349 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Chinese Academy of SciencesCN20 papers
- Shenzhen UniversityCN20 papers
- Texas A&M UniversityUS15 papers
- University of CambridgeGB13 papers
- Zhejiang UniversityCN12 papers
- Beihang UniversityCN11 papers
- Academy of Mathematics and Systems ScienceCN9 papers
- Korea Institute for Advanced StudyKR9 papers
- University of Science and Technology of ChinaCN8 papers
- Beijing Normal UniversityCN7 papers
- Peking UniversityCN7 papers
- Tsinghua UniversityCN7 papers
10 papers · 1 filter
Integrated Multivariate Segmentation Tree for Heterogeneous Credit Data Analysis in Small- and Medium-Sized Enterprises
Lu Han, Xiuying Wang
Traditional decision tree models, which rely exclusively on numerical variables, often face challenges in handling high-dimensional data and are limited in their ability to incorpo…
Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models
Shuchen Meng, Andi Chen, Chihang Wang +5
Accurate exchange rate prediction is fundamental to financial stability and international trade, positioning it as a critical focus in economic and financial research. Traditional…
Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers
Haowei Ni, Shuchen Meng, Xieming Geng +5
Cardiovascular disease (CVD) is a leading cause of death globally, necessitating precise forecasting models for monitoring vital signs like heart rate, blood pressure, and ECG. Tra…
Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks
Pengyong Li, Jun Wang, Ziliang Li +6
Self-supervised learning has gradually emerged as a powerful technique for graph representation learning. However, transferable, generalizable, and robust representation learning o…
Explainable Enterprise Credit Rating via Deep Feature Crossing Network
Weiyu Guo, Zhijiang Yang, Shu Wu +1
Due to the powerful learning ability on high-rank and non-linear features, deep neural networks (DNNs) are being applied to data mining and machine learning in various fields, and…
Input Perturbation: A New Paradigm between Central and Local Differential Privacy
Yilin Kang, Yong Liu, Ben Niu +3
Traditionally, there are two models on differential privacy: the central model and the local model. The central model focuses on the machine learning model and the local model focu…
Discovery of Bias and Strategic Behavior in Crowdsourced Performance Assessment
Yifei Huang, Matt Shum, Xi Wu +1
With the industry trend of shifting from a traditional hierarchical approach to flatter management structure, crowdsourced performance assessment gained mainstream popularity. One…
Learning Backtrackless Aligned-Spatial Graph Convolutional Networks for Graph Classification
Lu Bail, Lixin Cui, Yuhang Jiao +2
In this paper, we develop a novel Backtrackless Aligned-Spatial Graph Convolutional Network (BASGCN) model to learn effective features for graph classification. Our idea is to tran…
Identifying The Most Informative Features Using A Structurally Interacting Elastic Net
Lixin Cui, Lu Bai, Zhihong Zhang +2
Feature selection can efficiently identify the most informative features with respect to the target feature used in training. However, state-of-the-art vector-based methods are una…
Graph Convolutional Neural Networks based on Quantum Vertex Saliency
Lu Bai, Yuhang Jiao, Luca Rossi +3
This paper proposes a new Quantum Spatial Graph Convolutional Neural Network (QSGCNN) model that can directly learn a classification function for graphs of arbitrary sizes. Unlike…