Publications

You can also find my articles on my Google Scholar profile

* indicates the corresponding author.

Preprints

• Federated Semi-Supervised Learning with Annotation Heterogeneity
  Xinyi Shang, Gang Huang, Yang Lu*, Jian Lou, Bo Han, Yiu-ming Cheung, Hanzi Wang. [arXiv]
• FediOS: Decoupling Orthogonal Subspaces for Personalization in Feature-skew Federated Learning
  Lingzhi Gao, Zexi Li, Yang Lu, Chao Wu. [arXiv]
• Frequency Domain Nuances Mining for Visible-Infrared Person Re-identification
  Yukang Zhang, Yang Lu, Yan Yan, Hanzi Wang, Xuelong Li. [arXiv]
• Transitive Vision-Language Prompt Learning for Domain Generalization
  Liyuan Wang, Yan Jin, Zhen Chen, Jinlin Wu, Mengke Li, Yang Lu*, Hanzi Wang. [arXiv]

Conference

• [ECAI’24] Learning Order Forest for Qualitative-Attribute Data Clustering
  Mingjie Zhao, Sen Feng, Yiqun Zhang, Mengke Li, Yang Lu, Yiu-Ming Cheung
  European Conference on Artificial Intelligence, Santiago de Compostela, October 19-24, 2024. (CCF-B)

• [IJCAI’24] Dynamically Anchored Prompting for Task-Imbalanced Continual Learning
  Chenxing Hong, Yan Jin, Zhiqi Kang, Yizhou Chen, Mengke Li, Yang Lu* and Hanzi Wang
  International Joint Conference on Artificial Intelligence, Jeju, Korea, August 3-9, 2024. (CCF-A) [arxiv] [code]

• [AAAI’24] Federated Learning with Extremely Noisy Clients via Negative Distillation
  Yang Lu, Lin Chen, Yonggang Zhang, Yiliang Zhang, Bo Han, Yiu-ming Cheung, and Hanzi Wang
  AAAI Conference on Artificial Intelligence, Vancouver, Canada, February 20–27, 2024. (CCF-A) [arxiv] [code][video]

• [AAAI’24] Feature Fusion from Head to Tail for Long-Tailed Visual Recognition
  Mengke Li, Zhikai Hu, Yang Lu, Weichao Lan, Yiu-ming Cheung, and Hui Huang
  AAAI Conference on Artificial Intelligence, Vancouver, Canada, February 20–27, 2024. (CCF-A) [arxiv] [code]

• [AAAI’24] CLIP-guided Federated Learning on Heterogeneous and Long-Tailed Data
  Jiangming Shi, Shanshan Zheng, Xiangbo Yin, Yang Lu, Yuan Xie, and Yanyun Qu
  AAAI Conference on Artificial Intelligence, Vancouver, Canada, February 20–27, 2024. (CCF-A) [arxiv] [code]

• [ICCV’23] Label-Noise Learning with Intrinsically Long-Tailed Data
  Yang Lu, Yiliang Zhang, Bo Han, Yiu-ming Cheung, and Hanzi Wang
  IEEE/CVF International Conference on Computer Vision, Paris, France, October 2–6, 2023. (CCF-A) [arxiv] [code]

• [CVPR’23] Long-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation
  Yan Jin, Mengke Li, Yang Lu*, Yiu-ming Cheung, and Hanzi Wang
  IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, Canada, June 18–22, 2023. (CCF-A) [arxiv][code]

• [ICIP’23] Long-Tailed Federated Learning via Aggregated Meta Mapping
  Pinxin Qian, Yang Lu*, and Hanzi Wang
  IEEE International Conference on Image Processing, Kuala Lumpur, Malaysia, October 8-11, 2023. (CCF-C)

• [ICASSP’22] Personalized Federated Learning on Long-Tailed Data via Adversarial Feature Augmentation
  Yang Lu, Pinxin Qian, Gang Huang, and Hanzi Wang
  IEEE International Conference on Acoustics, Speech and Signal Processing, Greece, June 4-10, 2023. (CCF-B) [arxiv][code]

• [IJCAI’22] Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features
  Xinyi Shang, Yang Lu*, Gang Huang, and Hanzi Wang
  International Joint Conference on Artificial Intelligence, pp.2218-2224, Vienna, Austria, July 23-29, 2022. (CCF-A) [arXiv][code][video]

• [ICME’22] FEDIC: Federated Learning on Non-IID and Long-Tailed Data via Calibrated Distillation
  Xinyi Shang, Yang Lu*, Yiu-ming Cheung, and Hanzi Wang
  IEEE International Conference on Multimedia and Expo, pp.1-6, Taipei, Taiwan, July 18-22, 2022. (CCF-B) [arXiv][code]

