Publications [Google Scholar]

Books

Book Chapters

  1. Kang Li, Sheng Li, and Yun Fu, Time Series Modeling for Activity Prediction, Human Activity Recognition and Prediction, Springer, 2016.
  2. Sheng Li, Liangyue Li, and Yun Fu, Low-Rank Dictionary Learning, Low-Rank and Sparse Modeling for Visual Analysis, Springer, 2014.
  3. Sheng Li, Ming Shao, and Yun Fu, Low-Rank Outlier Detection, Low-Rank and Sparse Modeling for Visual Analysis, Springer, 2014.

Papers

    2024
  1. Sheng Li. Large Pretrained Models for Treatment Effect Estimation: Are We There Yet? Patterns, 2024. (Invited Paper)
  2. Weili Shi and Sheng Li. Dual-windowed Vision Transformer with Angular Self-Attention. Transactions on Machine Learning Research (TMLR), 2024.
  3. Daiqing Qi, Handong Zhao, Xiaowei Jia, and Sheng Li. Revealing an Overlooked Challenge in Class-Incremental Graph Learning. Transactions on Machine Learning Research (TMLR), 2024.
  4. Mengxuan Hu, Zhixuan Chu, and Sheng Li. DTRNet: Precisely Correcting Selection Bias in Individual-Level Continuous Treatment Estimation through Reweighted Disentangled Representation. Transactions on Machine Learning Research (TMLR), 2024.
  5. Ronghang Zhu, Dongliang Guo, Daiqing Qi, Zhixuan Chu, Xiang Yu, and Sheng Li. Trustworthy Representation Learning Across Domains. ACM Trans. Knowledge Discovery from Data (T-KDD), 2024.
  6. Zhongliang Zhou*, Wayland Yeung*, Saber Soleymani, Nathan Gravel, Mariah Salcedo, Sheng Li, and Natarajan Kannan. Using explainable machine learning to uncover the kinase-substrate interaction landscape. Bioinformatics. 2024. (* indicates equal contribution)
  7. Haixing Dai, Zhengliang Liu, Wenxiong Liao, Xiaoke Huang, Zihao Wu, Lin Zhao, Wei Liu, Ninghao Liu, Sheng Li, Dajiang Zhu, Hongmin Cai, Quanzheng Li, Dinggang Shen, Tianming Liu, and Xiang Li. ChatAug: Leveraging ChatGPT for Text Data Augmentation, IEEE Transactions on Big Data (TBD), 2024.
  8. Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Haixing Dai, Gengchen Mai, Ninghao Liu, Chen Zhen, Tianming Liu, Sheng Li. Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications. IEEE Transactions on Big Data (TBD), 2024.
  9. Weili Shi, Ronghang Zhu, and Sheng Li. Unsupervised Class-imbalanced Domain Adaptation with Pairwise Adversarial Training and Semantic Alignment. IEEE Transactions on on Circuits and Systems for Video Technology (TCSVT), 2024.
  10. Weili Shi and Sheng Li. Mixup Virtual Adversarial Training for Robust Vision Transformers. IEEE Transactions on Big Data (TBD), 2024.
  11. Daniel Petti, Ronghang Zhu, Sheng Li, and Changying Li. Graph Neural Networks for Lightweight Plant Organ Tracking. Computers and Electronics in Agriculture (CEA), 2024.
  12. Daiqing Qi, Handong Zhao, and Sheng Li. Easy Regional Contrastive Learning of Expressive Visual Fashion Representations. The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024.
  13. Daiqing Qi, Handong Zhao, Aidong Zhang, and Sheng Li. Generalizing to Unseen Domains via Text-guided Augmentation: A Training-free Approach, European Conference on Computer Vision (ECCV), 2024.
  14. Daiqing Qi, Handong Zhao, Zijun Wei, and Sheng Li. Tag-grounded Visual Instruction Tuning with Retrieval Augmentation. The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
  15. Yu Wang, Ronghang Zhu, Pengsheng Ji, and Sheng Li. Open-Set Graph Domain Adaptation via Separate Domain Alignment. The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024. [Code]
  16. Zhixuan Chu, Mengxuan Hu, Qing Cui, Longfei Li, and Sheng Li. Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction. The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024.
  17. Yan Wang, Zhixuan Chu, Xin Ouyang, Simeng Wang, Hongyan Hao, Yue Shen, Jinjie Gu, Siqiao Xue, James Zhang, Qing Cui, Longfei Li, Jun Zhou, and Sheng Li. LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs. The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024.
  18. Zihan Guan, Mengxuan Hu, Zhongliang Zhou, Jielu Zhang, Sheng Li, and Ninghao Liu. BadSAM: Exploring Security Vulnerabilities of SAM via Backdoor Attacks. (Student Abstract) The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024.
  19. Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, and Jundong Li. Causal Inference with Latent Variables: Recent Advances and Future Prospectives. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024. (Tutorial Track & Survey Paper).
  20. Dongliang Guo, Yun Fu, and Sheng Li. Ada-VAD: Domain Adaptable Video Anomaly Detection. SIAM International Conference on Data Mining (SDM), 2024.
  21. Zhongliang Zhou, Jielu Zhang, Zihan Guan, Mengxuan Hu, Ni Lao, Lan Mu, Sheng Li, and Gengchen Mai. Img2Loc: revisiting image localization using multi-modality foundation models and Image-based Retrieval-Augmented Generation. (Demo Paper) The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2024.
  22. Jielu Zhang, Zhongliang Zhou, Gengchen Mai, Mengxuan Hu, Zihan Guan, Sheng Li, and Lan Mu. Text2Seg: Zero-shot Remote Sensing Image Semantic Segmentation via Text-Guided Visual Foundation Models. The 7th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (GeoAI), 2024.

