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07/15/2023
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms
Bias evaluation benchmarks and dataset and model documentation have emer...
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02/03/2023
Less, but Stronger: On the Value of Strong Heuristics in Semi-supervised Learning for Software Analytics
In many domains, there are many examples and far fewer labels for those ...
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05/21/2022
How to Find Actionable Static Analysis Warnings
Automatically generated static code warnings suffer from a large number ...
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05/02/2022
Reducing the Cost of Training Security Classifier (via Optimized Semi-Supervised Learning)
Background: Most of the existing machine learning models for security ta...
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01/25/2022
DebtFree: Minimizing Labeling Cost in Self-Admitted Technical Debt Identification using Semi-Supervised Learning
Keeping track of and managing Self-Admitted Technical Debts (SATDs) is i...
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11/03/2021
Can We Achieve Fairness Using Semi-Supervised Learning?
Ethical bias in machine learning models has become a matter of concern i...
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08/22/2021
FRUGAL: Unlocking SSL for Software Analytics
Standard software analytics often involves having a large amount of data...
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03/22/2021
Mining Scientific Workflows for Anomalous Data Transfers
Modern scientific workflows are data-driven and are often executed on di...
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03/12/2020
The Changing Nature of Computational Science Software
How should software engineering be adapted for Computational Science (CS...
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02/25/2020
Identifying Self-Admitted Technical Debts with Jitterbug: A Two-step Approach
Keeping track of and managing the self-admitted technical debts (SATDs) ...
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05/05/2019
Enhanced Labeling of Issue Reports (with F^3T)
Standard automatic methods for recognizing problematic code can be great...
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07/29/2018
Is One Hyperparameter Optimizer Enough?
Hyperparameter tuning is the black art of automatically finding a good c...
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07/29/2018
While Tuning is Good, No Tuner is Best
Hyperparameter tuning is the black art of automatically finding a good c...
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04/27/2018
