769 citations · 1k across the 13 of their papers we have counts for
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Situating Recommender Systems in Practice: Towards Inductive Learning and Incremental Updates
Tobias Schnabel, Mengting Wan, Longqi Yang
With information systems becoming larger scale, recommendation systems are a topic of growing interest in machine learning research and industry. Even though progress on improving…
Learning Causal Effects on Hypergraphs
Jing Ma, Mengting Wan, Longqi Yang +3
Hypergraphs provide an effective abstraction for modeling multi-way group interactions among nodes, where each hyperedge can connect any number of nodes. Different from most existi…
Lightweight Compositional Embeddings for Incremental Streaming Recommendation
Mengyue Hang, Tobias Schnabel, Longqi Yang +1
Most work in graph-based recommender systems considers a {\em static} setting where all information about test nodes (i.e., users and items) is available upfront at training time.…
Learning Fair Node Representations with Graph Counterfactual Fairness
Jing Ma, Ruocheng Guo, Mengting Wan +3
Fair machine learning aims to mitigate the biases of model predictions against certain subpopulations regarding sensitive attributes such as race and gender. Among the many existin…