1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers
Felix den Breejen, Sangmin Bae, Stephen Cha +1
The recently introduced TabPFN pretrains an In-Context Learning (ICL) transformer on synthetic data to perform tabular data classification. In this work, we extend TabPFN to the fi…
cs.LG2023★ 1 cited
Fine-Tuning the Retrieval Mechanism for Tabular Deep Learning
Felix den Breejen, Sangmin Bae, Stephen Cha +3
While interests in tabular deep learning has significantly grown, conventional tree-based models still outperform deep learning methods. To narrow this performance gap, we explore…
cs.CV2022★ 1 cited
A Survey of Supernet Optimization and its Applications: Spatial and Temporal Optimization for Neural Architecture Search
Stephen Cha, Taehyeon Kim, Hayeon Lee +1
This survey focuses on categorizing and evaluating the methods of supernet optimization in the field of Neural Architecture Search (NAS). Supernet optimization involves training a…