Real-Time Selection Under General Constraints via Predictive Inference
Authors: Yuyang Huo, Lin Lu, Haojie Ren, Changliang Zou
NeurIPS 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We illustrate the breadth of applicability of the II-COS procedure by experiments on simulated data and real-data applications. |
| Researcher Affiliation | Academia | 1School of Statistics and Data Sciences, LPMC, KLMDASR and LEBPS, Nankai University, Tianjin, China 2School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China |
| Pseudocode | Yes | Algorithm 1 The data-driven II-COS procedure |
| Open Source Code | Yes | Code for implementing II-COS and reproducing the experiments and figures in our paper is available at https://github.com/lulin2023/II-COS. |
| Open Datasets | Yes | We consider the recruitment dataset from Kaggle [22] that contains 45,372 candidates... The other problem is to use 1994 Census Bureau dataset [8] to select a subset of individuals who may have high incomes in precision marketing. |
| Dataset Splits | Yes | we resort to a data-splitting strategy: randomly split historical data D into two parts, the training set Dtr and the calibration one Dcal of sizes n0 and n1 respectively. For each dataset, we randomly partition the data into three parts: ntr = 1,000 training data, ncal = 1,000 calibration data and the rest which are used as the online observations. |
| Hardware Specification | Yes | All the experiments were conducted on 3.11 GHz Intel Gen i5-11300H processors with 16 Gb memory at a Lenovo personal computer |
| Software Dependencies | Yes | R platform with version 4.2.1. implemented by R package nnet and R packages kernlab |
| Experiment Setup | Yes | As an example, we set the stopping rule as selecting total m = 100 samples, i.e., T = Tm = inft{t : Pt i=1 δi = m}. The predictor H is taken as random forest with defaulted parameters. We fix training data size ntr = 1, 000. Take α = 0.1 and K = 0.045 for FSR and m ES, respectively. |