3 papers
cs.LG2025
Feature-aware Modulation for Learning from Temporal Tabular Data
Hao-Run Cai, Han-Jia Ye
While tabular machine learning has achieved remarkable success, temporal distribution shifts pose significant challenges in real-world deployment, as the relationships between feat…
cs.LG2025
Representation Learning for Tabular Data: A Comprehensive Survey
Jun-Peng Jiang, Si-Yang Liu, Hao-Run Cai +2
Tabular data, structured as rows and columns, is among the most prevalent data types in machine learning classification and regression applications. Models for learning from tabula…
cs.LG2025
Understanding the Limits of Deep Tabular Methods with Temporal Shift
Hao-Run Cai, Han-Jia Ye
Deep tabular models have demonstrated remarkable success on i.i.d. data, excelling in a variety of structured data tasks. However, their performance often deteriorates under tempor…