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Fengrui Hao

2 accepted papers

2026

FairGSE: Fairness-Aware Graph Neural Network Without High False Positive Rates

AAAI 2026technical

Graph neural networks (GNNs) have emerged as the mainstream paradigm for graph representation learning due to their effective message aggregation. However, this advantage also amplifies biases inherent in graph topology, raising fairness concerns. Existing fairness-aware GNNs provide satisfactory pe

Cited by 0SourcePDFScholar
2025

BID-Net: Balanced Incremental Distillation Network for Fair Dermatological Disease Diagnosis

ICASSP 2025accepted

Given the increasing prevalence of deep learning applications in dermatological disease diagnosis, the pursuit of diagnostic accuracy needs to be accompanied by a focus on decision-making fairness to avoid unfair discrimination against under-represented demographic groups. This requires a tradeoff b…

Cited by 0SourceScholar