Xiaofeng Cao

According to our database, Xiaofeng Cao authored at least 30 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Improving Augmentation Consistency for Graph Contrastive Learning.

Weixin Bu, Xiaofeng Cao, Yizhen Zheng, Shirui Pan

Pattern Recognit., April, 2024

Enhancing Locally Adaptive Smoothing of Graph Neural Networks Via Laplacian Node Disagreement.

Yu Wang, Liang Hu, Xiaofeng Cao, Yi Chang, Ivor W. Tsang

IEEE Trans. Knowl. Data Eng., March, 2024

Hyperbolic Uncertainty Aware Semantic Segmentation.

Bi-ke Chen, Wei Peng, Xiaofeng Cao, Juha Röning

IEEE Trans. Intell. Transp. Syst., February, 2024

Breaking the curse of dimensional collapse in graph contrastive learning: A whitening perspective.

Yang Tao, Kai Guo, Yizhen Zheng, Shirui Pan, Xiaofeng Cao, Yi Chang

Inf. Sci., February, 2024

Transductive Reward Inference on Graph.

Bohao Qu, Xiaofeng Cao, Qing Guo, Yi Chang, Ivor W. Tsang, Chengqi Zhang

CoRR, 2024

A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization.

Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang

CoRR, 2024

2023

Data-Efficient Learning via Minimizing Hyperspherical Energy.

Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang

IEEE Trans. Pattern Anal. Mach. Intell., November, 2023

Taming over-smoothing representation on heterophilic graphs.

Kai Guo, Xiaofeng Cao, Zhining Liu, Yi Chang

Inf. Sci., November, 2023

Improving generalization of double low-rank representation using Schatten-<i>p</i> norm.

Jiaoyan Zhao, Yongsheng Liang, Shuangyan Yi, Qiangqiang Shen, Xiaofeng Cao

Pattern Recognit., June, 2023

AdaNS: Adaptive negative sampling for unsupervised graph representation learning.

Yu Wang, Liang Hu, Wanfu Gao, Xiaofeng Cao, Yi Chang

Pattern Recognit., April, 2023

Aggregation Weighting of Federated Learning via Generalization Bound Estimation.

Mingwei Xu, Xiaofeng Cao, Ivor W. Tsang, James T. Kwok

CoRR, 2023

IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks.

Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor W. Tsang, Yang Liu, Qing Guo

CoRR, 2023

Policy Dispersion in Non-Markovian Environment.

Bohao Qu, Xiaofeng Cao, Jielong Yang, Hechang Chen, Yi Chang, Ivor W. Tsang, Yew-Soon Ong

CoRR, 2023

Nonparametric Teaching for Multiple Learners.

Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Nonparametric Iterative Machine Teaching.

Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok

Proceedings of the International Conference on Machine Learning, 2023

Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships.

Yaming Guo, Kai Guo, Xiaofeng Cao, Tieru Wu, Yi Chang

Proceedings of the International Conference on Machine Learning, 2023

2022

Shattering Distribution for Active Learning.

Xiaofeng Cao, Ivor W. Tsang

IEEE Trans. Neural Networks Learn. Syst., 2022

Cold-Start Active Sampling Via γ-Tube.

Xiaofeng Cao, Ivor W. Tsang, Jianliang Xu

IEEE Trans. Cybern., 2022

Distribution Disagreement via Lorentzian Focal Representation.

Xiaofeng Cao, Ivor W. Tsang

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Robust active representation via ℓ2, p-norm constraints.

Jiaoyan Zhao, Shuangyan Yi, Yongsheng Liang, Wei Liu, Xiaofeng Cao

Knowl. Based Syst., 2022

One-shot Machine Teaching: Cost Very Few Examples to Converge Faster.

Chen Zhang, Xiaofeng Cao, Yi Chang, Ivor W. Tsang

CoRR, 2022

A Survey of Learning on Small Data.

Xiaofeng Cao, Weixin Bu, Shengjun Huang, Ying-Peng Tang, Yaming Guo, Yi Chang, Ivor W. Tsang

CoRR, 2022

When an Active Learner Meets a Black-box Teacher.

Xiaofeng Cao, Yaming Guo, Tieru Wu, Ivor W. Tsang

CoRR, 2022

2021

Distribution-based Active Learning

Xiaofeng Cao

PhD thesis, 2021

High-dimensional cluster boundary detection using directed Markov tree.

Xiaofeng Cao

Pattern Anal. Appl., 2021

Distribution Matching for Machine Teaching.

Xiaofeng Cao, Ivor W. Tsang

CoRR, 2021

Bayesian Active Learning by Disagreements: A Geometric Perspective.

Xiaofeng Cao, Ivor W. Tsang

CoRR, 2021

2020

A structured perspective of volumes on active learning.

Xiaofeng Cao

Neurocomputing, 2020

A divide-and-conquer approach to geometric sampling for active learning.

Xiaofeng Cao

Expert Syst. Appl., 2020

2019

Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation.

Xiaofeng Xu, Ivor W. Tsang, Xiaofeng Cao, Ruiheng Zhang, Chuancai Liu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019