    23. 2023
  23. Ronghang Zhu, Xiang Yu, and Sheng Li. Semi-Supervised Single Domain Generalization with Label-Free Adversarial Data Augmentation. Transactions on Machine Learning Research (TMLR), 2023.
  24. Zhongliang Zhou*, Wayland Yeung*, Nathan Gravel, Mariah Salcedo, Saber Soleymani, Sheng Li, and Natarajan Kannan. Phosformer: An explainable Transformer model for protein kinase-specific phosphorylation predictions. Bioinformatics, 2023. (* indicates equal contribution)
  25. Lin Zhao, Haixing Dai, Zihao Wu, Zhenxiang Xiao, Lu Zhang, David Weizhong Liu, Xintao Hu, Xi Jiang, Sheng Li, Dajiang Zhu, and Tianming Liu. Coupling visual semantics of artificial neural networks and human brain function via synchronized activations. IEEE Transactions on Cognitive and Developmental Systems (T-CDS), 2023.
  26. Shengyu Chen, Nasrin Kalanat, Yiqun Xie, Sheng Li, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, Jordan Read, and Xiaowei Jia. Physics-Guided Machine Learning from Simulated Data with Different Physical Parameters. Knowledge and Information Systems (KAIS), 2023.
  27. Juliet N. Sekandi, Weili Shi, Ronghang Zhu, Patrick Evans Kaggwa, Ernest Mwebaze, and Sheng Li. Application of Artificial Intelligence to Monitoring of Medication Adherence for Tuberculosis Treatment in Africa: A Pilot Study. Journal of Medical Internet Research (JMIR) AI, 2023.
  28. Xiaojun Wei, Tadas Penkauskas, Joseph E Reiner, Celeste Kennard, Mark J Uline, Qian Wang, Sheng Li, Aleksei Aksimentiev, Joseph WF Robertson, and Chang Liu. Engineering Biological Nanopore Approaches toward Protein Sequencing. ACS Nano, 2023.
  29. Lian Zhang, Jason M Holmes, Zhengliang Liu, Sujay A Vora, Terence T Sio, Carlos E Vargas, Nathan Y Yu, Sameer R Keole, Steven E Schild, Martin Bues, Sheng Li, Tianming Liu, Jiajian Shen, William W Wong, and Wei Liu. Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy. Medical Physics, 2023.
  30. Dongliang Guo, Zhixuan Chu, and Sheng Li. Fair Attribute Completion on Graph with Missing Attributes. International Conference on Learning Representations (ICLR), 2023.
  31. Daiqing Qi, Handong Zhao, and Sheng Li. Better Generative Replay for Continual Federated Learning. International Conference on Learning Representations (ICLR), 2023.
  32. Ronghang Zhu, Xiang Yu, and Sheng Li. Progressive Mix-Up for Few-Shot Supervised Multi-Source Domain Transfer. International Conference on Learning Representations (ICLR), 2023.
  33. Zhaiming Shen, Ming-Jun Lai, Sheng Li. Graph-based Semi-supervised Local Clustering with Few Labeled Nodes. The 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023
  34. Yunyi Zhou, Zhixuan Chu, Yijia Ruan, Ge Jin, Yuchen Huang, and Sheng Li. pTSE: A Multi-model Ensemble Method for Probabilistic Time Series Forecasting. The 32nd International Joint Conference on Artificial Intelligence (IJCAI), 2023.
  35. Yitian Zhang, Yue Bai, Chang Liu, Huan Wang, Sheng Li, and Yun Fu. Frame Flexible Network. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  36. Zhixuan Chu, Ruopeng Li, Stephen Rathbun, and Sheng Li. Continual Causal Inference with Incremental Observational Data. The 39th IEEE International Conference on Data Engineering (ICDE), 2023.
  37. Saed Rezayi, Handong Zhao, Ronghang Zhu, and Sheng Li. XDC: Adaptive Cross Domain Short Text Clustering. SIAM International Conference on Data Mining (SDM), 2023.
  38. Zhixuan Chu, Mechelle Claridy, Jose Cordero, Sheng Li, and Stephen Rathbun. Estimating Propensity Scores with Deep Adaptive Variable Selection. SIAM International Conference on Data Mining (SDM), 2023.
  39. Sheng Li. Towards Trustworthy Representation Learning. SIAM International Conference on Data Mining (SDM) - Blue Sky Idea Track, 2023.
  40. Weili Shi, Xueying Yang, Xujiang Zhao, Haifeng Chen, Zhiqiang Tao, and Sheng Li. Calibrate Graph Neural Networks under Out-of-Distribution Nodes via Deep Q-learning. The 32nd ACM International Conference on Information and Knowledge Management (ACM CIKM), 2023.
  41. Zhixuan Chu and Sheng Li. Continual Causal Inference: Challenges and Opportunities. The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI) Bridge Program - Continual Causality, 2023.
  42. Zhanwen Chen, Saed Rezayi, Sheng Li. More Knowledge, Less Bias: Unbiasing Scene Graph Generation with Explicit Ontological Adjustment. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023.
  43. Weili Shi*, Zhongliang Zhou*, Ben Letcher, Nathaniel Hitt, Yoichiro Kanno, Ryo Futamura, Osamu Kishida, Kentar Morita, and Sheng Li. Aging Contrast: A Contrastive Learning Framework for Fish Re-identification Across Seasons and Years. The 36th Australasian Joint Conference on Artificial Intelligence (AJCAI), 2023.
  44. Hemadri Jayalath, Ghadeer Yassin, Lakshmish Ramaswamy, and Sheng Li. Continual Optimization of In-Production Machine Learning Systems through Semantic Analysis of User Feedback. The 15th International Conference on Agents and Artificial Intelligence (ICAART), 2023.
  45. Zhongliang Zhou, Wayland Yeung, Saber Soleymani, Nathan Gravel, Mariah Salcedo, Sheng Li, and Natarajan Kannan. Explaining the blackbox - Unraveling Protein Language Model's Learning Mechanisms for Kinase-Specific Phosphorylation Prediction. The ICML Workshop on Computational Biology, 2023.
  46. Wenxiong Liao, Zhengliang Liu, Yiyang Zhang, Xiaoke Huang, Fei Qi, Siqi Ding, Hui Ren, Zihao Wu, Haixing Dai, Sheng Li, Lingfei Wu, Ninghao Liu, Quanzheng Li, Tianming Liu, Xiang Li, and Hongmin Cai. Coarse-to-fine Knowledge Graph Domain Adaptation based on Distantly-supervised Iterative Training. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023.

