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ORCIDXiaofeng 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
![[0000-0003-1839-8830]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-1839-8830")
— National University of Defense Technology, NUDT, Science and Technology on Information Systems Engineering Laboratory, Changsha, China
Other persons with a similar name
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2020 – today
- 2024
[j22]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)- [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) - [c7]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 - [c6]Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor W. Tsang, Yang Liu, Qing Guo:
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks. ICLR 2024 - [c5]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 - [i13]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) - [i12]Bohao Qu, Xiaofeng Cao, Qing Guo, Yi Chang, Ivor W. Tsang, Chengqi Zhang:
Transductive Reward Inference on Graph. CoRR abs/2402.03661 (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 2024-11-25 22:43 CET by the dblp team
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