Publications

You can also find my articles on my Google Scholar profile.

⁺corresponding author.

Preprint

[1] Yanyue Xie, Zhi Zhang, Ding Zhou, Cong Xie, Ziang Song, Xin Liu, Yanzhi Wang, Xue Lin, An Xu⁺. “MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router”. arxiv.

[2] Shuhua Yu, Ding Zhou, Cong Xie, An Xu, Zhi Zhang, Xin Liu, Soummya Kar. “Distributed Sign Momentum with Local Steps for Training Transformers”. arxiv.

Published

[14] Xu, An, and Yang Bai. “Cross Model Parallelism for Faster Bidirectional Training of Large Convolutional Neural Networks.” In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 637-653. Cham: Springer Nature Switzerland, 2023.

[13] Xu, An, and Yang Bai. “Distributed Adaptive Optimization with Divisible Communication.” In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 654-670. Cham: Springer Nature Switzerland, 2023.

[12] Guo, Pengfei, Dong Yang, Ali Hatamizadeh, An Xu, Ziyue Xu, Wenqi Li, Can Zhao et al. “Auto-fedrl: Federated hyperparameter optimization for multi-institutional medical image segmentation.” In European Conference on Computer Vision, pp. 437-455. Cham: Springer Nature Switzerland, 2022.

[11] Xu, An, and Heng Huang. “Detached error feedback for distributed SGD with random sparsification.” In International Conference on Machine Learning, pp. 24550-24575. PMLR, 2022.

[10] Xu, An, and Heng Huang. “Coordinating momenta for cross-silo federated learning.” In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 8, pp. 8735-8743. 2022.

[9] Xu, An, Wenqi Li, Pengfei Guo, Dong Yang, Holger R. Roth, Ali Hatamizadeh, Can Zhao, Daguang Xu, Heng Huang, and Ziyue Xu. “Closing the generalization gap of cross-silo federated medical image segmentation.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 20866-20875. 2022.

[8] Gu, Bin, An Xu, Zhouyuan Huo, Cheng Deng, and Heng Huang. “Privacy-preserving asynchronous vertical federated learning algorithms for multiparty collaborative learning.” IEEE transactions on neural networks and learning systems 33, no. 11 (2021): 6103-6115.

[7] Xu, An, Zhouyuan Huo, and Heng Huang. “Step-ahead error feedback for distributed training with compressed gradient.” In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 12, pp. 10478-10486. 2021.

[6] Gao, Hongchang, An Xu, and Heng Huang. “On the convergence of communication-efficient local SGD for federated learning.” In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 9, pp. 7510-7518. 2021.

[5] Xu, An, Zhouyuan Huo, and Heng Huang. “On the acceleration of deep learning model parallelism with staleness.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 2088-2097. 2020.

[4] Huang, Yuzhen, Xiao Yan, Guanxian Jiang, Tatiana Jin, James Cheng, An Xu, Zhanhao Liu, and Shuo Tu. “Tangram: bridging immutable and mutable abstractions for distributed data analytics.” In 2019 USENIX Annual Technical Conference (USENIX ATC 19), pp. 191-206. 2019.

[3] Liu, Yuejiang, An Xu, and Zichong Chen. “Map-based deep imitation learning for obstacle avoidance.” In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 8644-8649. IEEE, 2018.

[2] Li, Jinfeng, Xiao Yan, Jian Zhang, An Xu, James Cheng, Jie Liu, Kelvin KW Ng, and Ti-chung Cheng. “A general and efficient querying method for learning to hash.” In Proceedings of the 2018 International Conference on Management of Data, pp. 1333-1347. 2018.

[1] Li, Yongkang, Zhiyuan Jiang, An Xu, Sheng Zhou, and Zhisheng Niu. “Elastic local breakout strategy and implementation for delay-sensitive packets with local significance.” In 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP), pp. 1-6. IEEE, 2017.