111 citations · 240 across the 24 of their papers we have counts for
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Prediction Errors for Penalized Regressions based on Generalized Approximate Message Passing
Ayaka Sakata
We discuss the prediction accuracy of assumed statistical models in terms of prediction errors for the generalized linear model and penalized maximum likelihood methods. We derive…
Active pooling design in group testing based on Bayesian posterior prediction
Ayaka Sakata
In identifying infected patients in a population, group testing is an effective method to reduce the number of tests and correct the test errors. In the group testing procedure, te…
Bayesian inference of infected patients in group testing with prevalence estimation
Ayaka Sakata
Group testing is a method of identifying infected patients by performing tests on a pool of specimens collected from patients. For the case in which the test returns a false result…
Cross validation in sparse linear regression with piecewise continuous nonconvex penalties and its acceleration
Tomoyuki Obuchi, Ayaka Sakata
We investigate the signal reconstruction performance of sparse linear regression in the presence of noise when piecewise continuous nonconvex penalties are used. Among such penalti…
Perfect reconstruction of sparse signals with piecewise continuous nonconvex penalties and nonconvexity control
Ayaka Sakata, Tomoyuki Obuchi
We consider compressed sensing formulated as a minimization problem of nonconvex sparse penalties, Smoothly Clipped Absolute deviation (SCAD) and Minimax Concave Penalty (MCP). The…
Estimator of Prediction Error Based on Approximate Message Passing for Penalized Linear Regression
Ayaka Sakata
We propose an estimator of prediction error using an approximate message passing (AMP) algorithm that can be applied to a broad range of sparse penalties. Following Stein's lemma,…