4 citations · 4 across the 5 of their papers we have counts for
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cs.IR2024
Towards Personalized Federated Multi-Scenario Multi-Task Recommendation
Yue Ding, Yanbiao Ji, Xun Cai +7
In modern recommender systems, especially in e-commerce, predicting multiple targets such as click-through rate (CTR) and post-view conversion rate (CTCVR) is common. Multi-task re…
cs.LG2024
DEGNN: Dual Experts Graph Neural Network Handling Both Edge and Node Feature Noise
Tai Hasegawa, Sukwon Yun, Xin Liu +2
Graph Neural Networks (GNNs) have achieved notable success in various applications over graph data. However, recent research has revealed that real-world graphs often contain noise…
cs.LG2024★ 4 cited
Future-Proofing Class-Incremental Learning
Quentin Jodelet, Xin Liu, Yin Jun Phua +1
Exemplar-Free Class Incremental Learning is a highly challenging setting where replay memory is unavailable. Methods relying on frozen feature extractors have drawn attention recen…