    47. 2022
  47. Wayland Yeung*, Zhongliang Zhou*, Sheng Li, and Natarajan Kannan. Alignment-Free Estimation of Sequence Conservation for Identifying Functional Sites Using Protein Sequence Embeddings. Briefings in Bioinformatics, 2022. (* indicates equal contribution)
  48. Wayland Yeung*, Zhongliang Zhou*, Liju Mathew, Nathan Gravel, Rahil Taujale, Brady O’Boyle, Mariah Salcedo, Aarya Venkat, William Lanzilotta, Sheng Li, and Natarajan Kannan. Tree Visualizations of Protein Sequence Embedding Space Enable Improved Functional Clustering of Diverse Protein Superfamilies. Briefings in Bioinformatics, 2022. (* indicates equal contribution)
  49. Liuyi Yao, Yaliang Li, Sheng Li, Jinduo Liu, Mengdi Huai, Aidong Zhang, and Jing Gao. Concept-Level Model Interpretation from the Causal Aspect. IEEE Trans. Knowledge and Data Engineering (T-KDE), 2022.
  50. Weili Shi, Ronghang Zhu, and Sheng Li. Pairwise Adversarial Training for Unsupervised Class-imbalanced Domain Adaptation. The 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022.
  51. Ronghang Zhu and Sheng Li. CrossMatch: Cross-Classifier Consistency Regularization for Open-Set Single Domain Generalization. International Conference on Learning Representations (ICLR), 2022.
  52. Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Chen Zhen, Tianming Liu, and Sheng Li. AgriBERT: Knowledge-Infused Agricultural Language Models for Matching Food and Nutrition. The 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022.
  53. Ronghang Zhu and Sheng Li. Self-supervision based Semantic Alignment for Unsupervised Domain Adaptation. SIAM International Conference on Data Mining (SDM), 2022.
  54. Zhixuan, Chu, Stephen Rathbun, and Sheng Li. Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Observational Data. SIAM International Conference on Data Mining (SDM), 2022.
  55. Yue Bai, Zhiqiang Tao, Lichen Wang, Sheng Li, Yu Yin, and Yun Fu. Collaborative Attention Mechanism for Multi-Modal Time Series Classification. SIAM International Conference on Data Mining (SDM), 2022.
  56. Saed Rezayi, Handong Zhao and Sheng Li. XDC: Adversarial Adaptive Cross Domain Face Clustering. The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), 2022. (Poster)
  57. Zhixuan Chu, Stephen Rathbun and Sheng Li. Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials. AHLI Conference on Health, Inference and Learning (CHIL), 2022.
  58. Zhixuan Chu, Hui Ding, Guang Zeng, Yuchen Huang, Tan Yan, Yulin Kang and Sheng Li. Hierarchical Capsule Prediction Network for Marketing Campaigns Effect. The 31st ACM International Conference on Information and Knowledge Management (ACM CIKM), 2022.
  59. Xueying Yang, Jiamian Wang, Xujiang Zhao, Sheng Li and Zhiqiang Tao. Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty. The 31st ACM International Conference on Information and Knowledge Management (ACM CIKM), 2022.
  60. Weili Shi and Sheng Li. Improving Robustness of Vision Transformers via Data-Augmented Virtual Adversarial Training. IEEE International Conference on Big Data (IEEE BigData), 2022.
  61. Zhongliang Zhou, Nathaniel Hitt, Benjamin Letcher, Weili Shi, and Sheng Li. Pigmentation-based Visual Learning for Salvelinus fontinalis Individual Re-identification. IEEE International Conference on Big Data (IEEE BigData), 2022.
  62. Saed Rezayi, Haixing Dai, Zhengliang Liu, Zihao Wu, Akarsh Hebbar, Andrew H. Burns, Lin Zhao, Dajiang Zhu, Xiang Li, Quanzheng Li, Wei Liu, Sheng Li, Tianming Liu. ClinicalRadioBERT: Knowledge-Infused Few Shot Learning for Clinical Notes Named Entity Recognition. International Workshop on Machine Learning in Medical Imaging (in conjunction with MICCAI), 2022.

