4 citations · 27 across the 34 of their papers we have counts for
4 papers · 2 filters
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…