Xingjian Li

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 49

Top Topics

Transfer Learning

Learning Transfer

Graph Transduction

Rademacher Complexity

Top Venues

ACM Trans. Knowl. Discov. Data

Publications

Xingjian Li, Di Hu, Xuhong Li, Haoyi Xiong, Cheng-Zhong Xu, Dejing Dou
Towards accurate knowledge transfer via target-awareness representation disentanglement. Mach. Learn. 113 (2) (2024)
Haoran Li, Xingjian Li, Jiahua Shi, Huaming Chen, Bo Du, Daisuke Kihara, Johan Barthelemy, Jun Shen, Min Xu
Vox-UDA: Voxel-wise Unsupervised Domain Adaptation for Cryo-Electron Subtomogram Segmentation with Denoised Pseudo Labeling. CoRR (2024)
Xuhong Li, Haoyi Xiong, Xingjian Li, Xiao Zhang, Ji Liu, Haiyan Jiang, Zeyu Chen, Dejing Dou
G-LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint). AAAI (2024)
Xingjian Li, Pengkun Yang, Yangcheng Gu, Xueying Zhan, Tianyang Wang, Min Xu, Chengzhong Xu
Deep Active Learning with Noise Stability. AAAI (2024)
Xingjian Li, Abulikemu Abuduweili, Humphrey Shi, Pengkun Yang, Dejing Dou, Haoyi Xiong, Chengzhong Xu
Semi-supervised transfer learning with hierarchical self-regularization. Pattern Recognit. 144 (2023)
Xingjian Li, Haoyi Xiong, Cheng-Zhong Xu, Dejing Dou
SMILE: Sample-to-feature Mixup for Efficient Transfer Learning. Trans. Mach. Learn. Res. 2023 (2023)
Ji Liu, Daxiang Dong, Xi Wang, An Qin, Xingjian Li, Patrick Valduriez, Dejing Dou, Dianhai Yu
Large-scale knowledge distillation with elastic heterogeneous computing resources. Concurr. Comput. Pract. Exp. 35 (26) (2023)
Jicun Li, Xingjian Li, Tianyang Wang, Shi Wang, Yanan Cao, Cheng-Zhong Xu, Dejing Dou
Improving Bert Fine-Tuning via Stabilizing Cross-Layer Mutual Information. ICASSP (2023)
Wenke Xia, Xingjian Li, Andong Deng, Haoyi Xiong, Dejing Dou, Di Hu
Robust Cross-Modal Knowledge Distillation for Unconstrained Videos. CoRR (2023)
Andong Deng, Xingjian Li, Di Hu, Tianyang Wang, Haoyi Xiong, Cheng-Zhong Xu
Towards Inadequately Pre-trained Models in Transfer Learning. ICCV (2023)
Xuhong Li, Haoyi Xiong, Xingjian Li, Xiao Zhang, Ji Liu, Haiyan Jiang, Zeyu Chen, Dejing Dou
G-LIME: Statistical learning for local interpretations of deep neural networks using global priors. Artif. Intell. 314 (2023)
Zeren Zhang, Xingjian Li, Tao Hong, Tianyang Wang, Jinwen Ma, Haoyi Xiong, Cheng-Zhong Xu
Overcoming Catastrophic Forgetting for Fine-Tuning Pre-trained GANs. ECML/PKDD (5) (2023)
Hang Hua, Xingjian Li, Dejing Dou, Cheng-Zhong Xu, Jiebo Luo
Fine-tuning Pre-trained Language Models with Noise Stability Regularization. CoRR (2022)
Tianyang Wang, Xingjian Li, Pengkun Yang, Guosheng Hu, Xiangrui Zeng, Siyu Huang, Cheng-Zhong Xu, Min Xu
Boosting Active Learning via Improving Test Performance. AAAI (2022)
Andong Deng, Xingjian Li, Zhibing Li, Di Hu, Chengzhong Xu, Dejing Dou
Inadequately Pre-trained Models are Better Feature Extractors. CoRR (2022)
Xuhong Li, Haoyi Xiong, Xingjian Li, Xuanyu Wu, Zeyu Chen, Dejing Dou
