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Due to the demand for tackling the problem of streaming data with high-dimensional covarites, we propose an online sparse sliced inverse regression (OSSIR) ...
Sep 30, 2020 · We propose an online sparse sliced inverse regression (OSSIR) method for online sufficient dimension reduction.
Jul 5, 2021 · Due to the demand for tackling the problem of streaming data with high dimensional covarites, we propose an online sparse sliced inverse ...
Dec 13, 2022 · In this paper, we adapt the sparse sliced inverse regression to cope with high-dimensional streaming data where the dimen- sion p is large.
Due to the demand for tackling the problem of streaming data with high-dimensional covarites, we propose an online sparse sliced inverse regression (OSSIR) ...
May 7, 2022 · In this article, we propose dimension reduction and variable selection for semi-parametric models in the high-dimensional setting.
Sep 6, 2024 · Sliced inverse regression is an efficient approach to estimate the central subspace for sufficient dimension reduction.
Sliced inverse regression is an effective paradigm that achieves the goal of dimension re- duction through replacing high dimensional covariates with a small ...
Aug 22, 2024 · Sliced inverse regression (SIR) is a highly efficient paradigm used for the purpose of dimension reduction by replacing high-dimensional ...
May 7, 2022 · The sliced inverse regression (SIR) method, which can be formulated as a generalized eigenvalue decomposition problem, offers a model-free estimation approach.
Missing: Online streaming