High-dimensional Gaussian graphical models on network-linked data

被引:0
|
作者
Li, Tianxi [1 ]
Qian, Cheng [2 ]
Levina, Elizaveta [3 ]
Zhu, Ji [3 ]
机构
[1] Li, Tianxi
[2] Qian, Cheng
[3] Levina, Elizaveta
[4] Zhu, Ji
来源
| 1600年 / Microtome Publishing卷 / 21期
关键词
80;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [41] High-Dimensional Inference for Cluster-Based Graphical Models
    Eisenach, Carson
    Bunea, Florentina
    Ning, Yang
    Dinicu, Claudiu
    JOURNAL OF MACHINE LEARNING RESEARCH, 2020, 21
  • [42] Constrained Covariance Matrices With a Biologically Realistic Structure: Comparison of Methods for Generating High-Dimensional Gaussian Graphical Models
    Emmert-Streib, Frank
    Tripathi, Shailesh
    Dehmer, Matthias
    FRONTIERS IN APPLIED MATHEMATICS AND STATISTICS, 2019, 5
  • [43] Gradient-Based Training of Gaussian Mixture Models for High-Dimensional Streaming Data
    Alexander Gepperth
    Benedikt Pfülb
    Neural Processing Letters, 2021, 53 : 4331 - 4348
  • [44] Learning Sparse High-Dimensional Matrix-Valued Graphical Models From Dependent Data
    Tugnait, Jitendra K.
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2024, 72 : 3363 - 3379
  • [45] Gradient-Based Training of Gaussian Mixture Models for High-Dimensional Streaming Data
    Gepperth, Alexander
    Pfulb, Benedikt
    NEURAL PROCESSING LETTERS, 2021, 53 (06) : 4331 - 4348
  • [46] Gaussian Graphical Model Estimation and Selection for High-Dimensional Incomplete Data Using Multiple Imputation and Horseshoe Estimators
    Zhang, Yunxi
    Kim, Soeun
    MATHEMATICS, 2024, 12 (12)
  • [47] Fast Classification Rates for High-dimensional Gaussian Generative Models
    Li, Tianyang
    Prasad, Adarsh
    Ravikumar, Pradeep
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 28 (NIPS 2015), 2015, 28
  • [48] Regularized Parameter Estimation in High-Dimensional Gaussian Mixture Models
    Ruan, Lingyan
    Yuan, Ming
    Zou, Hui
    NEURAL COMPUTATION, 2011, 23 (06) : 1605 - 1622
  • [49] Linear regression and its inference on noisy network-linked data
    Le, Can M.
    Li, Tianxi
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2022, 84 (05) : 1851 - 1885
  • [50] Gaussian Variational Approximations for High-dimensional State Space Models
    Quiroz, Matias
    Nott, David J.
    Kohn, Robert
    BAYESIAN ANALYSIS, 2023, 18 (03): : 989 - 1016