most citedUltra High-Dimensional Nonlinear Feature Selection for Big Biological Data

9 citations · 14 across the 4 of their papers we have counts for

collaborators
Showing 2014Show all

2 papers · 1 filter

stat.ML2014★ 2 cited

Consistent Collective Matrix Completion under Joint Low Rank Structure

Suriya Gunasekar, Makoto Yamada, Dawei Yin +1

We address the collective matrix completion problem of jointly recovering a collection of matrices with shared structure from partial (and potentially noisy) observations. To ensur…

stat.ML2014★ 3 cited

NLARS: Minimum Redundancy Maximum Relevance Feature Selection for Large and High-dimensional Data

Makoto Yamada, Avishek Saha, Hua Ouyang +2

We propose a feature selection method that finds non-redundant features from a large and high-dimensional data in nonlinear way. Specifically, we propose a nonlinear extension of t…