Cheng‐Wei Hung

Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search

2024 · arXiv (Cornell University)

Programmatic reinforcement learning (PRL) has been explored for representing policies through programs as a means to achieve interpretability and generalization. Despite promising outcomes, current state-of-the-art PRL methods are hindered by sample inefficiency, necessitating tens of …

FADEL: Ensemble Learning Enhanced by Feature Augmentation and Discretization

2025 · Bioengineering

In recent years, data augmentation techniques have become the predominant approach for addressing highly imbalanced classification problems in machine learning. Algorithms such as the Synthetic Minority Over-sampling Technique (SMOTE) and Conditional Tabular Generative Adversarial Network …