2 papers
stat.ML2026
Relaxed Sparsest-Permutation Formulation for Causal Discovery at Scale
Sunmin Oh, Sang-Yun Oh, Gunwoong Park
Despite the growing availability of large datasets, causal structure learning remains computationally prohibitive at scale. We revisit sparsest-permutation learning for linear stru…
stat.ML2025
Learning Massive-scale Partial Correlation Networks in Clinical Multi-omics Studies with HP-ACCORD
Sungdong Lee, Joshua Bang, Youngrae Kim +3
Graphical model estimation from multi-omics data requires a balance between statistical estimation performance and computational scalability. We introduce a novel pseudolikelihood-…