Wei Fu

Affiliations:
  • North Carolina State University, Department of Computer Science, Raleigh, NC, USA


According to our database1, Wei Fu authored at least 15 papers between 2016 and 2022.

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

Timeline

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Links

On csauthors.net:

Bibliography

2022
Predicting health indicators for open source projects (using hyperparameter optimization).
Empir. Softw. Eng., 2022

2021
How to "DODGE" Complex Software Analytics.
IEEE Trans. Software Eng., 2021

2020
Predicting Project Health for Open Source Projects (using the DECART Hyperparameter Optimizer).
CoRR, 2020

2018
Heterogeneous Defect Prediction.
IEEE Trans. Software Eng., 2018

What is wrong with topic modeling? And how to fix it using search-based software engineering.
Inf. Softw. Technol., 2018

Building Better Quality Predictors Using "ε-Dominance".
CoRR, 2018

Applications of psychological science for actionable analytics.
Proceedings of the 2018 ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2018

Data-driven search-based software engineering.
Proceedings of the 15th International Conference on Mining Software Repositories, 2018

500+ times faster than deep learning: a case study exploring faster methods for text mining stackoverflow.
Proceedings of the 15th International Conference on Mining Software Repositories, 2018

2017
Revisiting unsupervised learning for defect prediction.
Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, 2017

Easy over hard: a case study on deep learning.
Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, 2017

2016
Tuning for software analytics: Is it really necessary?
Inf. Softw. Technol., 2016

Why is Differential Evolution Better than Grid Search for Tuning Defect Predictors?
CoRR, 2016

What is Wrong with Topic Modeling? (and How to Fix it Using Search-based SE).
CoRR, 2016

Too much automation? the bellwether effect and its implications for transfer learning.
Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering, 2016


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