1 citations · 2 across the 5 of their papers we have counts for
5 papers
GFLC: Graph-based Fairness-aware Label Correction for Fair Classification
Modar Sulaiman, Kallol Roy
Fairness in machine learning (ML) has a critical importance for building trustworthy machine learning system as artificial intelligence (AI) systems increasingly impact various asp…
The Fairness Stitch: Unveiling the Potential of Model Stitching in Neural Network De-Biasing
Modar Sulaiman, Kallol Roy
The pursuit of fairness in machine learning models has emerged as a critical research challenge in different applications ranging from bank loan approval to face detection. Despite…
Fair Classification via Transformer Neural Networks: Case Study of an Educational Domain
Modar Sulaiman, Kallol Roy
Educational technologies nowadays increasingly use data and Machine Learning (ML) models. This gives the students, instructors, and administrators support and insights for the opti…
Pre-Trained Language Transformers are Universal Image Classifiers
Rahul Goel, Modar Sulaiman, Kimia Noorbakhsh +4
Facial images disclose many hidden personal traits such as age, gender, race, health, emotion, and psychology. Understanding these traits will help to classify the people in differ…
Pretrained Language Models are Symbolic Mathematics Solvers too!
Kimia Noorbakhsh, Modar Sulaiman, Mahdi Sharifi +2
Solving symbolic mathematics has always been of in the arena of human ingenuity that needs compositional reasoning and recurrence. However, recent studies have shown that large-sca…