55 citations · 64 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 9 cited
Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization
Jonathan Wilton, Abigail M. Y. Koay, Ryan K. L. Ko +2
The need to learn from positive and unlabeled data, or PU learning, arises in many applications and has attracted increasing interest. While random forests are known to perform wel…
cs.LG2020★ 55 cited
Embedding Java Classes with code2vec: Improvements from Variable Obfuscation
Rhys Compton, Eibe Frank, Panos Patros +1
Automatic source code analysis in key areas of software engineering, such as code security, can benefit from Machine Learning (ML). However, many standard ML approaches require a n…