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20212025
most citedKeeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting

91 citations · 223 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2025★ 1 cited

MetaSel: A Test Selection Approach for Fine-tuned DNN Models

Amin Abbasishahkoo, Mahboubeh Dadkhah, Lionel Briand +1

Deep Neural Networks (DNNs) face challenges during deployment due to covariate shift, i.e., data distribution shifts between development and deployment contexts. Fine-tuning adapts…

cs.SE2024★ 91 cited

Keeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting

Hao Li, Gopi Krishnan Rajbahadur, Dayi Lin +3

In software engineering, deep learning models are increasingly deployed for critical tasks such as bug detection and code review. However, overfitting remains a challenge that affe…

cs.SE2023★ 4 cited

TEASMA: A Practical Methodology for Test Adequacy Assessment of Deep Neural Networks

Amin Abbasishahkoo, Mahboubeh Dadkhah, Lionel Briand +1

Successful deployment of Deep Neural Networks (DNNs) requires their validation with an adequate test set to ensure a sufficient degree of confidence in test outcomes. Although well…

cs.GT2022

An Empirical Study of Delayed Games on Steam

Balreet Grewal, Dayi Lin, Lars Doucet +1

The gaming industry is rapidly expanding. With over 2.7 billion players worldwide, game development has become increasingly challenging. To meet the ever-changing demands and expec…

cs.LG2022★ 47 cited

Towards Training Reproducible Deep Learning Models

Boyuan Chen, Mingzhi Wen, Yong Shi +4

Reproducibility is an increasing concern in Artificial Intelligence (AI), particularly in the area of Deep Learning (DL). Being able to reproduce DL models is crucial for AI-based…

cs.LG2022★ 29 cited

Towards a consistent interpretation of AIOps models

Yingzhe Lyu, Gopi Krishnan Rajbahadur, Dayi Lin +3

Artificial Intelligence for IT Operations (AIOps) has been adopted in organizations in various tasks, including interpreting models to identify indicators of service failures. To a…

cs.SE2021★ 24 cited

An Empirical Study of the Characteristics of Popular Minecraft Mods

Daniel Lee, Gopi Krishnan Rajbahadur, Dayi Lin +3

It is becoming increasingly difficult for game developers to manage the cost of developing a game, while meeting the high expectations of gamers. One way to balance the increasing…

cs.SE2021★ 27 cited

Building the perfect game -- an empirical study of game modifications

Daniel Lee, Dayi Lin, Cor-Paul Bezemer +1

Game developers cannot always meet the growing and changing needs of the gaming community, due to the often already overloaded schedules of developers. So-called modders can potent…