Search Results for author:
Found 4 papers, 2 papers with code
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems
Most subsampling methods are model-based and often require a pre-trained pilot model to measure data importance via e. g. sample hardness.
Label Inference Attack against Split Learning under Regression Setting
In this work, we step further to study the leakage in the scenario of the regression model, where the private labels are continuous numbers (instead of discrete labels in classification).
DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation
Graph Neural Network (GNN) based recommender systems have been attracting more and more attention in recent years due to their excellent performance in accuracy.
Person Re-Identification by Discriminative Selection in Video Ranking
Current person re-identification (ReID) methods typically rely on single-frame imagery features, whilst ignoring space-time information from image sequences often available in the practical surveillance scenarios.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
