450 citations · 1.2k across the 59 of their papers we have counts for
3 papers · 2 filters
Post Selection Inference with Kernels
Makoto Yamada, Yuta Umezu, Kenji Fukumizu +1
We propose a novel kernel based post selection inference (PSI) algorithm, which can not only handle non-linearity in data but also structured output such as multi-dimensional and m…
Ultra High-Dimensional Nonlinear Feature Selection for Big Biological Data
Makoto Yamada, Jiliang Tang, Jose Lugo-Martinez +10
Machine learning methods are used to discover complex nonlinear relationships in biological and medical data. However, sophisticated learning models are computationally unfeasible…
Localized Lasso for High-Dimensional Regression
Makoto Yamada, Koh Takeuchi, Tomoharu Iwata +2
We introduce the localized Lasso, which is suited for learning models that are both interpretable and have a high predictive power in problems with high dimensionality and smal…