    63. 2021
  63. Rahil Taujale*, Zhongliang Zhou*, Wayland Yeung, Kelley Moremen, Sheng Li, and Natarajan Kannan. Mapping the glycosyltransferase fold landscape using interpretable deep learning. Nature Communications, 2021. (* indicates equal contribution)
  64. Heng-Shiou Sheu, Zhixuan Chu, Daiqing Qi, and Sheng Li. Knowledge-Guided Article Embedding Refinement for Session-based News Recommendation. IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2021. [Code]
  65. Ronghang Zhu, Xiaodong Jiang, Jiasen Lu, and Sheng Li. Cross-Domain Graph Convolutions for Adversarial Unsupervised Domain Adaptation. IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2021.
  66. Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, and Aidong Zhang. A Survey on Causal Inference. ACM Trans. Knowledge Discovery from Data (TKDD), 2021.
  67. Zhixuan Chu, Stephen Rathbun and Sheng Li. Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data. The 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2021.
  68. Saed Rezayi, Handong Zhao, Sungchul Kim, Ryan Rossi, Nedim Lipka and Sheng Li. EDGE: Enriching Knowledge Graph Embeddings with External Text. The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2021. (Long Paper)
  69. Yue Bai, Lichen Wang, Zhiqiang Tao, Sheng Li and Yun Fu. Correlative Channel-Aware Fusion for Multi-View Time Series Classification. The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021.
  70. Ronghang Zhu, Zhiqiang Tao, Yaliang Li, and Sheng Li. Automated Graph Learning via Population Based Self-Tuning GCN. The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR), 2021.
  71. Liuyi Yao, Yaliang Li, Sheng Li, Mengdi Huai, Jing Gao and Aidong Zhang. SCI: Subspace Learning Based Counterfactual Inference for Individual Treatment Effect Estimation. The 30th ACM International Conference on Information and Knowledge Management (ACM CIKM), 2021.
  72. Ronghang Zhu and Sheng Li. Self-supervised Universal Domain Adaptation with Adaptive Memory Separation. IEEE International Conference on Data Mining (IEEE ICDM), 2021.
  73. Xiaowei Jia, Yiqun Xie, Sheng Li, Shengyu Chen, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, and Jordan Read. Physics-Guided Machine Learning from Simulation Data: An Application in Modeling Lake and River Systems. IEEE International Conference on Data Mining (IEEE ICDM), 2021.
  74. Ronghang Zhu, Xiaodong Jiang, Jiasen Lu and Sheng Li. Transferable Feature Learning on Graphs Across Visual Domains. IEEE International Conference on Multimedia and Expo (IEEE ICME), 2021.
  75. Kang Yuan, Sheng Li. 2.5D Pose Guided Human Image Generation. ACM International Conference on Multimedia Retrieval (ACM ICMR), 2021.
  76. Saed Rezayi, Nedim Lipka, Vishwa Vinay, Ryan A. Rossi, Franck Dernoncourt, Tracy H. King, Sheng Li. A Framework for Knowledge-Derived Query Suggestions. IEEE International Conference on Big Data (IEEE BigData), 2021.
  77. Saed Rezayi, Saber Soleymani, Hamid R. Arabnia and Sheng Li. Socially Aware Multimodal Deep Neural Networks for Fake News Classification. IEEE 4th International Conference on Multimedia Information Processing and Retrieval (IEEE MIPR), 2021.
  78. Sumer Singh, Sheng Li. Exploiting Auxiliary Data for Offensive Language Detection with Bidirectional Transformers. ACL Workshop on Online Abuse and Harms (ACL-WOAH), 2021.

    79. 2020
  79. Xiaodong Jiang, Ronghang Zhu, Pengsheng Ji, and Sheng Li. Co-embedding of Nodes and Edges with Graph Neural Networks. IEEE Trans. Pattern Analysis and Machine Intelligence (T-PAMI), 2020. [Code]
  80. Rahil Taujale, Aarya Venkat, Liang-Chin Huang, Zhongliang Zhou, Wayland Yeung, Khaled M Rasheed, Sheng Li, Arthur S Edison, Kelley W Moremen, Natarajan Kannan. Deep evolutionary analysis reveals the design principles of fold A glycosyltransferases. eLife, 2020.
  81. Jiahuan Ren, Zhao Zhang, Sheng Li, Yang Wang, Guangcan Liu, Shuicheng Yan, and Meng Wang. Learning Hybrid Representation by Robust Dictionary Learning in Factorized Compressed Space. IEEE Trans. Image Processing (T-IP), 2020.
  82. Liang‑Chin Huang, Wayland Yeung, Ye Wang, Huimin Cheng, Aarya Venkat, Sheng Li, Ping Ma, Khaled Rasheed, and Natarajan Kannan. Quantitative Structure–Mutation–Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction. BMC Bioinformatics, 2020.
  83. Fangyu Li, Jose Clemente, Maria Valero, Zion Tse, Sheng Li, WenZhan Song. Smart Home Monitoring System via Footstep Induced Vibrations. IEEE Systems Journal, 14(3): 3383 - 3389, 2020.
  84. Sheng Li and Handong Zhao. A Survey on Representation Learning for User Modeling. The 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  85. Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu and Jing Gao. Causal Inference Meets Machine Learning. The 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2020. (Tutorial)
  86. Zhixuan Chu, Stephen Rathbun and Sheng Li. Matching in Selective and Balanced Representation Space for Treatment Effects Estimation. The 29th ACM International Conference on Information and Knowledge Management (ACM CIKM), 2020.
  87. Abhilash Dorle, Fangyu Li, Wenzhan Song and Sheng Li. Learning Discriminative Virtual Sequences for Time Series Classification. The 29th ACM International Conference on Information and Knowledge Management (ACM CIKM), 2020.
  88. Heng-Shiou Sheu and Sheng Li. Context-aware Graph Embedding for Session-based News Recommendation. The 14th ACM Conference on Recommender Systems (ACM RecSys), 2020. [Code]

