Xianjie Guo

Orcid: 0000-0002-0656-2309

According to our database1, Xianjie Guo authored at least 15 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Progressive Skeleton Learning for Effective Local-to-Global Causal Structure Learning.
IEEE Trans. Knowl. Data Eng., December, 2024

Bootstrap-Based Layerwise Refining for Causal Structure Learning.
IEEE Trans. Artif. Intell., June, 2024

Local causal structure learning with missing data.
Expert Syst. Appl., March, 2024

Causal Feature Selection With Dual Correction.
IEEE Trans. Neural Networks Learn. Syst., January, 2024

Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

FedCSL: A Scalable and Accurate Approach to Federated Causal Structure Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Towards Privacy-Aware Causal Structure Learning in Federated Setting.
IEEE Trans. Big Data, December, 2023

A novel data enhancement approach to DAG learning with small data samples.
Appl. Intell., November, 2023

Adaptive Skeleton Construction for Accurate DAG Learning.
IEEE Trans. Knowl. Data Eng., October, 2023

Causal Feature Selection in the Presence of Sample Selection Bias.
ACM Trans. Intell. Syst. Technol., October, 2023

2022
Error-aware Markov blanket learning for causal feature selection.
Inf. Sci., 2022

Bootstrap-based Causal Structure Learning.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Causality-based Feature Selection: Methods and Evaluations.
ACM Comput. Surv., 2021

Improving Gradient-based DAG Learning by Structural Asymmetry.
Proceedings of the 2021 IEEE International Conference on Big Knowledge, 2021

Accelerating Learning Bayesian Network Structures by Reducing Redundant CI Tests.
Proceedings of the 2021 IEEE International Conference on Big Knowledge, 2021


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