2 papers
stat.ML2026
Selective Inference for Deep Clustering in Latent Spaces
Eina Mizui, Tomohiro Shiraishi, Shunichi Nishino +1
Deep clustering is a powerful approach for discovering meaningful structures in high-dimensional data by learning a low-dimensional latent representation prior to clustering. Despi…
stat.ML2026
Statistical Testing Framework for Clustering Pipelines by Selective Inference
Yugo Miyata, Tomohiro Shiraishi, Shuichi Nishino +1
A data analysis pipeline is a structured sequence of steps that transforms raw data into meaningful insights by integrating multiple analysis algorithms. In many practical applicat…