InterpretDL: Explaining Deep Models in PaddlePaddle. J. Mach. Learn. Res. 23 (2022)
Xingjian Li, Pengkun Yang, Tianyang Wang, Xueying Zhan, Min Xu, Dejing Dou, Chengzhong Xu
Deep Active Learning with Noise Stability. CoRR (2022)
Xingjian Li, Haoyi Xiong, Haozhe An, Cheng-Zhong Xu, Dejing Dou
COLAM: Co-Learning of Deep Neural Networks and Soft Labels via Alternating Minimization. Neural Process. Lett. 54 (6) (2022)
Haoyi Xiong, Ruosi Wan, Jian Zhao, Zeyu Chen, Xingjian Li, Zhanxing Zhu, Jun Huan
GrOD: Deep Learning with Gradients Orthogonal Decomposition for Knowledge Transfer, Distillation, and Adversarial Training. ACM Trans. Knowl. Discov. Data 16 (6) (2022)
Ji Liu, Daxiang Dong, Xi Wang, An Qin, Xingjian Li, Patrick Valduriez, Dejing Dou, Dianhai Yu
Large-scale Knowledge Distillation with Elastic Heterogeneous Computing Resources. CoRR (2022)
Xuhong Li, Haoyi Xiong, Xingjian Li, Xuanyu Wu, Xiao Zhang, Ji Liu, Jiang Bian, Dejing Dou
Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyond. Knowl. Inf. Syst. 64 (12) (2022)
Xingjian Li, Haoyi Xiong, Zeyu Chen, Jun Huan, Ji Liu, Cheng-Zhong Xu, Dejing Dou
Knowledge Distillation with Attention for Deep Transfer Learning of Convolutional Networks. ACM Trans. Knowl. Discov. Data 16 (3) (2022)
Xuhong Li, Haoyi Xiong, Xingjian Li, Xuanyu Wu, Xiao Zhang, Ji Liu, Jiang Bian, Dejing Dou
Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond. CoRR (2021)
Hang Hua, Xingjian Li, Dejing Dou, Cheng-Zhong Xu, Jiebo Luo
Noise Stability Regularization for Improving BERT Fine-tuning. NAACL-HLT (2021)
Daxiang Dong, Ji Liu, Xi Wang, Weibao Gong, An Qin, Xingjian Li, Dianhai Yu, Patrick Valduriez, Dejing Dou
Elastic Deep Learning Using Knowledge Distillation with Heterogeneous Computing Resources. Euro-Par Workshops (2021)
Hang Hua, Xingjian Li, Dejing Dou, Cheng-Zhong Xu, Jiebo Luo
Noise Stability Regularization for Improving BERT Fine-tuning. CoRR (2021)
Xingjian Li, Dou Goodman, Ji Liu, Tao Wei, Dejing Dou
Improving Adversarial Robustness via Attention and Adversarial Logit Pairing. Frontiers Artif. Intell. 4 (2021)
Xingjian Li, Haoyi Xiong, Chengzhong Xu, Dejing Dou
SMILE: Self-Distilled MIxup for Efficient Transfer LEarning. CoRR (2021)
Abulikemu Abuduweili, Xingjian Li, Humphrey Shi, Cheng-Zhong Xu, Dejing Dou
Adaptive Consistency Regularization for Semi-Supervised Transfer Learning. CVPR (2021)
Abulikemu Abuduweili, Xingjian Li, Humphrey Shi, Cheng-Zhong Xu, Dejing Dou
Adaptive Consistency Regularization for Semi-Supervised Transfer Learning. CoRR (2021)
Xingjian Li, Haoyi Xiong, Zeyu Chen, Jun Huan, Cheng-Zhong Xu, Dejing Dou
"In-Network Ensemble": Deep Ensemble Learning with Diversified Knowledge Distillation. ACM Trans. Intell. Syst. Technol. 12 (5) (2021)
Dong Wang, Di Hu, Xingjian Li, Dejing Dou
Temporal Relational Modeling with Self-Supervision for Action Segmentation. AAAI (2021)
Tianyang Wang, Xingjian Li, Pengkun Yang, Guosheng Hu, Xiangrui Zeng, Siyu Huang, Cheng-Zhong Xu, Min Xu
Boosting Active Learning via Improving Test Performance. CoRR (2021)
