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Kohei Hatano

1 accepted papers

2016

Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling

ICML 2016poster

The problem of learning a sparse model is conceptually interpreted as the process of identifying active features/samples and then optimizing the model over them. Recently introduced safe screening allows us to identify a part of non-active features/samples. So far, safe screening has been individual…