67 citations · 164 across the 11 of their papers we have counts for
10 papers · 1 filter
A Pre-trained Data Deduplication Model based on Active Learning
Haochen Shi, Xinyao Liu, Fengmao Lv +4
In the era of big data, the issue of data quality has become increasingly prominent. One of the main challenges is the problem of duplicate data, which can arise from repeated entr…
A Missing Value Filling Model Based on Feature Fusion Enhanced Autoencoder
Xinyao Liu, Shengdong Du, Tianrui Li +2
With the advent of the big data era, the data quality problem is becoming more critical. Among many factors, data with missing values is one primary issue, and thus developing effe…
DRAformer: Differentially Reconstructed Attention Transformer for Time-Series Forecasting
Benhan Li, Shengdong Du, Tianrui Li +2
Time-series forecasting plays an important role in many real-world scenarios, such as equipment life cycle forecasting, weather forecasting, and traffic flow forecasting. It can be…
Spatio-Temporal Dynamic Graph Relation Learning for Urban Metro Flow Prediction
Peng Xie, Minbo Ma, Tianrui Li +4
Urban metro flow prediction is of great value for metro operation scheduling, passenger flow management and personal travel planning. However, it faces two main challenges. First,…
A Differential Attention Fusion Model Based on Transformer for Time Series Forecasting
Benhan Li, Shengdong Du, Tianrui Li
Time series forecasting is widely used in the fields of equipment life cycle forecasting, weather forecasting, traffic flow forecasting, and other fields. Recently, some scholars h…
Spatio-Temporal Latent Graph Structure Learning for Traffic Forecasting
Jiabin Tang, Tang Qian, Shijing Liu +3
Accurate traffic forecasting, the foundation of intelligent transportation systems (ITS), has never been more significant than nowadays due to the prosperity of smart cities and ur…
Fairness and Accuracy in Federated Learning
Wei Huang, Tianrui Li, Dexian Wang +2
In the federated learning setting, multiple clients jointly train a model under the coordination of the central server, while the training data is kept on the client to ensure priv…
Urban flows prediction from spatial-temporal data using machine learning: A survey
Peng Xie, Tianrui Li, Jia Liu +3
Urban spatial-temporal flows prediction is of great importance to traffic management, land use, public safety, etc. Urban flows are affected by several complex and dynamic factors,…
Deep Air Quality Forecasting Using Hybrid Deep Learning Framework
Shengdong Du, Tianrui Li, Yan Yang +1
Air quality forecasting has been regarded as the key problem of air pollution early warning and control management. In this paper, we propose a novel deep learning model for air qu…
A Hybrid Method for Traffic Flow Forecasting Using Multimodal Deep Learning
Shengdong Du, Tianrui Li, Xun Gong +1
Traffic flow forecasting has been regarded as a key problem of intelligent transport systems. In this work, we propose a hybrid multimodal deep learning method for short-term traff…