Xingjian Li

Orcid: 0000-0001-8073-7552

Affiliations:

Baidu, Inc., China
University of Macau, Macau, SAR, China
High Performance Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, China (former)

According to our database¹, Xingjian Li authored at least 45 papers between 2011 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

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In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Towards accurate knowledge transfer via target-awareness representation disentanglement.

[BibT_eX]

[DOI]

Mach. Learn., February, 2024

Multimodal Generalized Category Discovery.

[BibT_eX]

[DOI]

CoRR, 2024

Vox-UDA: Voxel-wise Unsupervised Domain Adaptation for Cryo-Electron Subtomogram Segmentation with Denoised Pseudo Labeling.

[BibT_eX]

[DOI]

CoRR, 2024

Geometry-Guided Conditional Adaptation for Surrogate Models of Large-Scale 3D PDEs on Arbitrary Geometries.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Deep Active Learning with Noise Stability.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

G-LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint).

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Semi-supervised transfer learning with hierarchical self-regularization.

[BibT_eX]

[DOI]

Pattern Recognit., December, 2023

SMILE: Sample-to-feature Mixup for Efficient Transfer Learning.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Robust Cross-Modal Knowledge Distillation for Unconstrained Videos.

[BibT_eX]

[DOI]

CoRR, 2023

Large-scale knowledge distillation with elastic heterogeneous computing resources.

[BibT_eX]

[DOI]

Concurr. Comput. Pract. Exp., 2023

G-LIME: Statistical learning for local interpretations of deep neural networks using global priors.

[BibT_eX]

[DOI]

Artif. Intell., 2023

Overcoming Catastrophic Forgetting for Fine-Tuning Pre-trained GANs.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Towards Inadequately Pre-trained Models in Transfer Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Improving Bert Fine-Tuning via Stabilizing Cross-Layer Mutual Information.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

GrOD: Deep Learning with Gradients Orthogonal Decomposition for Knowledge Transfer, Distillation, and Adversarial Training.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2022

Knowledge Distillation with Attention for Deep Transfer Learning of Convolutional Networks.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2022

COLAM: Co-Learning of Deep Neural Networks and Soft Labels via Alternating Minimization.

[BibT_eX]

[DOI]

Neural Process. Lett., 2022

Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyond.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2022

InterpretDL: Explaining Deep Models in PaddlePaddle.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Fine-tuning Pre-trained Language Models with Noise Stability Regularization.

[BibT_eX]

[DOI]

CoRR, 2022

Deep Active Learning with Noise Stability.

[BibT_eX]

[DOI]

CoRR, 2022

Inadequately Pre-trained Models are Better Feature Extractors.

[BibT_eX]

[DOI]

CoRR, 2022

Boosting Active Learning via Improving Test Performance.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

"In-Network Ensemble": Deep Ensemble Learning with Diversified Knowledge Distillation.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., 2021

Improving Adversarial Robustness via Attention and Adversarial Logit Pairing.

[BibT_eX]

[DOI]

Frontiers Artif. Intell., 2021

SMILE: Self-Distilled MIxup for Efficient Transfer LEarning.

[BibT_eX]

[DOI]

CoRR, 2021

Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond.

[BibT_eX]

[DOI]

CoRR, 2021

Noise Stability Regularization for Improving BERT Fine-tuning.

[BibT_eX]

[DOI]

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Elastic Deep Learning Using Knowledge Distillation with Heterogeneous Computing Resources.

[BibT_eX]

[DOI]

Proceedings of the Euro-Par 2021: Parallel Processing Workshops, 2021

Adaptive Consistency Regularization for Semi-Supervised Transfer Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Temporal Relational Modeling with Self-Supervision for Action Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Towards Accurate Knowledge Transfer via Target-awareness Representation Disentanglement.

[BibT_eX]

[DOI]

CoRR, 2020

Measuring Information Transfer in Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

XMixup: Efficient Transfer Learning with Auxiliary Samples by Cross-domain Mixup.

[BibT_eX]

[DOI]

CoRR, 2020

RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Pay Attention to Features, Transfer Learn Faster CNNs.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Neighbours Matter: Image Captioning with Similar Images.

[BibT_eX]

[DOI]

Proceedings of the 31st British Machine Vision Conference 2020, 2020

Quasi-optimal Data Placement for Secure Multi-tenant Data Federation on the Cloud.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

An Empirical Study on Regularization of Deep Neural Networks by Local Rademacher Complexity.

[BibT_eX]

[DOI]

Yingzhen Yang

Xingjian Li

Jun Huan

CoRR, 2019

Delta: Deep Learning Transfer using Feature Map with Attention for Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Towards Making Deep Transfer Learning Never Hurt.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2012

An optimized large-scale hybrid DGEMM design for CPUs and ATI GPUs.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Supercomputing, 2012

2011

Biprominer: Automatic Mining of Binary Protocol Features.

[BibT_eX]

[DOI]

Proceedings of the 12th International Conference on Parallel and Distributed Computing, 2011

Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system.

[BibT_eX]

[DOI]

Proceedings of the 20th ACM International Symposium on High Performance Distributed Computing, 2011

Floating-point mixed-radix FFT core generation for FPGA and comparison with GPU and CPU.

[BibT_eX]

[DOI]

Proceedings of the 2011 International Conference on Field-Programmable Technology, 2011

Xingjian Li

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