongjun Bao, Weipeng Yan

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

AISTATS 2022 Finding Dynamics Preserving Adversarial Winning Tickets Xupeng Shi, Pengfei Zheng, A. Adam Ding, Yuan Gao, Weizhong Zhang

NeurIPSW 2022 A Neural Tangent Kernel Perspective on Function-Space Regularization in Neural Networks Zonghao Chen, Xupeng Shi, Tim G. J. Rudner, Qixuan Feng, Weizhong Zhang, Tong Zhang

ICML 2022 Model Agnostic Sample Reweighting for Out-of-Distribution Learning Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang

ICML 2022 Probabilistic Bilevel Coreset Selection Xiao Zhou, Renjie Pi, Weizhong Zhang, Yong Lin, Zonghao Chen, Tong Zhang

ICML 2022 Sparse Invariant Risk Minimization Xiao Zhou, Yong Lin, Weizhong Zhang, Tong Zhang

CVPR 2021 Effective Sparsification of Neural Networks with Global Sparsity Constraint Xiao Zhou, Weizhong Zhang, Hang Xu, Tong Zhang

NeurIPS 2021 Efficient Neural Network Training via Forward and Backward Propagation Sparsification Xiao Zhou, Weizhong Zhang, Zonghao Chen, Shizhe Diao, Tong Zhang

AAAI 2020 Gradient Method for Continuous Influence Maximization with Budget-Saving Considerations Wei Chen, Weizhong Zhang, Haoyu Zhao

NeurIPS 2020 How to Characterize the Landscape of Overparameterized Convolutional Neural Networks Yihong Gu, Weizhong Zhang, Cong Fang, Jason Lee, Tong Zhang

JMLR 2019 Scaling up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction Bin Hong, Weizhong Zhang, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang

NeurIPS 2018 Parsimonious Quantile Regression of Financial Asset Tail Dynamics via Sequential Learning Xing Yan, Weizhong Zhang, Lin Ma, Wei Liu, Qi Wu

ICML 2018 Safe Element Screening for Submodular Function Minimization Weizhong Zhang, Bin Hong, Lin Ma, Wei Liu, Tong Zhang

ICML 2017 Scaling up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction Weizhong Zhang, Bin Hong, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang

AAAI 2016 Accelerated Sparse Linear Regression via Random Projection Weizhong Zhang, Lijun Zhang, Rong Jin, Deng Cai, Xiaofei He

AAAI 2014 Sparse Learning for Stochastic Composite Optimization Weizhong Zhang, Lijun Zhang, Yao Hu, Rong Jin, Deng Cai, Xiaofei He