3 citations · 11 across the 15 of their papers we have counts for
9 papers · 1 filter
Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression
Yung-Chien Wang, Kuang-Da Wang, Wei-Yao Wang +1
Tabular data serve as a fundamental and ubiquitous representation of structured information in numerous real-world applications, e.g., finance and urban planning. In the realm of t…
EXPRESS: An LLM-Generated Explainable Property Valuation System with Neighbor Imputation
Wei-Wei Du, Yung-Chien Wang, Wen-Chih Peng
The demand for property valuation has attracted significant attention from sellers, buyers, and customers applying for loans. Reviews of existing approaches have revealed shortcomi…
APAR: Modeling Irregular Target Functions in Tabular Regression via Arithmetic-Aware Pre-Training and Adaptive-Regularized Fine-Tuning
Hong-Wei Wu, Wei-Yao Wang, Kuang-Da Wang +1
Tabular data are fundamental in common machine learning applications, ranging from finance to genomics and healthcare. This paper focuses on tabular regression tasks, a field where…
Self-Supervised Learning of Disentangled Representations for Multivariate Time-Series
Ching Chang, Chiao-Tung Chan, Wei-Yao Wang +2
Multivariate time-series data in fields like healthcare and industry are informative but challenging due to high dimensionality and lack of labels. Recent self-supervised learning…
Root Cause Analysis In Microservice Using Neural Granger Causal Discovery
Cheng-Ming Lin, Ching Chang, Wei-Yao Wang +2
In recent years, microservices have gained widespread adoption in IT operations due to their scalability, maintenance, and flexibility. However, it becomes challenging for site rel…
A Survey on Self-Supervised Learning for Non-Sequential Tabular Data
Wei-Yao Wang, Wei-Wei Du, Derek Xu +2
Self-supervised learning (SSL) has been incorporated into many state-of-the-art models in various domains, where SSL defines pretext tasks based on unlabeled datasets to learn cont…
TimeDRL: Disentangled Representation Learning for Multivariate Time-Series
Ching Chang, Chiao-Tung Chan, Wei-Yao Wang +2
Multivariate time-series data in numerous real-world applications (e.g., healthcare and industry) are informative but challenging due to the lack of labels and high dimensionality.…
DoRA: Domain-Based Self-Supervised Learning Framework for Low-Resource Real Estate Appraisal
Wei-Wei Du, Wei-Yao Wang, Wen-Chih Peng
The marketplace system connecting demands and supplies has been explored to develop unbiased decision-making in valuing properties. Real estate appraisal serves as one of the high-…
ShuttleSet: A Human-Annotated Stroke-Level Singles Dataset for Badminton Tactical Analysis
Wei-Yao Wang, Yung-Chang Huang, Tsi-Ui Ik +1
With the recent progress in sports analytics, deep learning approaches have demonstrated the effectiveness of mining insights into players' tactics for improving performance qualit…