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Found 5 papers, 3 papers with code
Deep Mutual Learning across Task Towers for Effective Multi-Task Recommender Learning
Recommender systems usually leverage multi-task learning methods to simultaneously optimize several objectives because of the multi-faceted user behavior data.
Improving Item Cold-start Recommendation via Model-agnostic Conditional Variational Autoencoder
This paper attempts to tackle the item cold-start problem by generating enhanced warmed-up ID embeddings for cold items with historical data and limited interaction records.
Fast sensor placement by enlarging principle submatrix for large-scale linear inverse problems
Sensor placement for linear inverse problems is the selection of locations to assign sensors so that the entire physical signal can be well recovered from partial observations.
One-Class Graph Neural Networks for Anomaly Detection in Attributed Networks
Since traditional anomaly detection methods are stable, robust and easy to use, it is vitally important to generalize them to graph data.
adVAE: A self-adversarial variational autoencoder with Gaussian anomaly prior knowledge for anomaly detection
We assume that both the anomalous and the normal prior distribution are Gaussian and have overlaps in the latent space.
