Image de couverture de livre

Batch-based Bayesian Optimal Experimental Design in Linear Inverse Problems

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Mäkinen, Sofia, Duncan, Andrew B., Helin, Tapio
Format:	Preprint
Publié:	2026
Sujets:	Methodology Optimization and Control
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

PNOD: An Efficient Projected Newton Framework for Exact Optimal Experimental Designs
par: Liang, Ling, et autres
Publié: (2024)

Operational Dosage: Implications of Capacity Constraints for the Design and Interpretation of Experiments
par: Boutilier, Justin, et autres
Publié: (2024)

Evaluating consumption effects of intelligent control algorithms for district heated buildings
par: Solonen, Antti, et autres
Publié: (2026)

Posterior and Likelihood Sensitivity in Bayesian Distributionally Robust Optimization
par: Gotoh, Jun-ya, et autres
Publié: (2026)

Optimal Cross-Validation for Sparse Linear Regression
par: Cory-Wright, Ryan, et autres
Publié: (2023)

Generalized modes in Bayesian inverse problems
par: Clason, Christian, et autres
Publié: (2018)

Solving Minimax Problems with Bilinear Objectives with ADMM
par: Wilson, Bob
Publié: (2026)

A Non-Gaussian Bayesian Filter Using Power and Generalized Logarithmic Moments
par: Wu, Guangyu, et autres
Publié: (2022)

Experimenting under Stochastic Congestion
par: Li, Shuangning, et autres
Publié: (2023)

Reduced-Rank Estimation for Ill-Conditioned Stochastic Linear Model with High Signal-to-Noise Ratio
par: Piotrowski, Tomasz, et autres
Publié: (2024)

Truncated Multidimensional Trigonometric Moment Problem: A Choice of Bases and the Unique Solution
par: Wu, Guangyu, et autres
Publié: (2026)

The Monge optimal transport barycenter problem
par: Lipnick, Andrew D., et autres
Publié: (2025)

Learning Large Causal Structures from Inverse Covariance Matrix via Sparse Matrix Decomposition
par: Dong, Shuyu, et autres
Publié: (2022)

Automatic Outlier Rectification via Optimal Transport
par: Blanchet, Jose, et autres
Publié: (2024)

Bayesian optimization for mixed variables using an adaptive dimension reduction process: applications to aircraft design
par: Saves, Paul, et autres
Publié: (2025)

Bridging Constraints and Stochasticity: A Fully First-Order Method for Stochastic Bilevel Optimization with Linear Constraints
par: Phan, Cac, et autres
Publié: (2025)

Unmixing highly mixed grain size distribution data via maximum volume constrained end member analysis
par: Qi, Qianqian, et autres
Publié: (2026)

Toward Exact Convergence in Byzantine-Robust Decentralized Learning: A Statistical Identification Approach
par: Zhang, Siyuan, et autres
Publié: (2026)

Fenchel-Young Estimators of Perturbed Utility Models
par: Lin, Xi, et autres
Publié: (2026)

Feasibility Determination for Subjective Probability Constraints
par: Kim, Taehoon, et autres
Publié: (2026)

An Efficient Dual ADMM for Huber Regression with Fused Lasso Penalty
par: Shi, Mengjiao, et autres
Publié: (2025)

Joint optimization for production operations considering reworking
par: Shen, Yilan, et autres
Publié: (2024)

A Graph-Prediction-Based Approach for Debiasing Underreported Data
par: Jiang, Hanyang, et autres
Publié: (2023)

Sensitivity Analysis for Binary Outcome Misclassification in Randomization Tests via Integer Programming
par: Heng, Siyu, et autres
Publié: (2022)

Tuning parameter selection for the adaptive nuclear norm regularized trace regression
par: Shang, Pan, et autres
Publié: (2024)

Clustering sequence data with mixture Markov chains with covariates using multiple simplex constrained optimization routine (MSiCOR)
par: Das, Priyam, et autres
Publié: (2016)

Constrained Markov decision processes for response-adaptive procedures in clinical trials with binary outcomes
par: Baas, Stef, et autres
Publié: (2024)

Fixed Confidence and Fixed Tolerance Bi-level Optimization for Selecting the Best Optimized System
par: Wang, Yuhao, et autres
Publié: (2025)

Distributionally robust halfspace depth
par: Ivanovs, Jevgenijs, et autres
Publié: (2021)

Distributed Online Economic Dispatch with Time-Varying Coupled Inequality Constraints
par: Zhou, Yingjie, et autres
Publié: (2025)

The hierarchical barycenter: conditional probability simulation with structured and unobserved covariates
par: Tabak, Esteban G., et autres
Publié: (2025)

Semismooth Newton Augmented Lagrangian Algorithm for Adaptive Lasso Penalized Least Squares in Semiparametric Regression
par: Li, Peili, et autres
Publié: (2021)

Safe subspace screening for the adaptive nuclear norm regularized trace regression
par: Shang, Pan, et autres
Publié: (2024)

Shape-Constrained Distributional Optimization via Importance-Weighted Sample Average Approximation
par: Lam, Henry, et autres
Publié: (2024)

Derivative Estimation from Coarse, Irregular, Noisy Samples: An MLE-Spline Approach
par: Avrachenkov, Konstantin E., et autres
Publié: (2025)

Filtering Dynamical Systems Using Observations of Statistics
par: Bach, Eviatar, et autres
Publié: (2023)

Sensitivity analysis for stopping criteria with application to organ transplantations
par: Ren, Xingyu, et autres
Publié: (2026)

Recursive identification with regularization and on-line hyperparameters estimation
par: Vau, Bernard, et autres
Publié: (2023)

Optimal Experimental Design for Large-Scale Inverse Problems via Multi-PDE-constrained Optimization
par: Petrocchi, Andrea, et autres
Publié: (2024)

Fast Rerandomization via the BRAIN
par: Lu, Jiuyao, et autres
Publié: (2023)