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Xiaofeng Cao 0002
Person information
- affiliation: Jilin University, School of Artificial Intelligence, Changchun, China
- affiliation (PhD 2021): University of Technology Sydney, Australian Artificial Intelligence Institute, Advanced Analytics Institute, Australia
Other persons with the same name
- Xiaofeng Cao — disambiguation page
- Xiaofeng Cao 0001
— National University of Defense Technology, NUDT, Science and Technology on Information Systems Engineering Laboratory, Changsha, China
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2020 – today
- 2026
[j30]Xiaofeng Cao
, Mingwei Xu
, Xin Yu
, Jiangchao Yao
, Wei Ye
, Sheng-Jun Huang
, Min-Ling Zhang
, Ivor W. Tsang
, Yew-Soon Ong
, James T. Kwok
, Heng Tao Shen
:
Analytical Survey of Learning with Low-Resource Data: From Analysis to Investigation. ACM Comput. Surv. 58(6): 144:1-144:47 (2026)
[j29]Yucheng Jiang, Jiateng Li, Yuan Tian, Jiangchao Yao, Xin Yu, Wei Ye, Xiaofeng Cao:
Positional Relation Contextual Mixing for Imbalanced Classification. Mach. Learn. 115(3): 62 (2026)
[j28]Gabriel Tjio, Jie Zhang, Xulei Yang, Yun Xing, Nhat Chung, Xiaofeng Cao, Ivor W. Tsang, Chee Keong Kwoh, Qing Guo:
FOCUS: Frequency-Optimized Conditioning of diffUSion models for mitigating catastrophic forgetting during test-time adaptation. Mach. Vis. Appl. 37(2): 40 (2026)
[j27]Zeyang Zhang
, Xiaofeng Cao
, Xiang Zhang, Li Peng
, Lijia Ma
, Jielong Yang
:
ViDR-GNN: Vision Implicit Discriminative Reorganization Graph Neural Networks. IEEE Trans. Multim. 28: 2172-2185 (2026)
[c18]Yihua Shao, Deyang Lin, Minxi Yan, Siyu Chen, Fanhu Zeng, Minwen Liao, Ao Ma, Ziyang Yan, Haozhe Wang, Yan Wang, Zhi Chen, Xiaofeng Cao, Haotong Qin, Hao Tang, Jingcai Guo:
TR-DQ: Time-Rotation Diffusion Quantization. AAAI 2026: 8869-8877
[c17]Disen Hu, Xun Jiang, Xiaofeng Cao, Zheng Wang, Jingkuan Song, Heng Tao Shen, Xing Xu:
Hyper-Opinion Vagueness Quantification for Robust Multimodal Learning. AAAI 2026: 21831-21839
[c16]Bohao Qu, Xiaofeng Cao, Bing Li, Menglin Zhang, Tuan-Anh Vu, Di Lin, Qing Guo:
Exploiting Geometric Structures for Modeling Multi-Agent Behaviors: A New Thinking. AAAI 2026: 25027-25035
[i25]Jiaying Wu, Can Gao, Jinglu Hu, Hui Li, Xiaofeng Cao, Jingcai Guo:
PMCE: Probabilistic Multi-Granularity Semantics with Caption-Guided Enhancement for Few-Shot Learning. CoRR abs/2601.14111 (2026)
[i24]Yue Niu, Zhaokai Sun, Jiayi Yang, Xiaofeng Cao, Rui Fan, Xin Sun, Hanli Wang, Wei Ye:
Revealing Combinatorial Reasoning of GNNs via Graph Concept Bottleneck Layer. CoRR abs/2603.02025 (2026)
[i23]Shiyuan Li, Yixin Liu, Yu Zheng, Xiaofeng Cao, Shirui Pan, Heng Tao Shen:
Towards One-for-All Anomaly Detection for Tabular Data. CoRR abs/2603.14407 (2026)- 2025
[j26]Yang Tao, Xiaofeng Cao
, Yi Chang:
Towards a structured analysis of domain perturbations in Tubular Geometry. Pattern Recognit. 168: 111815 (2025)
[j25]Menglin Zhang
, Xiaoxin Guo
, Xiaofeng Cao
, Shuifa Sun
, Huazhu Fu
, Qing Guo
:
Lighting is Unreliable: Adversarial Video Relighting Against rPPG Heart Rate Measurement. IEEE Trans. Inf. Forensics Secur. 20: 8341-8356 (2025)
[j24]Wei Ye
, Wengang Guo, Shuhao Tang
, Hao Tian
, Xin Sun
, Xiaofeng Cao
, Heng Tao Shen
:
Distributional Shortest-Path Graph Kernels. IEEE Trans. Knowl. Data Eng. 37(11): 6367-6378 (2025)
[c15]Yuxiao Lee, Xiaofeng Cao, Jingcai Guo, Wei Ye, Qing Guo, Yi Chang:
Concept Matching with Agent for Out-of-Distribution Detection. AAAI 2025: 4562-4570
