이남길

전체 50건 중 41번부터 50번까지의 결과를 표시합니다.

2018

Conference

Shrinkage estimation and model selection for vector autoregressive models with an application to fMRI data analysis

Conference

Tensor networks for dimensionality reduction and large-scale optimizations

2017

Conference

Robust Multilinear Rank Estimation for Multiway Data Analysis

Article

Robust Multilinear Tensor Rank Estimation Using Higher Order Singular Value Decomposition and Information Criteria

Article

Tensor networks for dimensionality reduction and large-scale optimizations: Part 2 applications and future perspectives

2016

Article

Bayes shrinkage estimation for high-dimensional VAR models with scale mixture of normal distributions for noise

Article

An improvement on local FDR analysis applied to functional MRI data

Article

Tensor networks for dimensionality reduction and large-scale optimization part 1 low-rank tensor decompositions

Article

REGULARIZED COMPUTATION OF APPROXIMATE PSEUDOINVERSE OF LARGE MATRICES USING LOW-RANK TENSOR TRAIN DECOMPOSITIONS

2015

Article

ESTIMATING A FEW EXTREME SINGULAR VALUES AND VECTORS FOR LARGE-SCALE MATRICES IN TENSOR TRAIN FORMAT

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이남길

연구분야

자료유형

발행연도

키워드

언어

Shrinkage estimation and model selection for vector autoregressive models with an application to fMRI data analysis

Tensor networks for dimensionality reduction and large-scale optimizations

Robust Multilinear Rank Estimation for Multiway Data Analysis

Robust Multilinear Tensor Rank Estimation Using Higher Order Singular Value Decomposition and Information Criteria

Tensor networks for dimensionality reduction and large-scale optimizations: Part 2 applications and future perspectives

Bayes shrinkage estimation for high-dimensional VAR models with scale mixture of normal distributions for noise

An improvement on local FDR analysis applied to functional MRI data

Tensor networks for dimensionality reduction and large-scale optimization part 1 low-rank tensor decompositions

REGULARIZED COMPUTATION OF APPROXIMATE PSEUDOINVERSE OF LARGE MATRICES USING LOW-RANK TENSOR TRAIN DECOMPOSITIONS

ESTIMATING A FEW EXTREME SINGULAR VALUES AND VECTORS FOR LARGE-SCALE MATRICES IN TENSOR TRAIN FORMAT