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FuSSO: Functional Shrinkage and Selection Operator

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journal contribution
posted on 01.04.2014, 00:00 by Junier B. Oliva, Barnabas Poczos, Timothy VerstynenTimothy Verstynen, Aarti Singh, Jeff Schneider, Fang-Cheng Yeh, Wen-Yih Isaac Tseng

We present the FuSSO, a functional analogue to the LASSO, that efficiently finds a sparse set of functional input covariates to regress a real-valued response against. The FuSSO does so in a semi-parametric fashion, making no parametric assumptions about the nature of input functional covariates and assuming a linear form to the mapping of functional covariates to the response. We provide a statistical backing for use of the FuSSO via proof of asymptotic sparsistency under various conditions. Furthermore, we observe good results on both synthetic and real-world data.

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Copyright 2014 by the authors.

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01/04/2014

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