[c14]Menglin Zhang, Xiaoxin Guo, Bohao Qu, Xiaofeng Cao, Shuifa Sun, Qing Guo:
PhysLight: Accurate rPPG Heart Rate Measurement with Adaptive Video Relighting. ICME 2025: 1-6
[c13]Yadong Sun, Xiaofeng Cao, Ivor W. Tsang, Heng Tao Shen:
Analytical Construction on Geometric Architectures: Transitioning from Static to Temporal Link Prediction. ICML 2025
[c12]Miaoge Li, Jingcai Guo, Richard Yi Da Xu
, Dongsheng Wang, Xiaofeng Cao, Zhijie Rao, Song Guo:
TsCA: On the Semantic Consistency Alignment via Conditional Transport for Compositional Zero-Shot Learning. IJCAI 2025: 5607-5615
[i22]Yun Xing, Qing Guo, Xiaohong Li, Yihao Huang, Xiaofeng Cao, Di Lin, Ivor W. Tsang, Lei Ma:
Time-variant Image Inpainting via Interactive Distribution Transition Estimation. CoRR abs/2506.23461 (2025)
[i21]Gabriel Tjio, Jie Zhang, Xulei Yang, Yun Xing, Nhat Chung, Xiaofeng Cao, Ivor W. Tsang, Chee Keong Kwoh, Qing Guo:
FOCUS: Frequency-Optimized Conditioning of DiffUSion Models for mitigating catastrophic forgetting during Test-Time Adaptation. CoRR abs/2508.14437 (2025)
[i20]Yuxiao Lee, Xiaofeng Cao, Yen-Wei Chen, Jiangchao Yao, Jingkuan Song, Heng Tao Shen:
An Empirical Analysis of VLM-based OOD Detection: Mechanisms, Advantages, and Sensitivity. CoRR abs/2509.13375 (2025)
[i19]Jiaan Luo, Feng Hong, Qiang Hu, Xiaofeng Cao, Feng Liu, Jiangchao Yao:
Long-tailed Recognition with Model Rebalancing. CoRR abs/2510.08177 (2025)
[i18]Xiaofeng Cao, Mingwei Xu, Xin Yu, Jiangchao Yao, Wei Ye, Shengjun Huang, Minling Zhang, Ivor W. Tsang, Yew Soon Ong, James T. Kwok, Heng Tao Shen:
Analytical Survey of Learning with Low-Resource Data: From Analysis to Investigation. CoRR abs/2510.08962 (2025)
[i17]Xing Wei
, Chunchun Chen, Rui Fan, Xiaofeng Cao, Sourav Medya, Wei Ye:
Preference-driven Knowledge Distillation for Few-shot Node Classification. CoRR abs/2510.10116 (2025)- 2024
[j23]Yang Tao, Kai Guo, Yizhen Zheng
, Shirui Pan
, Xiaofeng Cao, Yi Chang:
Breaking the curse of dimensional collapse in graph contrastive learning: A whitening perspective. Inf. Sci. 657: 119952 (2024)
[j22]Xiaofeng Cao, Yaming Guo, Heng Tao Shen, Ivor W. Tsang, James T. Kwok:
Mentored Learning: Improving Generalization and Convergence of Student Learner. J. Mach. Learn. Res. 25: 325:1-325:45 (2024)
[j21]Bohao Qu
, Xiaofeng Cao
, Yi Chang
, Ivor W. Tsang
, Yew-Soon Ong
:
Diversifying Policies With Non-Markov Dispersion to Expand the Solution Space. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 11392-11408 (2024)
[j20]Weixin Bu, Xiaofeng Cao, Yizhen Zheng, Shirui Pan
:
Improving Augmentation Consistency for Graph Contrastive Learning. Pattern Recognit. 148: 110182 (2024)
[j19]Bike Chen
, Wei Peng
, Xiaofeng Cao
, Juha Röning
:
Hyperbolic Uncertainty Aware Semantic Segmentation. IEEE Trans. Intell. Transp. Syst. 25(2): 1275-1290 (2024)
[j18]Yu Wang
, Liang Hu
, Xiaofeng Cao
, Yi Chang
, Ivor W. Tsang
:
Enhancing Locally Adaptive Smoothing of Graph Neural Networks Via Laplacian Node Disagreement. IEEE Trans. Knowl. Data Eng. 36(3): 1099-1112 (2024)
[j17]Bohao Qu
, Xiaofeng Cao
, Qing Guo
, Yi Chang
, Ivor W. Tsang
, Chengqi Zhang
:
Transductive Reward Inference on Graph. IEEE Trans. Knowl. Data Eng. 36(11): 7217-7228 (2024)
[j16]Zhaogeng Liu
, Feng Ji
, Jielong Yang
, Xiaofeng Cao
, Muhan Zhang, Hechang Chen
, Yi Chang
:
Refining Euclidean Obfuscatory Nodes Helps: A Joint-Space Graph Learning Method for Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(9): 11720-11733 (2024)
