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Found 3 papers, 2 papers with code
SIGformer: Sign-aware Graph Transformer for Recommendation
Integrating both positive and negative feedback to form a signed graph can lead to a more comprehensive understanding of user preferences.
Distributionally Robust Graph-based Recommendation System
DR-GNN addresses two core challenges: 1) To enable DRO to cater to graph data intertwined with GNN, we reinterpret GNN as a graph smoothing regularizer, thereby facilitating the nuanced application of DRO; 2) Given the typically sparse nature of recommendation data, which might impede robust optimization, we introduce slight perturbations in the training distribution to expand its support.
Robust mmWave Beamforming by Self-Supervised Hybrid Deep Learning
Beamforming with large-scale antenna arrays has been widely used in recent years, which is acknowledged as an important part in 5G and incoming 6G.
