1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2023
FAIRLABEL: Correcting Bias in Labels
Srinivasan H Sengamedu, Hien Pham
There are several algorithms for measuring fairness of ML models. A fundamental assumption in these approaches is that the ground truth is fair or unbiased. In real-world datasets,…
cs.SE2022★ 1 cited
Example-based Synthesis of Static Analysis Rules
Pranav Garg, Srinivasan Sengamedu SHS
Static Analysis tools have rules for several code quality issues and these rules are created by experts manually. In this paper, we address the problem of automatic synthesis of co…
cs.LG2021
Universal Representation for Code
Linfeng Liu, Hoan Nguyen, George Karypis +1
Learning from source code usually requires a large amount of labeled data. Despite the possible scarcity of labeled data, the trained model is highly task-specific and lacks transf…