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Found 8 papers, 5 papers with code
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms
However, these auditing processes have been criticized for their failure to integrate the knowledge of marginalized communities and consider the power dynamics between auditors and the communities.
Less, but Stronger: On the Value of Strong Heuristics in Semi-supervised Learning for Software Analytics
Standard SSL algorithms use ``weak'' knowledge (i. e. those not based on specific SE knowledge) such as (e. g.) co-train two learners and use good labels from one to train the other.
How to Find Actionable Static Analysis Warnings: A Case Study with FindBugs
Automatically generated static code warnings suffer from a large number of false alarms.
DebtFree: Minimizing Labeling Cost in Self-Admitted Technical Debt Identification using Semi-Supervised Learning
The human experts are then required to read almost a quintuple of the SATD comments which indicates the inefficiency of the tool.
Fair-SSL: Building fair ML Software with less data
Semi-supervised learning is a machine learning technique where, incrementally, labeled data is used to generate pseudo-labels for the rest of the data (and then all that data is used for model training).
FRUGAL: Unlocking SSL for Software Analytics
However, prior work has shown that such requirements can be expensive, taking several weeks to label thousands of commits, and not always available when traversing new research problems and domains.
Identifying Self-Admitted Technical Debts with Jitterbug: A Two-step Approach
Keeping track of and managing the self-admitted technical debts (SATDs) is important to maintaining a healthy software project.
Software Engineering
Is One Hyperparameter Optimizer Enough?
Hyperparameter tuning is the black art of automatically finding a good combination of control parameters for a data miner.
