mlsanityData to 7 Oct 2026

Transfer Learning in Large-scale Gaussian Graphical Models with False Discovery Rate Control

arXiv 2010.11037 ↗First posted 21 Oct 2020stat.ME stat.MLcited by 38

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Abstract (arXiv)

Transfer learning for high-dimensional Gaussian graphical models (GGMs) is studied with the goal of estimating the target GGM by utilizing the data from similar and related auxiliary studies. The similarity between the target graph and each auxiliary graph is characterized by the sparsity of a divergence matrix. An estimation algorithm, Trans-CLIME, is proposed and shown to attain a faster convergence rate than the minimax rate in the single study setting. Furthermore, a debiased Trans-CLIME estimator is introduced and shown to be element-wise asymptotically normal. It is used to construct a multiple testing procedure for edge detection with false discovery rate control. The proposed estimation and multiple testing procedures demonstrate superior numerical performance in simulations and are applied to infer the gene networks in a target brain tissue by leveraging the gene expressions from multiple other brain tissues. A significant decrease in prediction errors and a significant increase in power for link detection are observed.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Oct 2020.

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Citing papers per year: 2021: 2; 2022: 3; 2023: 8; 2024: 9; 2025: 9; 2026: 7.

38 papers.

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  1. 2021Transfer Learning under High-dimensional Generalized Linear Modelscited by 69
  2. 2023Deep Transfer Learning for Automatic Speech Recognition: Towards Better Generalizationcited by 28
  3. 2022Transfer Learning for Contextual Multi-armed Banditscited by 24
  4. 2023Deep transfer learning for intrusion detection in industrial control networks: A comprehensive reviewcited by 21
  5. 2021Targeting Underrepresented Populations in Precision Medicine: A Federated Transfer Learning Approachcited by 20
  6. 2024Transfer Learning for Nonparametric Regression: Non-asymptotic Minimax Analysis and Adaptive Procedurecited by 19
  7. 2024Transfer Learning Beyond Bounded Density Ratioscited by 6
  8. 2024Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Biomedical Data Analysiscited by 6
  9. 2023Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shiftcited by 5
  10. 2023Guided Adversarial Robust Transfer Learning with Source Mixingcited by 4
  11. 2022Transfer Q-learningcited by 3
  12. 2023Transfer Learning for Kernel-based Regressioncited by 3
26 more
  1. 2023Bayesian Transfer Learningcited by 3
  2. 2022Transfer learning for tensor Gaussian graphical modelscited by 2
  3. 2023Multi-dimensional domain generalization with low-rank structurescited by 2
  4. 2024AdaTrans: Feature-wise and Sample-wise Adaptive Transfer Learning for High-dimensional Regressioncited by 2
  5. 2024Covariate-Elaborated Robust Partial Information Transfer with Conditional Spike-and-Slab Priorcited by 2
  6. 2024Trans-Glasso: A Transfer Learning Approach to Precision Matrix Estimationcited by 2
  7. 2025Fixed-Gaussian Spectral Algorithms: Minimax Optimal Rates for Misspecified Learning and Transfercited by 2
  8. 2024Transfer Learning for Spatial Autoregressive Models with Application to U.S. Presidential Election Predictioncited by 1
  9. 2025Late Fusion Multi-task Learning for Semiparametric Inference with Nuisance Parameterscited by 1
  10. 2023Structural transfer learning of non-Gaussian DAGcited by 0
  11. 2024An adaptive transfer learning perspective on classification in non-stationary environmentscited by 0
  12. 2024Transfer Learning in ℓ1 Regularized Regression: Hyperparameter Selection Strategy based on Sharp Asymptotic Analysiscited by 0
  13. 2025Sparse Optimization for Transfer Learning: A L0-Regularized Framework for Multi-Source Domain Adaptationcited by 0
  14. 2025Transfer Learning for High-dimensional Reduced Rank Time Series Modelscited by 0
  15. 2025Transfer Learning for Matrix Completioncited by 0
  16. 2025Adaptive Multi-task Learning for Multi-sector Portfolio Optimizationcited by 0
  17. 2025Formal Bayesian Transfer Learning via the Total Risk Priorcited by 0
  18. 2025Transfer learning under latent space modelcited by 0
  19. 2025Transfer Learning with Distance Covariance for Random Forest: Error Bounds and an EHR Applicationcited by 0
  20. 2026Model-agnostic information transfer and fusion for classification with label noisecited by 0
  21. 2026Harnessing Source Heterogeneity for Cluster-Structured Transfer Learningcited by 0
  22. 2026Multi-Source Transfer Learning of Sparse Single-Index Modelscited by 0
  23. 2026Transfer Learning in High-dimensional Ising Modelscited by 0
  24. 2026Joint estimation of high-dimensional spiked covariance matrices via a partially shared subspacecited by 0
  25. 2026Transfer Learning in Nonparametric Regression with Deep ReLU Networkscited by 0
  26. 2026Guided Uncertainty-Aware Robust Domain Transfercited by 0