Ming Wu

Orcid: 0000-0003-4556-1437

Affiliations:
  • Nanjing University of Science and Technology, School of Computer Science and Engineering, China


According to our database1, Ming Wu authored at least 15 papers between 2017 and 2024.

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

Timeline

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Bibliography

2024
A Little Truth Injection But a Big Reward: Label Aggregation With Graph Neural Networks.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2024

Active Crowdsourcing for Multilabel Annotation.
IEEE Trans. Neural Networks Learn. Syst., March, 2024

Label noise correction for crowdsourcing using dynamic resampling.
Eng. Appl. Artif. Intell., 2024

2023
Learning from biased crowdsourced labeling with deep clustering.
Expert Syst. Appl., 2023

2022
Label Aggregation with Clustering for Biased Crowdsourced Labeling.
Proceedings of the ICMLC 2022: 14th International Conference on Machine Learning and Computing, Guangzhou, China, February 18, 2022

Learning from Crowds with Mutual Correction-Based Co-Training.
Proceedings of the IEEE International Conference on Knowledge Graph, 2022

2021
Privacy preserving techniques for decision trees.
Int. J. Inf. Comput. Secur., 2021

Multi-label active learning from crowds for secure IIoT.
Ad Hoc Networks, 2021

2020
Learning deep networks with crowdsourcing for relevance evaluation.
EURASIP J. Wirel. Commun. Netw., 2020

2019
Ensemble Learning from Crowds.
IEEE Trans. Knowl. Data Eng., 2019

A Survey of Genetic Programming and Its Applications.
KSII Trans. Internet Inf. Syst., 2019

Safety Risk Monitoring of Cyber-Physical Power Systems Based on Ensemble Learning Algorithm.
IEEE Access, 2019

A Subjectivity-Aware Algorithm for Label Aggregation in Crowdsourcing.
Proceedings of the 2019 IEEE International Conference on Computational Science and Engineering, 2019

2017
A robust inference algorithm for crowd sourced categorization.
Proceedings of the 12th International Conference on Intelligent Systems and Knowledge Engineering, 2017

SimWalk: Learning network latent representations with social relation similarity.
Proceedings of the 12th International Conference on Intelligent Systems and Knowledge Engineering, 2017


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