[j15]Xiaofeng Cao
, Ivor W. Tsang
:
Distribution Matching for Machine Teaching. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12316-12329 (2024)
[c11]Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang:
A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. ECAI 2024: 2621-2628
[c10]Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor W. Tsang, Yang Liu, Qing Guo:
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks. ICLR 2024
[c9]Zhijie Rao, Jingcai Guo, Xiaocheng Lu, Jingming Liang, Jie Zhang, Haozhao Wang, Kang Wei, Xiaofeng Cao:
Dual Expert Distillation Network for Generalized Zero-Shot Learning. IJCAI 2024: 4833-4841
[c8]Shuhao Tang, Hao Tian, Xiaofeng Cao, Wei Ye:
Deep Hierarchical Graph Alignment Kernels. IJCAI 2024: 4964-4972
[c7]Yun Xing
, Qing Guo
, Xiaofeng Cao
, Ivor W. Tsang
, Lei Ma
:
MetaRepair: Learning to Repair Deep Neural Networks from Repairing Experiences. ACM Multimedia 2024: 1781-1790
[c6]Yadong Sun, Xiaofeng Cao, Yu Wang, Wei Ye, Jingcai Guo, Qing Guo:
Geometry Awakening: Cross-Geometry Learning Exhibits Superiority over Individual Structures. NeurIPS 2024
[c5]Mingwei Xu, Xiaofeng Cao, Ivor W. Tsang:
Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization. NeurIPS 2024
[i16]Feiyang Ye, Baijiong Lin
, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang
:
A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. CoRR abs/2401.09257 (2024)
[i15]Bohao Qu, Xiaofeng Cao, Qing Guo, Yi Chang, Ivor W. Tsang
, Chengqi Zhang:
Transductive Reward Inference on Graph. CoRR abs/2402.03661 (2024)
[i14]Zhijie Rao, Jingcai Guo, Xiaocheng Lu, Jingming Liang, Jie Zhang, Haozhao Wang, Kang Wei, Xiaofeng Cao:
Dual Expert Distillation Network for Generalized Zero-Shot Learning. CoRR abs/2404.16348 (2024)
[i13]Shuhao Tang, Hao Tian, Xiaofeng Cao, Wei Ye:
Deep Hierarchical Graph Alignment Kernels. CoRR abs/2405.05545 (2024)
[i12]Miaoge Li, Jingcai Guo, Richard Yi Da Xu, Dongsheng Wang, Xiaofeng Cao, Song Guo:
TsCA: On the Semantic Consistency Alignment via Conditional Transport for Compositional Zero-Shot Learning. CoRR abs/2408.08703 (2024)- 2023
[j14]Kai Guo
, Xiaofeng Cao, Zhining Liu
, Yi Chang:
Taming over-smoothing representation on heterophilic graphs. Inf. Sci. 647: 119463 (2023)
[j13]Bai Zhang
, Yixing Gao
, Feng Ji, Linbo Xie, Xiaofeng Cao, Yixiang Shan, Jielong Yang:
Towards fidelity of graph data augmentation via equivariance. Knowl. Based Syst. 280: 111017 (2023)
[j12]Xiaofeng Cao
, Weiyang Liu
, Ivor W. Tsang
:
Data-Efficient Learning via Minimizing Hyperspherical Energy. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13422-13437 (2023)
[j11]Yu Wang
, Liang Hu, Wanfu Gao, Xiaofeng Cao, Yi Chang:
AdaNS: Adaptive negative sampling for unsupervised graph representation learning. Pattern Recognit. 136: 109266 (2023)
[j10]Jiaoyan Zhao
, Yongsheng Liang, Shuangyan Yi, Qiangqiang Shen, Xiaofeng Cao:
Improving generalization of double low-rank representation using Schatten-p norm. Pattern Recognit. 138: 109352 (2023)
[c4]Yaming Guo, Kai Guo, Xiaofeng Cao, Tieru Wu, Yi Chang:
Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships. ICML 2023: 11905-11933
[c3]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang
, James T. Kwok:
Nonparametric Iterative Machine Teaching. ICML 2023: 40851-40870
[c2]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok:
Nonparametric Teaching for Multiple Learners. NeurIPS 2023
[i11]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang
