IPTV System Design: An ISP's Perspective. - Yali Liu; Zhengye Liu; Xidong Wu; Jin Wang; Charlie Chen-Yui Yang (CyberC, 2011)

QoS Monitoring and Troubleshooting of a Large Scale IPTV Deployment. - Xidong Wu; Zhengye Liu; Yali Liu; Menglin Liu; Charlie Chen-Yui Yang; Jin Wang (CyberC, 2011)

Compressive sensing-based coprime array direction-of-arrival estimation. - Chengwei Zhou; Yujie Gu 001; Yimin D. Zhang; Zhiguo Shi 001; Tao Jin; Xidong Wu (IET Commun., 2017)

Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems. - Feihu Huang 001; Xidong Wu; Heng Huang (NeurIPS, 2021)

Fast Stochastic Recursive Momentum Methods for Imbalanced Data Mining. - Xidong Wu; Feihu Huang 001; Heng Huang (ICDM, 2022)

Doubly Sparse Asynchronous Learning for Stochastic Composite Optimization. - Runxue Bao; Xidong Wu; Wenhan Xian; Heng Huang (IJCAI, 2022)

Distributed Dynamic Safe Screening Algorithms for Sparse Regularization. - Runxue Bao; Xidong Wu; Wenhan Xian; Heng Huang (CoRR, 2022)

Decentralized Riemannian Algorithm for Nonconvex Minimax Problems. - Xidong Wu; Zhengmian Hu; Heng Huang (AAAI, 2023)

Faster Adaptive Federated Learning. - Xidong Wu; Feihu Huang 001; Zhengmian Hu; Heng Huang (AAAI, 2023)

AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. - Feihu Huang 001; Xidong Wu; Zhengmian Hu (AISTATS, 2023)

Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization. - Zhengmian Hu; Xidong Wu; Heng Huang (ICML, 2023)

Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining. - Xidong Wu; Zhengmian Hu; Jian Pei 001; Heng Huang (KDD, 2023)

Federated Conditional Stochastic Optimization. - Xidong Wu; Jianhui Sun; Zhengmian Hu; Junyi Li; Aidong Zhang; Heng Huang (NeurIPS, 2023)

Solving a Class of Non-Convex Minimax Optimization in Federated Learning. - Xidong Wu; Jianhui Sun; Zhengmian Hu; Aidong Zhang; Heng Huang (NeurIPS, 2023)

Performance and Energy Consumption of Parallel Machine Learning Algorithms. - Xidong Wu; Preston Brazzle; Stephen Cahoon (CoRR, 2023)

Leveraging Foundation Models to Improve Lightweight Clients in Federated Learning. - Xidong Wu; Wan-Yi Lin; Devin Willmott; Filipe Condessa; Yufei Huang 001; Zhenzhen Li; Madan Ravi Ganesh (CoRR, 2023)

On the Role of Server Momentum in Federated Learning. - Jianhui Sun; Xidong Wu; Heng Huang; Aidong Zhang (AAAI, 2024)

ReguloGPT: Harnessing GPT for End-to-End Knowledge Graph Construction of Molecular Regulatory Pathways. - Xidong Wu; Sumin Jo; Yiming Zeng 014; Arun Das 001; Tinghe Zhang; Parth Patel; Yuanjing Wei; Lei Li; Shou-Jiang Gao; Jianqiu Zhang 002; Dexter Pratt; Yu-Chiao Chiu; et al. (BHI, 2024)

Auto- Train-Once: Controller Network Guided Automatic Network Pruning from Scratch. - Xidong Wu; Shangqian Gao; Zeyu Zhang; Zhenzhen Li; Runxue Bao; Yanfu Zhang; Xiaoqian Wang 001; Heng Huang (CVPR, 2024)

Unbiased Watermark for Large Language Models. - Zhengmian Hu; Lichang Chen; Xidong Wu; Yihan Wu; Hongyang Zhang 001; Heng Huang (ICLR, 2024)

Digital Approach In Case of FPGA Realization of Quartic Neuron Model (QNM) Using Cost-Effective Mathematical Modifications. - Yong Chen; Xidong Wu; Huajun Ba; Xinjun Miao; Mohammad Sh. Daoud; Xiaotian Pan; Abdulilah Mohammad Mayet; Guodao Zhang; Jun Sun (IEEE Trans. Circuits Syst. I Regul. Pap., 2024)

Multiscale feature enhanced gating network for atrial fibrillation detection. - Xidong Wu; Mingke Yan; Renqiao Wang; Liping Xie (Comput. Methods Programs Biomed., 2025)

Client-Centric Federated Adaptive Optimization. - Jianhui Sun; Xidong Wu; Heng Huang; Aidong Zhang (CoRR, 2025)

TreeDiff: AST-Guided Code Generation with Diffusion LLMs. - Yiming Zeng 012; Jinghan Cao; Zexin Li; Yiming Chen; Tao Ren; Dawei Xiang; Xidong Wu; Shangqian Gao; Tingting Yu (CoRR, 2025)