Starting with small and simple concepts, and gradually introducing compl...
In the era of big data, the issue of data quality has become increasingl...
High-resolution remote sensing (HRS) semantic segmentation extracts key
...
Deploying models on target domain data subject to distribution shift req...
Recently, the contrastive language-image pre-training, e.g., CLIP, has
d...
With the advent of the big data era, the data quality problem is becomin...
Multi-view unsupervised feature selection (MUFS) has been demonstrated a...
Time-series forecasting plays an important role in many real-world scena...
Urban metro flow prediction is of great value for metro operation schedu...
Multi-view unsupervised feature selection has been proven to be efficien...
Accurate traffic forecasting, the foundation of intelligent transportati...
Time series forecasting is widely used in the fields of equipment life c...
Weather Forecasting is an attractive challengeable task due to its influ...
Much more attention has been paid to unsupervised feature selection nowa...
Fusion technique is a key research topic in multimodal sentiment analysi...
Video-text retrieval plays an essential role in multi-modal research and...
Unsupervised feature selection is an important method to reduce dimensio...
In the federated learning setting, multiple clients jointly train a mode...
Span extraction is an essential problem in machine reading comprehension...
In this paper, we focus on the imbalance issue, which is rarely studied ...
The goal of unconditional text generation is training a model with real
...
Virus transmission from person to person is an emergency event facing th...
In high-dimensional data space, semi-supervised feature learning based o...
We propose UniViLM: a Unified Video and Language pre-training Model for
...
Deep neural networks (DNNs) can fit (or even over-fit) the training data...
Urban spatial-temporal flows prediction is of great importance to traffi...
Collaborative representation is a popular feature learning approach, whi...
This paper focuses on two related subtasks of aspect-based sentiment
ana...
This paper uses the weather forecasting as an application background to
...
Currently there exists a gap between deep learning and the techniques
re...
Air quality forecasting has been regarded as the key problem of air poll...
To obtain suitable feature distribution is a difficult task in machine
l...
Aspect term extraction is one of the important subtasks in aspect-based
...
Traffic flow forecasting has been regarded as a key problem of intellige...
This paper aims to develop a new architecture that can make full use of ...
This paper aims to develop a new and robust approach to feature
represen...
Forecasting the flow of crowds is of great importance to traffic managem...
The rapid growth of emerging information technologies and application
pa...