Prediction models with graph kernel regularization for network data
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Publication:6107665
DOI10.1080/02664763.2022.2028745OpenAlexW4210613152MaRDI QIDQ6107665
Haojie Chen, Jie Liu, Yang Yang
Publication date: 3 July 2023
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://figshare.com/articles/journal_contribution/Prediction_models_with_graph_kernel_regularization_for_network_data/19096327
Cites Work
- Unnamed Item
- The Adaptive Lasso and Its Oracle Properties
- Community detection in networks with node features
- Variable selection and regression analysis for graph-structured covariates with an application to genomics
- Least angle regression. (With discussion)
- Prediction models for network-linked data
- Network‐Based Penalized Regression With Application to Genomic Data
- Spectral Sparsification of Graphs
- Incorporating Predictor Network in Penalized Regression with Application to Microarray Data
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Community Detection and Stochastic Block Models
- Sparsity and Smoothness Via the Fused Lasso
- Regularization and Variable Selection Via the Elastic Net
- Covariate-assisted spectral clustering
- Model Selection and Estimation in Regression with Grouped Variables
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