Inwon Kang

Adaptive Ensemble Selection for Noisy Labels on Tabular Data

Incorrect or corrupted labels in tabular datasets can significantly degrade supervised learning performance, particularly when mislabeling is subtle and not easily detectable from feature space alone. In the context of automated or AI-augmented data science workflows, robust detection of such label noise is critical fo...

Towards Budget-Aware Dense Retrieval for Tables: Trade-offs, Alternatives and Future Directions

PFN-Syn: Generating Synthetic Tabular Data with Prior-Data Fitted Networks

PFN-Syn achieves the highest average downstream utility among evaluated synthetic generators, with higher generation throughput than training-based baselines, while maintaining competitive distributional similarity and distance-to-closest-record privacy behavior.