, James T. Kwok:
Nonparametric Iterative Machine Teaching. CoRR abs/2306.03007 (2023)
[i10]Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor W. Tsang
, Yang Liu, Qing Guo:
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks. CoRR abs/2310.11890 (2023)
[i9]Mingwei Xu, Xiaofeng Cao, Ivor W. Tsang
, James T. Kwok:
Aggregation Weighting of Federated Learning via Generalization Bound Estimation. CoRR abs/2311.05936 (2023)
[i8]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang
, James T. Kwok:
Nonparametric Teaching for Multiple Learners. CoRR abs/2311.10318 (2023)- 2022
[j9]Jiaoyan Zhao
, Shuangyan Yi, Yongsheng Liang, Wei Liu, Xiaofeng Cao:
Robust active representation via ℓ2, p-norm constraints. Knowl. Based Syst. 235: 107639 (2022)
[j8]Xiaofeng Cao
, Ivor W. Tsang
:
Distribution Disagreement via Lorentzian Focal Representation. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6872-6889 (2022)
[j7]Xiaofeng Cao
, Ivor W. Tsang
, Jianliang Xu
:
Cold-Start Active Sampling Via γ-Tube. IEEE Trans. Cybern. 52(7): 6034-6045 (2022)
[j6]Xiaofeng Cao
, Ivor W. Tsang
:
Shattering Distribution for Active Learning. IEEE Trans. Neural Networks Learn. Syst. 33(1): 215-228 (2022)
[i7]Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang
:
Data-Efficient Learning via Minimizing Hyperspherical Energy. CoRR abs/2206.15204 (2022)
[i6]Xiaofeng Cao, Yaming Guo, Tieru Wu, Ivor W. Tsang
:
When an Active Learner Meets a Black-box Teacher. CoRR abs/2206.15205 (2022)
[i5]Xiaofeng Cao, Weixin Bu, Shengjun Huang, Ying-Peng Tang, Yaming Guo, Yi Chang, Ivor W. Tsang
:
A Survey of Learning on Small Data. CoRR abs/2207.14443 (2022)
[i4]Chen Zhang, Xiaofeng Cao, Yi Chang, Ivor W. Tsang
:
One-shot Machine Teaching: Cost Very Few Examples to Converge Faster. CoRR abs/2212.06416 (2022)- 2021
[b1]Xiaofeng Cao:
Distribution-based Active Learning. University of Technology Sydney, Australia, 2021
[j5]Xiaofeng Cao
:
High-dimensional cluster boundary detection using directed Markov tree. Pattern Anal. Appl. 24(1): 35-47 (2021)
[i3]Xiaofeng Cao, Ivor W. Tsang:
Bayesian Active Learning by Disagreements: A Geometric Perspective. CoRR abs/2105.02543 (2021)
[i2]Xiaofeng Cao, Ivor W. Tsang:
Distribution Matching for Machine Teaching. CoRR abs/2105.13809 (2021)- 2020
[j4]Xiaofeng Cao
:
A divide-and-conquer approach to geometric sampling for active learning. Expert Syst. Appl. 140 (2020)
[j3]Xiaofeng Cao
:
A structured perspective of volumes on active learning. Neurocomputing 377: 200-212 (2020)
2010 – 2019
- 2019
[j2]Xiaofeng Cao, Baozhi Qiu, Guandong Xu:
BorderShift: toward optimal MeanShift vector for cluster boundary detection in high-dimensional data. Pattern Anal. Appl. 22(3): 1015-1027 (2019)
[j1]Xiaofeng Cao
, Baozhi Qiu, Xiangli Li, Zenglin Shi, Guandong Xu
, Jianliang Xu
:
Multidimensional Balance-Based Cluster Boundary Detection for High-Dimensional Data. IEEE Trans. Neural Networks Learn. Syst. 30(6): 1867-1880 (2019)
[c1]Xiaofeng Xu
, Ivor W. Tsang
, Xiaofeng Cao, Ruiheng Zhang
, Chuancai Liu:
Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation. IJCAI 2019: 3989-3995
[i1]Xiaofeng Xu, Ivor W. Tsang, Xiaofeng Cao, Ruiheng Zhang, Chuancai Liu:
Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation. CoRR abs/1905.07933 (2019)
Coauthor Index

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last updated on 2026-04-13 22:53 CEST by the dblp team
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