    89. 2019
  89. Sheng Li*, Zhiqiang Tao*, Kang Li, Yun Fu. Visual to Text: Survey of Image and Video Captioning. IEEE Trans. Emerging Topics in Computational Intelligence (T-ETCI), 2019. (* indicates equal contribution)
  90. Zhiqiang Tao, Hongfu Liu, Sheng Li, Zhengming Ding, and Yun Fu. Marginalized Multi-View Ensemble Clustering. IEEE Trans. Neural Networks and Learning Systems (TNNLS), 2019.
  91. Zhao Zhang, Yan Zhang, Sheng Li, Guangcan Liu, Shuicheng Yan, Meng Wang: Flexible Auto-weighted Local-coordinate Concept Factorization: A Robust Framework for Unsupervised Clustering. IEEE Trans. Knowledge and Data Engineering (T-KDE), 2019.
  92. Zhengming Li, Zheng Zhang, Jie Qin, Sheng Li, Hongmin Cai. Low-Rank Analysis–Synthesis Dictionary Learning with Adaptively Ordinal Locality. Neural Networks (NN), 2019.
  93. Jianyi Liu, Rui Qiao, Yueying Li, Sheng Li. Witness Detection in Multi-Instance Regression and Its Application for Age Estimation. Multimedia Tools and Applications (MTA), 2019.
  94. Xiaodong Jiang, Pengsheng Ji and Sheng Li. CensNet: Convolution with Edge-Node Switching in Graph Neural Networks. The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019.
  95. Liuyi Yao, Sheng Li, Yaliang Li, Hongfei Xue, Jing Gao, Aidong Zhang. On the Estimation of Treatment Effect with Text Covariates. The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019.
  96. Zhao Zhang, Weiming Jiang, Zheng Zhang, Sheng Li, Guangcan Liu, Jie Qin. Scalable Block-Diagonal Locality-Constrained Projective Dictionary Learning. The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019.
  97. Zhiqiang Tao, Sheng Li, Zhaowen Wang, Chen Fang, Longqi Yang, Handong Zhao and Yun Fu. Log2Intent: Towards Interpretable User Modeling via Recurrent Semantics Memory Unit. The 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2019. (Oral Presentation)
  98. Xiaowei Jia, Sheng Li, Handong Zhao, Sungchul Kim and Vipin Kumar. Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training? The 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2019.
  99. Jiuxiang Gu, Handong Zhao, Zhe Lin, Sheng Li, Jianfei Cai, Mingyang Ling. Scene Graph Generation with External Knowledge and Image Reconstruction. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
  100. Xiaowei Jia, Sheng Li, Ankush Khandelwal, Guruprasad Nayak, Anuj Karpatne, Vipin Kumar. Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection. SIAM International Conference on Data Mining (SDM), 2019.
  101. Zheng Zhang, Guosen Xie, Yang Li, Sheng Li and Zi Huang. SADIH: Semantic-Aware DIscrete Hashing. The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), 2019.
  102. Donghyun Kim, Sungchul Kim, Handong Zhao, Sheng Li, Ryan Rossi and Eunyee Koh. Domain Switch-Aware Holistic Recurrent Neural Network for Modeling Multi-Domain User Behavior. The 12th ACM International Conference on Web Search and Data Mining (WSDM), 2019.
  103. Xueyu Mao, Saayan Mitra and Sheng Li. Training Streaming Factorization Machines with Alternating Least Squares. The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR), 2019.
  104. Zhao Zhang, Jiahuan Ren, Sheng Li, Richang Hong, Zhengjun Zha and Meng Wang. Robust Subspace Discovery by Block-diagonal Adaptive Locality-constrained Representation. The 27th ACM International Conference on Multimedia (ACM MM), 2019.
  105. Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao and Aidong Zhang. ACE: Adaptively Similarity-preserved Representation Learning for Individual Treatment Effect Estimation. IEEE International Conference on Data Mining (IEEE ICDM), 2019.
  106. Zhao Zhang, Lei Wang, Yang Wang, Sheng Li, Zheng Zhang, Zhengjun Zha, and Meng Wang. Adaptive Structure-Constrained Robust Latent Low-Rank Coding for Image Recovery. IEEE International Conference on Data Mining (IEEE ICDM), 2019.
  107. Zhao Zhang, Yan Zhang, Sheng Li, Guangcan Liu, Meng Wang and Shuicheng Yan. Robust Unsupervised Flexible Auto-weighted Local-Coordinate Concept Factorization for Image Clustering. IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP), 2019.

