Optimizing Input Data Acquisition for Ranking and Selection

To optimize input data acquisition, we first show that the most probable best (MPB)―the solution with the largest posterior probability of being optimal ( ...

We then create a sequential sampling rule that balances the simulation and input data collection effort. The proposed algorithm stops with posterior confidence ...

Optimizing Input Data Acquisition for Ranking and Selection ...

To optimize input data acquisition, we first show that the most probable best (MPB)---the solution with the largest posterior probability of being optimal ( ...

Optimizing Input Data Acquisition for Ranking and Selection

To optimize input data acquisition, we first show that the most probable best (MPB)-the solution with the largest posterior probability of being optimal ( ...

Optimizing Input Data Collection for Ranking and Selection

Optimizing Input Data Collection for Ranking and Selection. Abstract. We consider a Bayesian ranking and selection problem under input uncertainty when all ...

[PDF] Optimizing Input Data Acquisition for Ranking and Selection

This paper investigates the optimal asymptotic static sampling ratios from the input data sources that maximizes the exponential convergence rate of the ...

Optimizing Input Data Acquisition for Ranking and Selection

VEMP inhibition depth (VEMPid) is a recently developed metric that estimates the percentage of saccular inhibition. VEMPid provides both normalization and ...

Ranking and Selection under Input Uncertainty: A Budget Allocation ...

... ranking & selection (R&S), or more generally as simulation optimization or ... input data is compared with simulation, the fewer input data. 2251. Page 8 ...

Optimizing Data Acquisition to Enhance Machine Learning ...

The state-of-the-art solution is the clustering-based training set selection (CTS) algorithm, which initially clusters the data points in a data pool and ...

Optimizing Data Acquisition to Enhance Machine Learning ...

The efficiency of CTS is constrained by its frequent retraining of the target ML model, and the effectiveness is limited by the selection ...

[PDF] Selection of the Most Probable Best | Semantic Scholar

38 References · Selection of the Most Probable Best Under Input Uncertainty · Optimal Selection of the Most Probable Multinomial Alternative · Robust ranking and ...

Data-Driven Optimal Allocation for Ranking and Selection under ...

In the existing R&S literature, sampling distributions of the observations are usually assumed to be from some known parametric distribution families, even in ...

arXiv:2405.07782v1 [cs.IR] 13 May 2024

This is because for local methods, the selection is made conditioned on full input information, and an incomplete input ... selection for ranking.

Distributionally Robust Selection of the Best | Management Science

Specifying a proper input distribution is often a challenging task in simulation modeling. In practice, there may be multiple plausible ...

Review on ranking and selection: A new perspective

Therefore, a selection procedure is required to determine how many samples need to be collected from each alternative and then which alternative should be ...

GMDH-based feature ranking and selection for improved ...

This paper describes a hierarchical approach to perform complete ranking of the input features according to their predictive quality by using the GMDH-based AIM ...

Review on ranking and selection: A new perspective

Reusing search data in ranking and selection: What could possibly go wrong? ACM Transactions on Modeling and Computer Simulation, 28(3): 1 ...

A worst‐case formulation for constrained ranking and selection with ...

In this research, we consider robust simulation optimization with stochastic constraints. In particular, we focus on the ranking and ...

optimal computing budget allocation for data-driven ranking ... - arXiv

Optimizing input data acquisition for ranking and selection: A view through the most probable best. In 2022 Winter Simulation Conference ...

Optimal computing budget allocation for complete ranking with input ...

To make this optimization problem computationally tractable, we develop an approximated probability of correct ranking and derive the asymptotic optimality ...