7 citations · 15 across the 5 of their papers we have counts for
3 papers · 1 filter
Automatically Detecting Numerical Instability in Machine Learning Applications via Soft Assertions
Shaila Sharmin, Anwar Hossain Zahid, Subhankar Bhattacharjee +3
Machine learning (ML) applications have become an integral part of our lives. ML applications extensively use floating-point computation and involve very large/small numbers; thus,…
An Effective Data-Driven Approach for Localizing Deep Learning Faults
Mohammad Wardat, Breno Dantas Cruz, Wei Le +1
Deep Learning (DL) applications are being used to solve problems in critical domains (e.g., autonomous driving or medical diagnosis systems). Thus, developers need to debug their s…
DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning Programs
Mohammad Wardat, Breno Dantas Cruz, Wei Le +1
Deep Neural Networks (DNNs) are used in a wide variety of applications. However, as in any software application, DNN-based apps are afflicted with bugs. Previous work observed that…