    108. 2018
  108. Sheng Li, Ming Shao, Yun Fu: Person Re-identification by Cross-View Multi-Level Dictionary Learning. IEEE Trans. Pattern Analysis and Machine Intelligence (T-PAMI), 2018. [Code]
  109. Sheng Li, Kang Li, Yun Fu: Self-Taught Low-Rank Coding for Visual Learning. IEEE Trans. Neural Networks and Learning Systems (T-NNLS), 29(3): 645-656, 2018. [Code]
  110. Sheng Li, Kang Li, Yun Fu: Early Recognition of 3D Human Actions. ACM Trans. Multimedia Computing Communications and Applications (TOMM), 14(1s): 20:1-20:21, 2018.
  111. Sheng Li, Ming Shao, Yun Fu: Multi-View Low-Rank Analysis with Applications to Outlier Detection. ACM Trans. Knowledge Discovery from Data (TKDD), 12(3): 32:1-32:22, 2018. [Code]
  112. Hongfu Liu, Ming Shao, Sheng Li, Yun Fu: Infinite Ensemble Clustering. Data Mining and Knowledge Discovery (DMKD), 32(2): 385-416, 2018.
  113. Chengcheng Jia, Ming Shao, Sheng Li, Handong Zhao, Yun Fu. Stacked Denoising Tensor Auto-Encoder for Action Recognition with Spatiotemporal Corruptions, IEEE Trans. Image Processing (T-IP), 27(4): 1878-1887, 2018.
  114. Zhiqiang Tao, Hongfu Liu, Sheng Li, Zhengming Ding, Yun Fu: Robust Spectral Ensemble Clustering via Rank Minimization. ACM Trans. Knowledge Discovery from Data(TKDD), 2018.
  115. Yan Zhang, Zhao Zhang, Sheng Li, Jie Qin, Guangcan Liu, Meng Wang, Shuicheng Yan: Unsupervised Nonnegative Adaptive Feature Extraction for Data Representation. IEEE Trans. Knowledge and Data Engineering (T-KDE), 2018.
  116. Kai Li, Zhengming Ding, Sheng Li, Yun Fu: Towards Resolution-Invariant Person Re-identification via Projective Dictionary Learning. IEEE Trans. Neural Networks and Learning Systems (T-NNLS), 2018.
  117. Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, and Aidong Zhang. Representation Learning for Treatment Effect Estimation from Observational Data. The Thirty-second Annual Conference on Neural Information Processing Systems (NeurIPS), 2018. [Code]
  118. Kai Li, Sheng Li, Zhengming Ding, Weidong Zhang, and Yun Fu. Latent Discriminant Subspace Representations for Multi-view Outlier Detection. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018.
  119. Kai Li, Zhengming Ding, Sheng Li, and Yun Fu. Discriminative Semi-coupled Projective Dictionary Learning for Low-Resolution Person Re-Identification. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018.
  120. Shumin Jing, Sheng Li. Contextual Collaborative Filtering for Student Response Prediction in Mixed-Format Tests. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018. (Poster)
  121. Zhengming Ding, Sheng Li, Ming Shao and Yun Fu. Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation. European Conference on Computer Vision (ECCV), 2018.
  122. Tuan Manh Lai, Trung Bui, Sheng Li. A Review on Deep Learning Techniques Applied to Answer Selection. The 27th International Conference on Computational Linguistics (COLING), 2018.
  123. Zhengming Ding, Ming Shao, Sheng Li and Yun Fu. Generic Embedded Semantic Dictionary for Robust Multi-label Classification. IEEE International Conference on Big Knowledge (ICBK), 2018.
  124. Tuan Manh Lai, Trung Bui, Nedim Lipka, Sheng Li. Supervised Transfer Learning for Product Information Question Answering. IEEE 17th International Conference on Machine Learning and Applications (ICMLA), 2018.
  125. Tuan Manh Lai, Trung Bui, Sheng Li, Nedim Lipka. A Simple End-to-End Question Answering Model for Product Information. ACL Workshop on Economics and Natural Language Processing (ECONLP), 2018.
  126. Zhao Zhang, Weiming Jiang, Sheng Li, Jie Qin, Guangcan Liu, Shuicheng Yan Robust Locality-Constrained Label Consistent KSVD by Joint Sparse Embedding. International Conference on Pattern Recognition (ICPR), 2018.
  127. Jiahuan Ren, Zhao Zhang, Sheng Li, Guangcan Liu, Meng Wang, Shuicheng Yan. Robust Projective Low-Rank and Sparse Representation by Robust Dictionary Learning. International Conference on Pattern Recognition (ICPR), 2018.
  128. Huan Zhang, Zhao Zhang, Sheng Li, Qiaolin Ye, Mingbo Zhao, Meng Wang. Robust Adaptive Label Propagation by Double Matrix Decomposition. International Conference on Pattern Recognition (ICPR), 2018.
  129. Lei Wang, Zhao Zhang, Sheng Li, Guangcan Liu, Chenping Hou and Jie Qin. Similarity-Adaptive Latent Low-Rank Representation for Robust Data Representation. The 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2018.

