Avishek Saha

most citedProtocols for Learning Classifiers on Distributed Data

5 citations · 10 across the 3 of their papers we have counts for

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Showing 2014 · stat.MLShow all

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stat.ML2014★ 3 cited

N $^{3}$ LARS: 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…

N3LARS: Minimum Redundancy Maximum Relevance Feature Selection for Large and High-dimensional Data

N $^{3}$ LARS: Minimum Redundancy Maximum Relevance Feature Selection for Large and High-dimensional Data