Multi-Target Cross Domain Recommendation(CDR) has attracted a surge of
i...
Graph neural networks (GNNs) have shown remarkable performance on homoph...
In recent years, semi-supervised graph learning with data augmentation (...
Risk prediction, as a typical time series modeling problem, is usually
a...
The concept of causality plays an important role in human cognition . In...
Treatment effect estimation, which refers to the estimation of causal ef...
A real-world graph has a complex topology structure, which is often form...
Human identification is an important topic in event detection, person
tr...
In zero-shot learning (ZSL), the samples to be classified are usually
pr...
Due to the deteriorated conditions of lack and uneven
lighting, nightti...
Graph representation learning aims to encode all nodes of a graph into
l...
Given a set of hand-crafted local features, acquiring a global represent...
Zero-shot learning (ZSL) has received extensive attention recently espec...
Zero-Shot Learning (ZSL) has received extensive attention and successes ...
Zero-shot learning (ZSL) has received increasing attention in recent yea...
Non-uniform blur, mainly caused by camera shake and motions of multiple
...
Time series prediction with deep learning methods, especially long short...
Convolutional neural network (CNN) features which represent images with
...
In this paper, we investigate the cross-media retrieval between images a...
Independent Component Analysis (ICA) is an effective unsupervised tool t...