Search Results for author:
Found 5 papers, 4 papers with code
SVD-AE: Simple Autoencoders for Collaborative Filtering
However, existing methods still have room to improve the trade-offs among accuracy, efficiency, and robustness.
Towards Fair Graph Anomaly Detection: Problem, New Datasets, and Evaluation
The Fair Graph Anomaly Detection (FairGAD) problem aims to accurately detect anomalous nodes in an input graph while ensuring fairness and avoiding biased predictions against individuals from sensitive subgroups such as gender or political leanings.
Trustworthiness-Driven Graph Convolutional Networks for Signed Network Embedding
The proposed approach consists of three modules: (M1) generation of each node's extended ego-network; (M2) measurement of trustworthiness on edge signs; and (M3) trustworthiness-aware propagation of embeddings.
A Survey of Graph Neural Networks for Social Recommender Systems
Social recommender systems (SocialRS) simultaneously leverage the user-to-item interactions as well as the user-to-user social relations for the task of generating item recommendations to users.
Linear, or Non-Linear, That is the Question!
To our knowledge, we are the first who design a hybrid method and report the correlation between the graph centrality and the linearity/non-linearity of nodes.
