Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition. - Yu Pan 005; Jing Xu; Maolin Wang 001; Jinmian Ye; Fei Wang 001; Kun Bai; Zenglin Xu (AAAI, 2019)

Tensor Ring Restricted Boltzmann Machines. - Maolin Wang 001; Chenbin Zhang; Yu Pan 005; Jing Xu; Zenglin Xu (IJCNN, 2019)

Concatenated Tensor Networks for Deep Multi-Task Learning. - Maolin Wang 001; Zeyong Su; Xu Luo 003; Yu Pan 005; Shenggen Zheng; Zenglin Xu (ICONIP (5), 2020)

Heuristic Rank Selection with Progressively Searching Tensor Ring Network. - Nannan Li 003; Yu Pan 005; Yaran Chen; Zixiang Ding; Dongbin Zhao; Zenglin Xu (CoRR, 2020)

AFINet: Attentive Feature Integration Networks for Image Classification. - Xinglin Pan; Jing Xu; Yu Pan 005; Liangjian Wen; Wenxiang Lin; Kun Bai; Zenglin Xu (CoRR, 2021)

Graph Partner Neural Networks for Semi-Supervised Learning on Graphs. - Langzhang Liang; Cuiyun Gao 001; Shiyi Chen; Shishi Duan; Yu Pan 005; Junjin Zheng; Lei Wang; Zenglin Xu (CoRR, 2021)

Semantically Proportional Patchmix for Few-Shot Learning. - Jingquan Wang; Jing Xu; Yu Pan 005; Zenglin Xu (ICASSP, 2022)

A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks. - Yu Pan 005; Zeyong Su; Ao Liu 008; Jingquan Wang; Nannan Li 001; Zenglin Xu (ICML, 2022)

TedNet: A Pytorch toolkit for tensor decomposition networks. - Yu Pan 005; Maolin Wang 001; Zenglin Xu (Neurocomputing, 2022)

AFINet: Attentive Feature Integration Networks for image classification. - Xinglin Pan; Jing Xu; Yu Pan 005; Liangjian Wen; Wenxiang Lin; Kun Bai; Hongguang Fu; Zenglin Xu (Neural Networks, 2022)

Reusing Pretrained Models by Multi-linear Operators for Efficient Training. - Yu Pan 005; Ye Yuan 016; Yichun Yin; Zenglin Xu; Lifeng Shang; Xin Jiang 002; Qun Liu 001 (NeurIPS, 2023)

Tensor Networks Meet Neural Networks: A Survey. - Maolin Wang 001; Yu Pan 005; Xiangli Yang; Guangxi Li; Zenglin Xu (CoRR, 2023)

Tensorized Hypergraph Neural Networks. - Maolin Wang 001; Yaoming Zhen; Yu Pan 005; Zenglin Xu; Ruocheng Guo; Xiangyu Zhao 001 (CoRR, 2023)

Exploring Federated Optimization by Reducing Variance of Adaptive Unbiased Client Sampling. - Dun Zeng; Zenglin Xu; Yu Pan 005; Qifan Wang 001; Xiaoying Tang 002 (CoRR, 2023)

Tackling Hybrid Heterogeneity on Federated Optimization via Gradient Diversity Maximization. - Dun Zeng; Zenglin Xu; Yu Pan 005; Qifan Wang 001; Xiaoying Tang 002 (CoRR, 2023)

RegNet: Self-Regulated Network for Image Classification. - Jing Xu; Yu Pan 005; Xinglin Pan; Steven C. H. Hoi; Zhang Yi 001; Zenglin Xu (IEEE Trans. Neural Networks Learn. Syst., 2023)

Preparing Lessons for Progressive Training on Language Models. - Yu Pan 005; Ye Yuan 016; Yichun Yin; Jiaxin Shi; Zenglin Xu; Ming Zhang 004; Lifeng Shang; Xin Jiang 002; Qun Liu 001 (AAAI, 2024)

Tensorized Hypergraph Neural Networks. - Maolin Wang 001; Yaoming Zhen; Yu Pan 005; Yao Zhao; Chenyi Zhuang; Zenglin Xu; Ruocheng Guo; Xiangyu Zhao 001 (SDM, 2024)

Cumulative Distribution Function based General Temporal Point Processes. - Maolin Wang 001; Yu Pan 005; Zenglin Xu; Ruocheng Guo; Xiangyu Zhao 001; Wanyu Wang; Yiqi Wang 001; Zitao Liu 001; Langming Liu (CoRR, 2024)

Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization. - Dun Zeng; Zheshun Wu; Shiyu Liu; Yu Pan 005; Xiaoying Tang 002; Zenglin Xu (CoRR, 2024)

On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and Beyond. - Dun Zeng; Zenglin Xu; Shiyu Liu; Yu Pan 005; Qifan Wang 001; Xiaoying Tang 002 (AISTATS, 2025)

IDInit: A Universal and Stable Initialization Method for Neural Network Training. - Yu Pan 005; Chaozheng Wang; Zekai Wu; Qifan Wang 001; Min Zhang 014; Zenglin Xu (ICLR, 2025)

Enhanced Federated Optimization: Adaptive Unbiased Client Sampling with Reduced Variance. - Dun Zeng; Zenglin Xu; Yu Pan 005; Xu Luo 003; Qifan Wang 001; Xiaoying Tang 002 (Trans. Mach. Learn. Res., 2025)