Federated Learning (FL) has emerged as a promising approach to enable
co...
Task-conditional architecture offers advantage in parameter efficiency b...
Detection of human body and its parts (e.g., head or hands) has been
int...
The message-passing scheme is the core of graph representation learning....
Data-efficient learning on graphs (GEL) is essential in real-world
appli...
Federated learning (FL) faces three major difficulties: cross-domain,
he...
The normalizing layer has become one of the basic configurations of deep...
The cold-start problem is a long-standing challenge in recommender syste...
Graph Contrastive Learning (GCL) has shown promising performance in grap...
Single image super-resolution(SISR) is an ill-posed problem that aims to...
In collaborative filtering, it is an important way to make full use of s...
Different studies of the embedding space of transformer models suggest t...
Item recommendation based on historical user-item interactions is of vit...
In this paper, we propose a novel model named DemiNet (short for
DEpende...
Sequential recommendation as an emerging topic has attracted increasing
...