14 citations · 74 across the 22 of their papers we have counts for
3 papers · 1 filter
Heterophily-Based Graph Neural Network for Imbalanced Classification
Zirui Liang, Yuntao Li, Tianjin Huang +3
Graph neural networks (GNNs) have shown promise in addressing graph-related problems, including node classification. However, conventional GNNs assume an even distribution of data…
FAL-CUR: Fair Active Learning using Uncertainty and Representativeness on Fair Clustering
Ricky Fajri, Akrati Saxena, Yulong Pei +1
Active Learning (AL) techniques have proven to be highly effective in reducing data labeling costs across a range of machine learning tasks. Nevertheless, one known challenge of th…
Survey on Fair Reinforcement Learning: Theory and Practice
Pratik Gajane, Akrati Saxena, Maryam Tavakol +2
Fairness-aware learning aims at satisfying various fairness constraints in addition to the usual performance criteria via data-driven machine learning techniques. Most of the resea…