Kafeng Wang, Xitong Gao, Yiren Zhao, Xingjian Li, Dejing Dou, Cheng-Zhong Xu
Pay Attention to Features, Transfer Learn Faster CNNs. ICLR (2020)
Xingjian Li, Haoyi Xiong, Haozhe An, Dejing Dou, Chengzhong Xu
COLAM: Co-Learning of Deep Neural Networks and Soft Labels via Alternating Minimization. CoRR (2020)
Dong Wang, Di Hu, Xingjian Li, Dejing Dou
Temporal Relational Modeling with Self-Supervision for Action Segmentation. CoRR (2020)
Xingjian Li, Di Hu, Xuhong Li, Haoyi Xiong, Zhi Ye, Zhipeng Wang, Chengzhong Xu, Dejing Dou
Towards Accurate Knowledge Transfer via Target-awareness Representation Disentanglement. CoRR (2020)
Xingjian Li, Haoyi Xiong, Haozhe An, Cheng-Zhong Xu, Dejing Dou
RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr. ICML (2020)
Xingjian Li, Haoyi Xiong, Haozhe An, Chengzhong Xu, Dejing Dou
RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr. CoRR (2020)
Qi Kang, Ji Liu, Sijia Yang, Haoyi Xiong, Haozhe An, Xingjian Li, Zhi Feng, Licheng Wang, Dejing Dou
Quasi-optimal Data Placement for Secure Multi-tenant Data Federation on the Cloud. IEEE BigData (2020)
Xingjian Li, Haoyi Xiong, Haozhe An, Chengzhong Xu, Dejing Dou
XMixup: Efficient Transfer Learning with Auxiliary Samples by Cross-domain Mixup. CoRR (2020)
Qingzhong Wang, Jiuniu Wang, Antoni B. Chan, Siyu Huang, Haoyi Xiong, Xingjian Li, Dejing Dou
Neighbours Matter: Image Captioning with Similar Images. BMVC (2020)
Xiao Zhang, Xingjian Li, Dejing Dou, Ji Wu
Measuring Information Transfer in Neural Networks. CoRR (2020)
Xingjian Li, Haoyi Xiong, Hanchao Wang, Yuxuan Rao, Liping Liu, Jun Huan
Delta: Deep Learning Transfer using Feature Map with Attention for Convolutional Networks. ICLR (Poster) (2019)
Ruosi Wan, Haoyi Xiong, Xingjian Li, Zhanxing Zhu, Jun Huan
Towards Making Deep Transfer Learning Never Hurt. CoRR (2019)
Xingjian Li, Haoyi Xiong, Hanchao Wang, Yuxuan Rao, Liping Liu, Jun Huan
DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks. CoRR (2019)
Yingzhen Yang, Xingjian Li, Jun Huan
An Empirical Study on Regularization of Deep Neural Networks by Local Rademacher Complexity. CoRR (2019)
Ruosi Wan, Haoyi Xiong, Xingjian Li, Zhanxing Zhu, Jun Huan
Towards Making Deep Transfer Learning Never Hurt. ICDM (2019)
Dou Goodman, Xingjian Li, Jun Huan, Tao Wei
Improving Adversarial Robustness via Attention and Adversarial Logit Pairing. CoRR (2019)
Jiajia Li, Xingjian Li, Guangming Tan, Mingyu Chen, Ninghui Sun
An optimized large-scale hybrid DGEMM design for CPUs and ATI GPUs. ICS (2012)
Linchuan Li, Xingjian Li, Guangming Tan, Mingyu Chen, Peiheng Zhang
Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system. HPDC (2011)
Yipeng Wang, Xingjian Li, Jiao Meng, Yong Zhao, Zhibin Zhang, Li Guo
Biprominer: Automatic Mining of Binary Protocol Features. PDCAT (2011)
Bo Duan, Wendi Wang, Xingjian Li, Chunming Zhang, Peiheng Zhang, Ninghui Sun
Floating-point mixed-radix FFT core generation for FPGA and comparison with GPU and CPU. FPT (2011)