As Graph Neural Networks (GNNs) have been widely used in real-world
appl...
Large Language Models (LLMs), armed with billions of parameters, exhibit...
Sharding a large machine learning model across multiple devices to balan...
Recently, there has been a growing demand for the deployment of Explaina...
Flow-level network measurement is critical to many network applications....
The training of graph neural networks (GNNs) is extremely time consuming...
Large-scale graph training is a notoriously challenging problem for grap...
Graph neural networks (GNNs), which learn the node representations by
re...
Human-designed data augmentation strategies have been replaced by
automa...
Detecting statistical interactions between input features is a crucial a...
Realistic recommender systems are often required to adapt to ever-changi...
Image captioning has made substantial progress with huge supporting imag...