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Found 6 papers, 1 papers with code
Balancing Augmentation with Edge-Utility Filter for Signed GNNs
Secondly, the original signed graph is selectively augmented with the use of (1) an edge perturbation regulator to balance the number of positive and negative edges and to determine the ratio of perturbed edges to original edges and (2) an edge utility filter to remove the negative edges with low utility to make the graph structure more balanced.
GIMIRec: Global Interaction Information Aware Multi-Interest Framework for Sequential Recommendation
Sequential recommendation based on multi-interest framework models the user's recent interaction sequence into multiple different interest vectors, since a single low-dimensional vector cannot fully represent the diversity of user interests.
Self-Supervised Dynamic Graph Representation Learning via Temporal Subgraph Contrast
Specifically, a novel temporal subgraph sampling strategy is firstly proposed, which takes each node of the dynamic graph as the central node and uses both neighborhood structures and edge timestamps to sample the corresponding temporal subgraph.
Pre-Training on Dynamic Graph Neural Networks
This paper proposes a pre-training method on dynamic graph neural networks (PT-DGNN), which uses dynamic attributed graph generation tasks to simultaneously learn the structure, semantics, and evolution features of the graph.
Sequential online prediction in the presence of outliers and change points: an instant temporal structure learning approach
We propose an INstant TEmporal structure Learning (INTEL) algorithm to address this problem.
Maximum Likelihood Estimation based on Random Subspace EDA: Application to Extrasolar Planet Detection
A population based searching method, called estimation of distribution algorithm (EDA), is adopted to explore the model parameter space starting from a batch of random locations.
