9 citations · 9 across the 2 of their papers we have counts for
2 papers
stat.ML2016★ 9 cited
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…
stat.ML2014
Sparse Learning over Infinite Subgraph Features
Ichigaku Takigawa, Hiroshi Mamitsuka
We present a supervised-learning algorithm from graph data (a set of graphs) for arbitrary twice-differentiable loss functions and sparse linear models over all possible subgraph f…