Bayesian Joint Chance Constrained Optimization: Approximations and Statistical Consistency
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Publication:6176420
DOI10.1137/21m1430005zbMath1522.90051arXiv2106.12199OpenAlexW3175846333MaRDI QIDQ6176420
Prateek Jaiswal, Harsha Honnappa, Unnamed Author
Publication date: 23 August 2023
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2106.12199
Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10) Nonlinear programming (90C30) Stochastic programming (90C15) Queues and service in operations research (90B22)
Cites Work
- Unnamed Item
- Data-driven chance constrained stochastic program
- Mean-variance portfolio optimization when means and covariances are unknown
- Sample average approximation method for chance constrained programming: Theory and applications
- Asymptotic behavior of statistical estimators and of optimal solutions of stochastic optimization problems
- An introduction to MCMC for machine learning
- Bayesian estimation of the global minimum variance portfolio
- Convergence rates of posterior distributions.
- Convergence rates of variational posterior distributions
- On distributionally robust chance constrained programs with Wasserstein distance
- On distributionally robust chance-constrained linear programs
- Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations
- Optimal Experimental Design for Inverse Problems with State Constraints
- A Sample Approximation Approach for Optimization with Probabilistic Constraints
- Uniform Convergence in Probability and Stochastic Equicontinuity
- Asymptotic Statistics
- Stochastic call center staffing with uncertain arrival, service and abandonment rates: A Bayesian perspective
- A Bayesian Risk Approach to Data-driven Stochastic Optimization: Formulations and Asymptotics
- Notes on the Scenario Design Approach
- Solving Chance-Constrained Problems via a Smooth Sample-Based Nonlinear Approximation
- Frequentist Consistency of Variational Bayes
- The Scenario Approach to Robust Control Design
- Probabilistically Constrained Linear Programs and Risk-Adjusted Controller Design
- Convex Approximations of Chance Constrained Programs
- On Bayes procedures
- Portfolio optimisation using constrained hierarchical bayes models
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