1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.LG2024
Correlation-Aware Graph Convolutional Networks for Multi-Label Node Classification
Yuanchen Bei, Weizhi Chen, Hao Chen +5
Multi-label node classification is an important yet under-explored domain in graph mining as many real-world nodes belong to multiple categories rather than just a single one. Alth…
cs.LG2024
Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation
Baoyu Jing, Dawei Zhou, Kan Ren +1
Spatiotemporal time series are usually collected via monitoring sensors placed at different locations, which usually contain missing values due to various failures, such as mechani…
cs.LG2024★ 1 cited
Contrastive Unlearning: A Contrastive Approach to Machine Unlearning
Hong kyu Lee, Qiuchen Zhang, Carl Yang +2
Machine unlearning aims to eliminate the influence of a subset of training samples (i.e., unlearning samples) from a trained model. Effectively and efficiently removing the unlearn…