97 citations · 220 across the 10 of their papers we have counts for
12 papers
An Empirical Study on the Bugs Found while Reusing Pre-trained Natural Language Processing Models
Rangeet Pan, Sumon Biswas, Mohna Chakraborty +2
In NLP, reusing pre-trained models instead of training from scratch has gained popularity; however, NLP models are mostly black boxes, very large, and often require significant res…
GADGET: Online Resource Optimization for Scheduling Ring-All-Reduce Learning Jobs
Menglu Yu, Ye Tian, Bo Ji +3
Fueled by advances in distributed deep learning (DDL), recent years have witnessed a rapidly growing demand for resource-intensive distributed/parallel computing to process DDL com…
Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline
Sumon Biswas, Hridesh Rajan
In recent years, many incidents have been reported where machine learning models exhibited discrimination among people based on race, sex, age, etc. Research has been conducted to…
DeepLocalize: Fault Localization for Deep Neural Networks
Mohammad Wardat, Wei Le, Hridesh Rajan
Deep neural networks (DNNs) are becoming an integral part of most software systems. Previous work has shown that DNNs have bugs. Unfortunately, existing debugging techniques do not…
BCFA: Bespoke Control Flow Analysis for CFA at Scale
Ramanathan Ramu, Ganesha B Upadhyaya, Hoan Anh Nguyen +1
Many data-driven software engineering tasks such as discovering programming patterns, mining API specifications, etc., perform source code analysis over control flow graphs (CFGs)…
Repairing Deep Neural Networks: Fix Patterns and Challenges
Md Johirul Islam, Rangeet Pan, Giang Nguyen +1
Significant interest in applying Deep Neural Network (DNN) has fueled the need to support engineering of software that uses DNNs. Repairing software that uses DNNs is one such unmi…