64 citations · 252 across the 64 of their papers we have counts for
3 papers · 2 filters
TabuLa: Harnessing Language Models for Tabular Data Synthesis
Zilong Zhao, Robert Birke, Lydia Chen
Tabular data synthesis is crucial for addressing privacy and security concerns in industries reliant on tabular data. While recent advancements adopt large language models (LLMs) f…
BatMan-CLR: Making Few-shots Meta-Learners Resilient Against Label Noise
Jeroen M. Galjaard, Robert Birke, Juan Perez +1
The negative impact of label noise is well studied in classical supervised learning yet remains an open research question in meta-learning. Meta-learners aim to adapt to unseen lea…
VT-GAN: Cooperative Tabular Data Synthesis using Vertical Federated Learning
Zilong Zhao, Han Wu, Aad Van Moorsel +1
This paper presents the application of Vertical Federated Learning (VFL) to generate synthetic tabular data using Generative Adversarial Networks (GANs). VFL is a collaborative app…