97 citations · 379 across the 26 of their papers we have counts for
7 papers · 1 filter
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…
Manas: Mining Software Repositories to Assist AutoML
Giang Nguyen, Md Johir Islam, Rangeet Pan +1
Today deep learning is widely used for building software. A software engineering problem with deep learning is that finding an appropriate convolutional neural network (CNN) model…
The Art and Practice of Data Science Pipelines: A Comprehensive Study of Data Science Pipelines In Theory, In-The-Small, and In-The-Large
Sumon Biswas, Mohammad Wardat, Hridesh Rajan
Increasingly larger number of software systems today are including data science components for descriptive, predictive, and prescriptive analytics. The collection of data science s…
Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules
Rangeet Pan, Hridesh Rajan
Training from scratch is the most common way to build a Convolutional Neural Network (CNN) based model. What if we can build new CNN models by reusing parts from previously build C…
A global convergence theory for deep ReLU implicit networks via over-parameterization
Tianxiang Gao, Hailiang Liu, Jia Liu +2
Implicit deep learning has received increasing attention recently due to the fact that it generalizes the recursive prediction rules of many commonly used neural network architectu…
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…