6 citations · 7 across the 5 of their papers we have counts for
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stat.ML2015★ 1 cited
Safe Feature Pruning for Sparse High-Order Interaction Models
Kazuya Nakagawa, Shinya Suzumura, Masayuki Karasuyama +2
Taking into account high-order interactions among covariates is valuable in many practical regression problems. This is, however, computationally challenging task because the numbe…
stat.ML2015
An Efficient Post-Selection Inference on High-Order Interaction Models
S. Suzumura, K. Nakagawa, K. Tsuda +1
Finding statistically significant high-order interaction features in predictive modeling is important but challenging task. The difficulty lies in the fact that, for a recent appli…