Hyperparameter Estimation for Sparse Bayesian Learning Models
Fuente:
arXiv
Guardado en:
| Autores principales: | Yu, Feng, Shen, Lixin, Song, Guohui |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Leveraging joint sparsity in hierarchical Bayesian learning
por: Glaubitz, Jan, et al.
Publicado: (2023)
por: Glaubitz, Jan, et al.
Publicado: (2023)
The Bayesian SIAC filter
por: Glaubitz, Jan, et al.
Publicado: (2025)
por: Glaubitz, Jan, et al.
Publicado: (2025)
Joint Signal Recovery and Uncertainty Quantification via the Residual Prior Transform
por: Xiao, Yao, et al.
Publicado: (2025)
por: Xiao, Yao, et al.
Publicado: (2025)
A new sparsity promoting residual transform operator for Lasso regression
por: Xiao, Yao, et al.
Publicado: (2025)
por: Xiao, Yao, et al.
Publicado: (2025)
Inexact Generalized Golub-Kahan Methods for Large-Scale Bayesian Inverse Problems
por: Bu, Yutong, et al.
Publicado: (2024)
por: Bu, Yutong, et al.
Publicado: (2024)
Generalized sparsity-promoting solvers for Bayesian inverse problems: Versatile sparsifying transforms and unknown noise variances
por: Lindbloom, Jonathan, et al.
Publicado: (2024)
por: Lindbloom, Jonathan, et al.
Publicado: (2024)
Inner Product Free Krylov Methods for Large-Scale Inverse Problems
por: Brown, Ariana N., et al.
Publicado: (2024)
por: Brown, Ariana N., et al.
Publicado: (2024)
A Majorization-Minimization with Monte Carlo Approach for Hyperparameter Estimation
por: Buser, Elle, et al.
Publicado: (2026)
por: Buser, Elle, et al.
Publicado: (2026)
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation
por: Tan, Hong Ye, et al.
Publicado: (2024)
por: Tan, Hong Ye, et al.
Publicado: (2024)
Gradient-Free Sequential Bayesian Experimental Design via Interacting Particle Systems
por: Gruhlke, Robert, et al.
Publicado: (2025)
por: Gruhlke, Robert, et al.
Publicado: (2025)
Efficient sampling approaches based on generalized Golub-Kahan methods for large-scale hierarchical Bayesian inverse problems
por: Buser, Elle, et al.
Publicado: (2025)
por: Buser, Elle, et al.
Publicado: (2025)
Fast & Fair: Efficient Second-Order Robust Optimization for Fairness in Machine Learning
por: Minch, Allen, et al.
Publicado: (2024)
por: Minch, Allen, et al.
Publicado: (2024)
Bayesian experimental design: grouped geometric pooled posterior via ensemble Kalman methods
por: Yang, Huchen, et al.
Publicado: (2026)
por: Yang, Huchen, et al.
Publicado: (2026)
A Scalable Sequential Framework for Dynamic Inverse Problems via Model Parameter Estimation
por: Keating, Aryeh, et al.
Publicado: (2026)
por: Keating, Aryeh, et al.
Publicado: (2026)
Coupled Input-Output Dimension Reduction: Application to Goal-oriented Bayesian Experimental Design and Global Sensitivity Analysis
por: Chen, Qiao, et al.
Publicado: (2024)
por: Chen, Qiao, et al.
Publicado: (2024)
On Optimal Regularization Parameters via Bilevel Learning
por: Ehrhardt, Matthias J., et al.
Publicado: (2023)
por: Ehrhardt, Matthias J., et al.
Publicado: (2023)
H-CMRH: a novel inner product free hybrid Krylov method for large-scale inverse problems
por: Brown, Ariana N., et al.
Publicado: (2024)
por: Brown, Ariana N., et al.
Publicado: (2024)
Riemannian multigrid line search for low-rank problems
por: Sutti, Marco, et al.
Publicado: (2020)
por: Sutti, Marco, et al.
Publicado: (2020)
Tractable Optimal Experimental Design using Transport Maps
por: Koval, Karina, et al.
Publicado: (2024)
por: Koval, Karina, et al.
Publicado: (2024)
Efficient iterative methods for hyperparameter estimation in large-scale linear inverse problems
por: Hall-Hooper, Khalil A, et al.
Publicado: (2023)
por: Hall-Hooper, Khalil A, et al.
Publicado: (2023)
Kernel-based linear system identification using augmented Krylov subspaces
por: Matti, Fabio, et al.
Publicado: (2026)
por: Matti, Fabio, et al.
