16 citations · 51 across the 7 of their papers we have counts for
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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…
cs.LG2016★ 4 cited
Scaling Submodular Maximization via Pruned Submodularity Graphs
Tianyi Zhou, Hua Ouyang, Yi Chang +2
We propose a new random pruning method (called "submodular sparsification (SS)") to reduce the cost of submodular maximization. The pruning is applied via a "submodularity graph" o…