Image de couverture de livre

Shape-Constrained Distributional Optimization via Importance-Weighted Sample Average Approximation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lam, Henry, Liu, Zhenyuan, Singham, Dashi I.
Format:	Preprint
Publié:	2024
Sujets:	Optimization and Control Methodology
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

0/1 Constrained Optimization Solving Sample Average Approximation for Chance Constrained Programming
par: Zhou, Shenglong, et autres
Publié: (2022)

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

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

Assortment Optimization and the Sample Average Approximation
par: Khalid, Hassaan, et autres
Publié: (2025)

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

Stochastic Optimization with Optimal Importance Sampling
par: Aolaritei, Liviu, et autres
Publié: (2025)

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

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

Sample Average Approximation for Distributionally Robust Optimization with $ϕ$-divergences
par: Li, Yan
Publié: (2026)

Online Resource Allocation with Average Budget Constraints
par: Ao, Ruicheng, et autres
Publié: (2024)

A Proximal DC Algorithm for Sample Average Approximation of Chance Constrained Programming
par: Wang, Peng, et autres
Publié: (2023)

Decision-Focused Bias Correction for Fluid Approximation
par: Er, Can, et autres
Publié: (2025)

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

Data-Driven Influence Functions for Optimization-Based Causal Inference
par: Jordan, Michael I., et autres
Publié: (2022)

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

Robust Learning Rate Selection for Stochastic Optimization via Splitting Diagnostic
par: Sordello, Matteo, et autres
Publié: (2019)

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

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

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

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

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

Data-Driven Sequential Sampling for Tail Risk Mitigation
par: Ahn, Dohyun, et autres
Publié: (2025)

Fast algorithm for sparse least trimmed squares via trimmed-regularized reformulation
par: Yagishita, Shotaro
Publié: (2024)

Robust Data-driven Prescriptiveness Optimization
par: Poursoltani, Mehran, et autres
Publié: (2023)

DCILP: A Distributed Approach for Large-Scale Causal Structure Learning
par: Dong, Shuyu, et autres
Publié: (2024)

Optimizing Input Data Collection for Ranking and Selection
par: Song, Eunhye, et autres
Publié: (2025)

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

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

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

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

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

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

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

Batch-based Bayesian Optimal Experimental Design in Linear Inverse Problems
par: Mäkinen, Sofia, et autres
Publié: (2026)

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)

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

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

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

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