Publicado: (2026)
Bayesian--AI Fusion for Epidemiological Decision Making: Calibrated Risk, Honest Uncertainty, and Hyperparameter Intelligence
por: Chatterjee, Debashis
Publicado: (2025)
por: Chatterjee, Debashis
Publicado: (2025)
Hybrid ABBA-GMRES for Unmatched Backprojectors in Large Scale X-Ray Computerized Tomography
por: Bentley, Ryan, et al.
Publicado: (2026)
por: Bentley, Ryan, et al.
Publicado: (2026)
Riemann-Oracle: A general-purpose Riemannian optimizer to solve nearness problems in matrix theory
por: Gnazzo, Miryam, et al.
Publicado: (2024)
por: Gnazzo, Miryam, et al.
Publicado: (2024)
Beating level-set methods for 3D seismic data interpolation: a primal-dual alternating approach
por: Kumar, Rajiv, et al.
Publicado: (2016)
por: Kumar, Rajiv, et al.
Publicado: (2016)
OBK-RCM: Accelerated Orthogonal Block Kaczmarz Algorithm via RCM Reordering and Dynamic Grouping for Sparse Linear Systems
por: Liang, Yu-Fang, et al.
Publicado: (2024)
por: Liang, Yu-Fang, et al.
Publicado: (2024)
Iterative Refinement and Flexible Iteratively Reweighed Solvers for Linear Inverse Problems with Sparse Solutions
por: Onisk, Lucas, et al.
Publicado: (2025)
por: Onisk, Lucas, et al.
Publicado: (2025)
Localized Schrödinger Bridge Sampler
por: Gottwald, Georg A., et al.
Publicado: (2024)
por: Gottwald, Georg A., et al.
Publicado: (2024)
Stable generative modeling using Schrödinger bridges
por: Gottwald, Georg A., et al.
Publicado: (2024)
por: Gottwald, Georg A., et al.
Publicado: (2024)
Fast Algorithms for Optimal Damping in Mechanical Systems
por: Li, Qingna, et al.
Publicado: (2026)
por: Li, Qingna, et al.
Publicado: (2026)
A Reduced Basis Decomposition Approach to Efficient Data Collection in Pairwise Comparison Studies
por: Jiang, Jiahua, et al.
Publicado: (2025)
por: Jiang, Jiahua, et al.
Publicado: (2025)
On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent
por: Laumont, Rémi, et al.
Publicado: (2022)
por: Laumont, Rémi, et al.
Publicado: (2022)
On identification in ill-posed linear regression
por: Finocchio, Gianluca, et al.
Publicado: (2025)
por: Finocchio, Gianluca, et al.
Publicado: (2025)
Randomized flexible Krylov methods for $\ell_p$ regularization
por: Landman, Malena Sabaté, et al.
Publicado: (2025)
por: Landman, Malena Sabaté, et al.
Publicado: (2025)
Mean--Variance Risk-Aware Bayesian Optimal Experimental Design for Nonlinear Models
por: Shen, Wanggang, et al.
Publicado: (2026)
por: Shen, Wanggang, et al.
Publicado: (2026)
A global optimum-informed greedy algorithm for A-optimal experimental design
por: Aarset, Christian
Publicado: (2024)
por: Aarset, Christian
Publicado: (2024)
How Regularization Terms Make Invertible Neural Networks Bayesian Point Estimators
por: Heilenkötter, Nick
Publicado: (2025)
por: Heilenkötter, Nick
Publicado: (2025)
Sequential Least-Squares Estimators with Fast Randomized Sketching for Linear Statistical Models
por: Chen, Guan-Yu, et al.
Publicado: (2025)
por: Chen, Guan-Yu, et al.
Publicado: (2025)
Fast Flexible LSQR with a Hybrid Variant for Efficient Large-Scale Regularization
por: Mikušová, Eva, et al.
Publicado: (2025)
por: Mikušová, Eva, et al.
Publicado: (2025)
Projected iterated Tikhonov regularization in low precision
por: Drum, Chelsea, et al.
Publicado: (2025)
por: Drum, Chelsea, et al.
Publicado: (2025)
Ejemplares similares
-
Leveraging joint sparsity in hierarchical Bayesian learning
por: Glaubitz, Jan, et al.
Publicado: (2023) -
The Bayesian SIAC filter
por: Glaubitz, Jan, et al.
Publicado: (2025) -
Joint Signal Recovery and Uncertainty Quantification via the Residual Prior Transform
por: Xiao, Yao, et al.
Publicado: (2025) -
A new sparsity promoting residual transform operator for Lasso regression
por: Xiao, Yao, et al.
Publicado: (2025) -
Inexact Generalized Golub-Kahan Methods for Large-Scale Bayesian Inverse Problems
por: Bu, Yutong, et al.
Publicado: (2024)