    130. 2017
  130. Kang Li, Sheng Li, Sangmin Oh, Yun Fu. Videography based Unconstrained Video Analysis, IEEE Trans. Image Processing (T-IP), 26(5): 2261-2273, 2017.
  131. Guoqiang Zhong, Yan Zheng, Sheng Li, Yun Fu: SLMOML: Online Metric Learning with Global Convergence, IEEE Trans. Circuits and Systems for Video Technology (T-CSVT), 2017.
  132. Sheng Li, Yun Fu. Matching on Balanced Nonlinear Representations for Treatment Effects Estimation. The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS), 2017.
  133. Sheng Li, Yun Fu. Robust Multi-Label Semi-Supervised Classification. IEEE International Conference on Big Data (IEEE BigData), 2017.
  134. Sheng Li, Hongfu Liu, Zhiqiang Tao, and Yun Fu. Multi-View Graph Learning with Adaptive Label Propagation. IEEE International Conference on Big Data (IEEE BigData), 2017. [Code]
  135. Zhiqiang Tao, Hongfu Liu, Sheng Li, Zhengming Ding, and Yun Fu. From Ensemble Clustering to Multi-View Clustering. The 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017.

    136. 2016
  136. Sheng Li, Yun Fu: Learning Robust and Discriminative Subspace with Low-Rank Constraints. IEEE Trans. Neural Networks and Learning Systems (T-NNLS), 27(11): 2160-2173, 2016. [Code]
  137. Sheng Li, Nikos Vlassis, Jaya Kawale and Yun Fu. Matching via Dimensionality Reduction for Estimation of Treatment Effects in Digital Marketing Campaigns. The 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016.
  138. Sheng Li. Learning Robust Representations for Data Analytics.  The 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016. (Poster)
  139. Sheng Li, Yaliang Li and Yun Fu. Multi-View Time Series Classification: A Discriminative Bilinear Projection Approach. The 25th ACM International Conference on Information and Knowledge Management (ACM CIKM), 2016.
  140. Zhiqiang Tao, Hongfu Liu, Sheng Li and Yun Fu. Robust Spectral Ensemble Clustering. The 25th ACM International Conference on Information and Knowledge Management (ACM CIKM), 2016.
  141. Hongfu Liu, Ming Shao, Sheng Li and Yun Fu. Infinite Ensemble for Image Clustering. The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016.
  142. Sheng Li, Yun Fu. Unsupervised Transfer Learning via Low-Rank Coding for Image Clustering, International Joint Conference on Neural Networks (IJCNN), 2016. [Code]
  143. Guoqiang Zhong, Yan Zheng, Sheng Li and Yun Fu. Scalable Large Margin Online Metric Learning, International Joint Conference on Neural Networks (IJCNN), 2016.

    144. 2015
  144. Sheng Li, Yun Fu: Learning Balanced and Unbalanced Graphs via Low-Rank Coding. IEEE Trans. Knowledge and Data Engineering (T-KDE), 27(5): 1274-1287, 2015. [Code]
  145. Sheng Li, Kang Li and Yun Fu. Temporal Subspace Clustering for Human Motion Segmentation, International Conference on Computer Vision (ICCV), 2015. [Code]
  146. Sheng Li, Ming Shao and Yun Fu. Cross-View Projective Dictionary Learning for Person Re-identification. International Joint Conference on Artificial Intelligence (IJCAI), 2015. [Code]
  147. Ming Shao, Sheng Li, Zhengming Ding and Yun Fu. Deep Linear Coding for Fast Graph Clustering. International Joint Conference on Artificial Intelligence (IJCAI), 2015.
  148. Sheng Li, Jaya Kawale and Yun Fu. Deep Collaborative Filtering via Marginalized Denoising Auto-encoder. The 24th ACM International Conference on Information and Knowledge Management (ACM CIKM), 2015.
  149. Sheng Li, Jaya Kawale and Yun Fu. Predicting User Behavior in Display Advertising via Dynamic Collective Matrix Factorization, The 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR), 2015.
  150. Sheng Li, Ming Shao and Yun Fu. Multi-view Low-Rank Analysis for Outlier Detection. SIAM International Conference on Data Mining (SDM), 2015. [Code]

    151. 2014
  151. Liangyue Li*, Sheng Li*, Yun Fu: Learning Low-Rank and Discriminative Dictionary for Image Classification. Image and Vision Computing (IVC), 32(10): 814-823, 2014. (* indicates equal contribution. Invited Paper) [Code]
  152. Ya Su, Sheng Li, Shengjin Wang, and Yun Fu, Submanifold Decomposition, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 24(11): 1885-1897, 2014.
  153. Sheng Li, Yun Fu, Robust Subspace Discovery through Supervised Low-Rank Constraints,  SIAM International Conference on Data Mining (SDM), 2014. (Best Paper Award) [Code]
  154. Kang Li, Sheng Li, and Yun Fu, Early Classification of Ongoing Observation,  IEEE International Conference on Data Mining (IEEE ICDM), 2014.
  155. Ming Shao, Sheng Li, Tongliang Liu, Dacheng Tao, Thomas S. Huang, and Yun Fu, Learning Relative Features Through Adaptive Pooling for Image Classification, IEEE International Conference on Multimedia and Expo (IEEE ICME), 2014. ( Best Paper Award Candidate)
  156. Sheng Li, Ming Shao, and Yun Fu, Locality Linear Fitting One-class SVM with Low-Rank Constraints for Outlier Detection, International Joint Conference on Neural Networks (IJCNN), 2014.

