most citedMentorGNN: Deriving Curriculum for Pre-Training GNNs

3 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI20231 cited

Towards Reliable Rare Category Analysis on Graphs via Individual Calibration

Longfeng Wu, Bowen Lei, Dongkuan Xu +1

Rare categories abound in a number of real-world networks and play a pivotal role in a variety of high-stakes applications, including financial fraud detection, network intrusion d…

cs.IR20231 cited

Streaming CTR Prediction: Rethinking Recommendation Task for Real-World Streaming Data

Qi-Wei Wang, Hongyu Lu, Yu Chen +4

The Click-Through Rate (CTR) prediction task is critical in industrial recommender systems, where models are usually deployed on dynamic streaming data in practical applications. S…

cs.LG2023

Preserving Locality in Vision Transformers for Class Incremental Learning

Bowen Zheng, Da-Wei Zhou, Han-Jia Ye +1

Learning new classes without forgetting is crucial for real-world applications for a classification model. Vision Transformers (ViT) recently achieve remarkable performance in Clas…

cs.LG20221 cited

Towards High-Order Complementary Recommendation via Logical Reasoning Network

Longfeng Wu, Yao Zhou, Dawei Zhou

Complementary recommendation gains increasing attention in e-commerce since it expedites the process of finding frequently-bought-with products for users in their shopping journey.…

cs.LG20223 cited

MentorGNN: Deriving Curriculum for Pre-Training GNNs

Dawei Zhou, Lecheng Zheng, Dongqi Fu +2

Graph pre-training strategies have been attracting a surge of attention in the graph mining community, due to their flexibility in parameterizing graph neural networks (GNNs) witho…