Yi Xu

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Professor   Supervisor of Doctorate Candidates   Supervisor of Master's Candidates  

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徐易,博士,教授,博士生导师,入选国家级青年人才计划。毕业于美国爱荷华大学(The Unversity of Iowa)计算机科学系,获计算机科学专业博士学位,导师是Prof. Tianbao Yang和Prof. Qihang Lin。硕士毕业于美国南达科他州立大学,本科毕业于浙江大学数学系。加入大连理工大学之前,曾任阿里巴巴达摩院算法专家。


主要研究方向为机器学习、机器视觉、数据驱动的人工智能、统计学习理论、优化。


课题组常年招收学生,欢迎对人工智能具有浓厚兴趣的学生联系我(yxu AT dlut DOT edu DOT cn),组内经费充足,资源丰富推免/考研招生专业为 人工智能、控制科学与工程;招收2026年秋季入学博士生。长期招收本科实习生、博士后


发表论文: (全部论文见谷歌学术:https://scholar.google.com/citations?user=D4jEMqEAAAAJ&hl=en)

  • 会议论文:

  • Chang Liu, Jiangrong Shen, Xuming Ran, Mingkun Xu, Qi Xu, Yi Xu, Gang Pan. Efficient ANN-SNN Conversion with Error Compensation Learning. Accepted to ICML 2025(CCF A)

  • Wei Miao, Jiangrong Shen, Qi Xu, Timo Hamalainen, Yi Xu, Fengyu Cong. SpikingYOLOX: Improved YOLOX Object Detection with Fast Fourier Convolution and Spiking Neural Networks. Accepted to AAAI 2025(CCF A)

  • Yusong Wang, Xuanye Fang, Huifeng Yin, Dongyuan Li, Guoqi Li, Qi Xu, Yi Xu, Shuai Zhong, Mingkun Xu. BIG-FUSION: Brain-Inspired Global-Local Context Fusion Framework for Multimodal Emotion Recognition in Conversations. Accepted to AAAI 2025(CCF A)

  • Cheems Wang, Yiqin Lv, Yixiu Mao, Yun Qu, Yi Xu, Xiangyang Ji. Robust Fast Adaptation from Adversarially Explicit Task Distribution Generation. KDD 2024 (CCF A)

  • Yang Yang, Qing-Yuan Jiang, FengqiangWan, Yi Xu. Facilitating Multimodal Classification via Dynamically Learning Modality Gap. NeurIPS 2024. (CCF A)

  • Qi Xu, Xuanye Fang, Yaxin Li, Jiangrong Shen, De Ma, Yi Xu, Gang Pan. RSNN: Recurrent Spiking Neural Networks for Dynamic Spatial-Temporal Information Processing. ACM Multimedia (ACM-MM) 2024. (CCF A)

  • Qiran Zou, Shangyuan Yuan, Shian Du, YuWang, Chang Liu, Yi Xu, Jie Chen, Xiangyang Ji. ParCo: Part-Coordinating Text-to-Motion Synthesis. ECCV 2024 (CCF B)

  • Ziquan Liu, Yufei Cui, Yan Yan, Yi Xu, Xiangyang Ji, Xue Liu, Antoni B. Chan. The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks. ICML 2024(CCF A)

  • Zihuan Qiu, Yi Xu, Fanman Meng, Hongliang Li, Linfeng Xu, Qingbo Wu. Dual-consistency Model Inversion for Non-exemplar Class Incremental Learning. CVPR 2024. (CCF A)

  • Yang Yang, Yuxuan Zhang, Xin Song, Yi Xu. Not All Out-of-Distribution Data Are Harmful to Open-Set Active Learning. NeurIPS 2023(CCF A)

  • Yixiu Mao, Hongchang Zhang, Chen Chen, Yi Xu, Xiangyang Ji. Supported Value Regularization for Offline Reinforcement Learning. NeurIPS 2023. (CCF A)

  • Yixiu Mao, Hongchang Zhang, Chen Chen, Yi Xu, Xiangyang Ji. Supported Trust Region Optimization for Offline Reinforcement Learning. ICML 2023(CCF A)

  • Ziquan Liu, Yi Xu#, Xiangyang Ji, Antoni Chan. TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization. CVPR 2023(CCF A)

  • Hongchang Zhang, Yixiu Mao, Boyuan Wang, Shuncheng He, Yi Xu, Xiangyang Ji. In-sample Actor Critic for Offline Reinforcement Learning. ICLR 2023

  • Ziquan Liu, Yi Xu#, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni Chan, Rong Jin. Improved Fine-Tuning by Better Leveraging Pre-Training Data. NeurIPS 2022(CCF A)

  • Zhiwu Qing, Shiwei Zhang, Ziyuan Huang, Yi Xu, Xiang Wang, Mingqian Tang, Changxin Gao, Rong Jin, Nong Sang. Learning from Untrimmed Videos: Self-Supervised Video Representation Learning with Hierarchical Consistency. CVPR 2022(CCF A)

  • Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung. CHEX: CHannel EXploration for CNN Model Compression. CVPR 2022(CCF A)

  • Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, and Yuan Xie. Effective Model Sparsification by Scheduled Grow-and-Prune Methods. ICLR 2022.