    157. Before 2013
  157. Sheng Li, Yun Fu. Low-Rank Coding with b-Matching Constraint for Semi-supervised Classification, International Joint Conference on Artificial Intelligence (IJCAI), 2013. [Code]
  158. Liangyue Li, Sheng Li, and Yun Fu. Discriminative Dictionary Learning with Low-Rank Regularization for Face Recognition. The 10th IEEE International Conference on Automatic Face and Gesture Recognition (IEEE FG), 2013. (Best Student Paper Honorable Mention Award) [Code]
  159. Sheng Li, Peng Li, and Yun Fu. Understanding 3D Human Torso Shape via Manifold Clustering. SPIE Defense, Security, and Sensing (DSS), 2013.
  160. Xiao-Yuan Jing, Sheng Li, David Zhang, Jian Yang, Jing-Yu Yang: Supervised and Unsupervised Parallel Subspace Learning for Large-Scale Image Recognition. IEEE Transactions on Circuits System for Video Technology (T-CSVT), 22(10): 1497-1511, 2012.
  161. Xiao-Yuan Jing, Sheng Li, David Zhang, Chao Lan, Jingyu Yang: Optimal Subset-division based Discrimination and Its Kernelization for Face and Palmprint Recognition. Pattern Recognition (PR), 45(10): 3590-3602, 2012.
  162. Xiao-Yuan Jing, Sheng Li, Wen-Qian Li, etc. Palmprint and Face Multi-Modal Biometric Recognition based on SDA-GSVD and Its Kernelization. Sensors, 12(5), pp. 5551-5571, 2012.
  163. Xiao-Yuan Jing, Chao Lan, David Zhang, Jing-Yu Yang, Min Li, Sheng Li, Songhao Zhu: Face Feature Extraction and Recognition based on Discriminant Subclass-center Manifold Preserving Projection. Pattern Recognition Letters (PRL), 33(6), pp. 709-717, 2012.
  164. Xiao-Yuan Jing, Sheng Li, Chao Lan, David Zhang, Jingyu Yang, Qian Liu: Color Image Canonical Correlation Analysis for Face Feature Extraction and Recognition. Signal Processing (SP), 91(8): 2132-2140, 2011.
  165. Sheng Li, Xiao-Yuan Jing, David Zhang, Yong-Fang Yao, Lu-Sha Bian. A Novel Kernel Discriminant Feature Extraction Framework based on Mapped Virtual Samples for Face Recognition. IEEE International Conference on Image Processing (ICIP): 3005-3008, 2011.
  166. Xiao-Yuan Jing, Sheng Li, David Zhang, Jingyu Yang. Face Recognition based on Local Uncorrelated and Weighted Global Uncorrelated Discriminant Transforms. IEEE International Conference on Image Processing (ICIP): 3049-3052, 2011.
  167. Xiao-Yuan Jing, Sheng Li, David Zhang, Jiang-Yue Man and Jing-Yu Yang. Supervised Local Sparsity Preserving Projection for Face Feature Extraction, The First Asian Conference on Pattern Recognition (ACPR), pp. 555-559, 2011.
  168. Xiao-Yuan Jing, Sheng Li, Yongfang Yao, etc.. Multi-Modal Biometric Feature Extraction and Recognition Based on Subclass Discriminant Analysis (SDA) and Generalized Singular Value Decomposition (GSVD). International Conference on Hand-Based Biometrics (ICHB), 2011.
  169. Sheng Li, Xiao-Yuan Jing, Lu-Sha Bian, Shi-Qiang Gao, Qian Liu, Yong-Fang Yao: Facial Image Recognition Based on a Statistical Uncorrelated Near Class Discriminant Approach. IEICE Transactions on Information and Systems, 93-D(4): 934-937, 2010.
  170. Xiao-Yuan Jing, Sheng Li, Yong-Fang Yao, Lu-Sha Bian, Jingyu Yang. Kernel Uncorrelated Adjacent-class Discriminant Analysis. International Conference on Pattern Recognition (ICPR): 706-709, 2010.
  171. Chao Lan, Xiao-yuan Jing, Sheng Li, Lu-Sha Bian, Yong-Fang Yao. Exploring the Natural Discriminative Information of Sparse Representation for Feature Extraction. The 3rd International Congress on Image and Signal Processing (CISP): 916-920, 2010.
  172. Xiao-Yuan Jing, Qian Liu, Chao Lan, Jiangyue Man, Sheng Li, David Zhang. Holistic Orthogonal Analysis of Discriminant Transforms for Color Face Recognition. IEEE International Conference on Image Processing (ICIP): 3841-3844, 2010.
  173. Sheng Li, Yong-Fang Yao, Xiao-Yuan Jing, Heng Chang, Shi-Qiang Gao, David Zhang, Jing-Yu Yang: Face Recognition Based on Nonlinear DCT Discriminant Feature Extraction Using Improved Kernel DCV. IEICE Transactions on Information and Systems, 92-D(12): 2527-2530, 2009.
  174. Sheng Li, Xiao-Yuan Jing, Qian Liu, etc.. Kernel-Plural Discriminant Analysis Based on Fourier Transform and Its Application to Face Recognition.  Chinese Conference on Pattern Recognition (CCPR): 503-507, 2009. (in Chinese)