1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
Fairness-Aware Interpretable Modeling (FAIM) for Trustworthy Machine Learning in Healthcare
Mingxuan Liu, Yilin Ning, Yuhe Ke +5
The escalating integration of machine learning in high-stakes fields such as healthcare raises substantial concerns about model fairness. We propose an interpretable framework - Fa…
cs.CV2024★ 1 cited
Democratizing Fine-grained Visual Recognition with Large Language Models
Mingxuan Liu, Subhankar Roy, Wenjing Li +3
Identifying subordinate-level categories from images is a longstanding task in computer vision and is referred to as fine-grained visual recognition (FGVR). It has tremendous signi…
cs.CV2022
Class-incremental Novel Class Discovery
Subhankar Roy, Mingxuan Liu, Zhun Zhong +2
We study the new task of class-incremental Novel Class Discovery (class-iNCD), which refers to the problem of discovering novel categories in an unlabelled data set by leveraging a…