  • Qi Qi, Zhishuai Guo, Yi Xu, Rong Jin, Tianbao Yang. An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives. NeurIPS 2021(CCF A)

  • Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-Feng Li, Baigui Sun, Hao Li, Rong Jin. Dash: Semi-Supervised Learning with Dynamic Thresholding. ICML 2021. (Long Talk, acceptance rate: 3%(CCF A)

  • Zhuoning Yuan*, Zhishuai Guo*, Yi Xu, Yiming Ying, Tianbao Yang. (*equal contribution) Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity. ICML 2021(CCF A)

  • Yan Yan, Yi Xu, Qihang Lin, Wei Liu, Tianbao Yang. Optimal Epoch Stochastic Gradient Descent Ascent Methods for Min-Max Optimization. NeurIPS 2020(CCF A)

  • Yan Yan, Yi Xu, Lijun Zhang, Xiaoyu Wang, Tianbao Yang. Stochastic Optimization for Non-convex Inf-Projection Problems. ICML 2020(CCF A)

  • Yi Xu, Shenghuo Zhu, Sen Yang, Chi Zhang, Rong Jin, Tianbao Yang. Learning with Non-Convex Truncated Losses by SGD. UAI 2020(CCF B)

  • Yi Xu, Rong Jin, Tianbao Yang. Non-asymptotic Analysis of Stoc hastic Methods for Non-Smooth Non-Convex Regularized Problems. NeurIPS 2019. (CCF A)

  • Yi Xu, Zhuoning Yuan, Sen Yang, Rong Jin, Tianbao Yang. On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization. IJCAI 2019(CCF A)

  • Yi Xu, Qi Qi, Qihang Lin, Rong Jin, Tianbao Yang. Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Nonasymptotic Convergence. ICML 2019(CCF A)

  • Zaiyi Chen, Yi Xu, Haoyuan Hu, Tianbao Yang. Katalyst: Boosting Convex Katayusha for Non-Convex Problems with a Large Condition Number. ICML 2019(CCF A)

  • Yi Xu, Rong Jin, Tianbao Yang. First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time. NeurIPS 2018(CCF A)

  • Zaiyi Chen*, Yi Xu*, Enhong Chen, Tianbao Yang. (*equal contribution) SadaGrad: Strongly Adaptive Stochastic Gradient Methods. ICML 2018(CCF A)

  • Yi Xu, Qihang Lin, Tianbao Yang. Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth Parameter. NeurIPS 2017(CCF A)

  • Yi Xu, Mingrui Liu, Qihang Lin, Tianbao Yang. ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization. NeurIPS 2017(CCF A)

  • Yi Xu, Qihang Lin, Tianbao Yang. Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence. ICML 2017(CCF A)

  • Yi Xu, Haiqing Yang, Lijun Zhang, Tianbao Yang. Efficient Non-oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee. AAAI 2017(CCF A)

  • Yi Xu*, Yan Yan*, Qihang Lin, Tianbao Yang. (*equal contribution) Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than O(1/ϵ). NeurIPS 2016(CCF A)

  • 期刊论文:

  • Hui Liu, Fan Wei, Lixin Yan, Sushan Wang, Chongfu Jia, Lina Zhang, Jiansheng Peng, Yi Xu#. GVI: Guideable Visual Interpretation on Medical Tomographic Images to Improve the Performance of Deep Network. Pattern Recognition Letters, 2025

  • Yang Yang, Hongpeng Pan, Qing-Yuan Jiang , Yi Xu#, Jinghui Tang. Learning to Rebalance Multi-Modal Optimization by Adaptively Masking Subnetworks. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025 (CCF A)

  • Tiancheng Wang, Yi Xu#, Di Guo, and Xi-Ming Sun. A contrastive Semi-Supervised Remaining Useful Life Prediction Method with Incomplete Life Histories on Turbofan. Computers and Electrical Engineering 123 (2025): 110134, 2025.

  • Zhishuai Guo, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang. Unified Convergence Analysis for Adaptive Optimization with Moving Average Estimator. Machine Learning, 2024(CCF B)

  • Yang Yang, Nan Jiang, Yi Xu#, De-Chuan Zhan. Robust Semi-supervised Learning by Wisely Leveraging Open-set Data. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.  (CCF A)

  • Peixuan Ding, Yi Xu#, Xi-Ming Sun. Multi-task Learning for Aero-engine Bearing Fault Diagnosis with Limited Data. IEEE Transactions on Instrumentation and Measurement, 2024.

  • Peixuan Ding, Yi Xu#, Pan Qing, Xi-Ming Sun. A novel deep learning approach for intelligent bearing fault diagnosis under extremely small samples. Applied Intelligence, 2024.

  • Rui Jiang, Xuetao Zhang, Yisha Liu, Yi Xu, Xuebo Zhang, Yan Zhuang. Multi-agent cooperative strategy with explicit teammate modeling and targeted informative communication. Neurocomputing, 2024.

  • Rui Xu, Xue-Mei Dong, Weijie Li, Jiangtao Peng, Weiwei Sun, Yi Xu. DBCTNet: Double Branch Convolution-Transformer Network for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing (TGARS), 62:1-15, 2024.

  • Zhiwu Qing, Shiwei Zhang, Ziyuan Huang, Yi Xu, Xiang Wang, Mingqian Tang, Changxin Gao, Rong Jin, Nong Sang. Self-Supervised Learning from Untrimmed Videos via Hierarchical Consistency. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2023(CCF A)

  • Qi Qi, Yi Xu, Rong Jin, Wotao Yin, Tianbao Yang. Attentional Biased Stochastic Gradient Descent. TMLR 2023.

  • Yi Xu, Qihang Lin, Tianbao Yang. Accelerate Stochastic Subgradient Method by Leveraging Local Growth Condition. Analysis and Applications. Vol. 17, No. 05, pp. 773-818, 2019


指导学生竞赛:

  • CVPR 2024 Foundational FSOD Challenge 冠军

  • ICCV 2023 Point Tracking冠军

  • CVPR 2023 Foundation Model Challenge: Cross-Modal Retrieval冠军

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