An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems

Research output: Journal article publication › Journal article › Academic research › peer-review

3 Citations (Scopus)

Original language	English
Pages (from-to)	524-543
Number of pages	20
Journal	SIAM Journal on Mathematics of Data Science
Volume	3
Issue number	2
DOIs	https://doi.org/10.1137/20M1344160
Publication status	E-pub ahead of print - 21 Apr 2021

More information

@article{40a61b99994b43298be460c7b07d0338,

title = "An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems",

author = "Ning Zhang and Yangjing Zhang and Defeng Sun and Kim-Chuan Toh",

year = "2021",

month = apr,

day = "21",

doi = "10.1137/20M1344160",

language = "English",

volume = "3",

pages = "524--543",

journal = "SIAM Journal on Mathematics of Data Science",

number = "2",

}

TY - JOUR

T1 - An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems

AU - Zhang, Ning

AU - Zhang, Yangjing

AU - Sun, Defeng

AU - Toh, Kim-Chuan

PY - 2021/4/21

Y1 - 2021/4/21

UR - https://epubs.siam.org/doi/abs/10.1137/20M1344160?mobileUi=0

U2 - 10.1137/20M1344160

DO - 10.1137/20M1344160

M3 - Journal article

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SP - 524

EP - 543

JO - SIAM Journal on Mathematics of Data Science

JF - SIAM Journal on Mathematics of Data Science

IS - 2

ER -