• [CVPR’22] Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment
  Mengke Li, Yiu-ming Cheung, and Yang Lu
  IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.6929-6938 , New Orleans, Louisiana, June 21–24, 2022. (CCF-A) [arXiv] [code]

• [ICASSP’22] Multi-Focus Guided Semantic Aggregation for Video Object Detection
  Haihui Ye, Guangge Wang, Yang Lu*, Yan Yan, and Hanzi Wang
  IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4723-4727 , Singapore, May 22–27, 2022. (CCF-B)

• [ACMMM’21] Towards a Unified Middle Modality Learning for Visible-Infrared Person Re-Identification
  Yukang Zhang, Yan Yan, Yang Lu, and Hanzi Wang
  ACM International Conference on Multimedia, pp. 788–796, Chengdu, China, October 20-24, 2021. (CCF-A)

• [ECML-PKDD’21] Small-Vote Sample Selection for Label-Noise Learning
  Youze Xu, Yan Yan, Jing-hao Xue, Yang Lu, and Hanzi Wang
  The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, pp. 729-744, Bilbao, Spain, September 13–17, 2021. (CCF-B)

• [IJCAI’17] Dynamic Weighted Majority for Incremental Learning of Imbalanced Data Streams with Concept Drift
  Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
  International Joint Conference on Artificial Intelligence, pp. 2393-2399, Melbourne, Australia, August 19-25, 2017. (CCF-A) [code]

• [WCICA’16] GOBoost: G-mean Optimized Boosting Framework for Class Imbalance Learning
  Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
  World Congress on Intelligent Control and Automation, pp. 3149-3154, Guilin, China, June 12-15, 2016.

• [PAKDD’16] Hybrid Sampling with Bagging for Class Imbalance Learning
  Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
  Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 14-26, Auckland, New Zealand, April 19-22, 2016. (CCF-C)

• [ICMLC’15] Learning Performance of DAGSVM Algorithm Based on Markov Sampling
  Jie Xu, Yang Lu, and Bin Zou
  International Conference on Machine Learning and Cybernetics, pp. 910-915, Guangzhou, China, July 12-15, 2015.

• [SMC’14] A Novel Method for Protein Structure Retrieval Using Tableau Representation and Sparse Coding
  Yang Lu, Lina Yang, Haoliang Yuan, Yulong Wang, Huiwu Luo and Yuan Yan Tang
  IEEE International Conference on Systems, Man and Cybernetics, pp. 4042-4046, San Diego, USA, October 5-8, 2014. (CCF-C)

