18 citations · 34 across the 10 of their papers we have counts for
10 papers
Marginal Nodes Matter: Towards Structure Fairness in Graphs
Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang +3
In social network, a person located at the periphery region (marginal node) is likely to be treated unfairly when compared with the persons at the center. While existing fairness w…
CODA: Temporal Domain Generalization via Concept Drift Simulator
Chia-Yuan Chang, Yu-Neng Chuang, Zhimeng Jiang +3
In real-world applications, machine learning models often become obsolete due to shifts in the joint distribution arising from underlying temporal trends, a phenomenon known as the…
Beyond Fairness: Age-Harmless Parkinson's Detection via Voice
Yicheng Wang, Xiaotian Han, Leisheng Yu +1
Parkinson's disease (PD), a neurodegenerative disorder, often manifests as speech and voice dysfunction. While utilizing voice data for PD detection has great potential in clinical…
DISPEL: Domain Generalization via Domain-Specific Liberating
Chia-Yuan Chang, Yu-Neng Chuang, Guanchu Wang +2
Domain generalization aims to learn a generalization model that can perform well on unseen test domains by only training on limited source domains. However, existing domain general…
Graph Mixup with Soft Alignments
Hongyi Ling, Zhimeng Jiang, Meng Liu +2
We study graph data augmentation by mixup, which has been used successfully on images. A key operation of mixup is to compute a convex combination of a pair of inputs. This operati…
PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data
Shenghan Zhang, Haoxuan Li, Ruixiang Tang +5
Detailed phenotype information is fundamental to accurate diagnosis and risk estimation of diseases. As a rich source of phenotype information, electronic health records (EHRs) pro…