Journal

• [TAI] Adjusting Logit in Gaussian Form for Long-Tailed Visual Recognition
  Mengke Li, Yiu-ming Cheung, Yang Lu, Zhikai Hu, Weichao Lan, and Hui Huang. IEEE Transactions on Artificial Intelligence, 2024, accepted. [arXiv]
• [TCSVT] Few-shot Action Recognition via Multi-view Representation Learning
  Xiao Wang, Yang Lu, Wanchuan Yu, Yanwei Pang, and Hanzi Wang
  IEEE Transactions on Circuits and Systems for Video Technology, accepted, 2024. (JCR 2区 / CCF-B)
• [TCSVT] PARFormer: Transformer-based Multi-Task Network for Pedestrian Attribute Recognition
  Xinwen Fan, Yukang Zhang, Yang Lu, and Hanzi Wang
  IEEE Transactions on Circuits and Systems for Video Technology, vol. 34, no. 1, pp. 411-423, 2024. (JCR 2区 / CCF-B)
• [TIP] DGRNet: A Dual-level Graph Relation Network for Video Object Detection
  Qiang Qi, Tianxiang Hou, Yang Lu, Yan Yan, and Hanzi Wang
  IEEE Transactions on Image Processing, vol. 32, pp. 4128-4141, 2023. (JCR 1区 / CCF-A)
• [TCSVT] TCNet: A Novel Triple-Cooperative Network for Video Object Detection
  Qiang Qi, Tianxiang Hou, Yan Yan, Yang Lu, and Hanzi Wang
  IEEE Transactions on Circuits and Systems for Video Technology, 2023, accepted. (JCR 2区 / CCF-B)
• [TCYB] Drop Loss for Person Attribute Recognition with Imbalanced Noisy-Labeled Samples
  Yan Yan, Youze Xu, Jing-Hao Xue, Yang Lu, Hanzi Wang, and Wentao Zhu
  IEEE Transactions on Cybernetics, 2022, accepted. (JCR 1区 / CCF-B)
• [SPL] Triplet Relationship Guided Sampling Consensus for Robust Model Estimation
  Hanlin Guo, Yang Lu, Guobao Xiao, Shuyuan Lin, and Hanzi Wang
  IEEE Signal Processing Letters, vol. 29, pp. 817-821, 2022. (JCR 3区 / CCF-C)
• [PRL] TRL: Transformer based refinement learning for hybrid-supervised semantic segmentation
  Lin Cheng, Pengfei Fang, Yan Yan, Yang Lu, and Hanzi Wang
  Pattern Recognition Letters, vol. 164, pp. 239-245, 2022. (JCR 3区 / CCF-C)
• [TIE] Motion Consistency Guided Robust Geometric Model Fitting with Severe Outliers
  Hanlin Guo, Yang Lu, Haosheng Chen, Hailing Luo, Guobao Xiao, Haifang Zhang, and Hanzi Wang
  IEEE Transactions on Industrial Electronics, vol. 69, no. 4, pp. 4065-4075, 2022. (JCR 1区)
• [SPL] Recurrent Context Aggregation Network for Single Image Dehazing
  Chen Wang, Runqing Chen, Yang Lu, Yan Yan, and Hanzi Wang
  IEEE Signal Processing Letters, vol. 28, pp. 419-423, 2021. (JCR 3区 / CCF-C)
• [TCYB] Self-Adaptive Multi-Prototype-based Competitive Learning Approach: A k-means-type Algorithm for Imbalanced Data Clustering
  Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
  IEEE Transactions on Cybernetics, vol. 51, no. 3, pp. 1598-1612, 2021. (JCR 1区 / CCF-B) [code]
• [TNNLS] Bayes Imbalance Impact Index: A Measure of Class Imbalanced Dataset for Classification Problem
  Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
  IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 9, pp. 3525-3539, 2020. (JCR 1区 / CCF-B) [code]
• [TNNLS] Adaptive Chunk-based Dynamic Weighted Majority for Imbalanced Data Streams with Concept Drift
  Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
  IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 8, pp. 2764-2778, 2020. (JCR 1区 / CCF-B) [code]
• [TNNLS] k-Times Markov Sampling for SVMC
  Bin Zou, Chen Xu, Yang Lu, Yuan Yan Tang, Jie Xu, and Xinge You
  IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 4, pp. 1328-1341, 2017. (JCR 1区 / CCF-B)
• [TGRS] Hyperspectral Image Classification Based on Three-Dimensional Scattering Wavelet Transform
  Yuan Yan Tang, Yang Lu, and Haoliang Yuan
  IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 5, pp. 2467-2480, 2015. (Supervisor is the first author) (JCR 2区 / CCF-B) [code]
• [TCBB] A Fractal Dimension and Wavelet Transform Based Method for Protein Sequence Similarity Analysis
  Lina Yang, Yuan Yan Tang, Yang Lu and Huiwu Luo
  IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 12, no. 2, pp. 348-369, 2015. (JCR 3区 / CCF-B)
• [TCYB] The Generalization Ability of SVM Classification Based on Markov Sampling
  Jie Xu, Yuan Yan Tang, Bin Zou, Zong Ben Xu, Luo Qing Li, Yang Lu, and Baochang Zhang
  IEEE Transactions on Cybernetics, vol. 45, no. 6, pp. 1169-1179, 2015. (JCR 1区 / CCF-B)
• [TNNLS] The Generalization Ability of Online SVM Classification Based on Markov Sampling
  Jie Xu, Yuan Yan Tang, Bin Zou, Zong Ben Xu, Luo Qing Li, Yang Lu, and Baochang Zhang
  IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 3, pp. 628-639, 2014. (JCR 1区 / CCF-B)
• [NN] Generalization performance of Gaussian kernels SVMC based on Markov sampling
  Jie Xu, Yuan Yan Tang, Bin Zou, Zong Ben Xu, Luo Qing Li, and Yang Lu
  Neural Networks, vol. 53, pp. 40-51, 2014. (JCR 2区 / CCF-B)
• [JSTARS] Hyperspectral Image Classification Based on Regularized Sparse Representation
  Haoliang Yuan, Yuan Yan Tang, Yang Lu, Lina Yang, and Huiwu Luo
  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2174-2182, 2014. (JCR 3区)
• [JSTARS] Spectral-Spatial Classification of Hyperspectral Image Based on Discriminant Analysis
  Haoliang Yuan, Yuan Yan Tang, Yang Lu, Lina Yang, and Huiwu Luo
  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2035-2043, 2014. (JCR 3区)
• [TCYB] The Generalization Performance of Regularized Regression Algorithms Based on Markov Sampling
  Bin Zou, Yuan Yan Tang, Zong Ben Xu, Luo Qing Li, Jie Xu, and Yang Lu
  IEEE Transactions on Cybernetics, vol. 44, no. 9, pp. 1497-1507, 2014. (JCR 1区 / CCF-B)