Preselection Bandits
Authors: Viktor Bengs, Eyke Hüllermeier
ICML 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We devote Section 6 to a simulation study demonstrating the usefulness and effi ciency of our algorithms. In this section, we investigate the performance of TRCB (Algorithm 1) as well as CBR (Algorithm 2) on synthetic data for some specific scenarios, while providing further scenarios in the supplementary material. |
| Researcher Affiliation | Academia | 1Heinz Nixdorf Institute and Department of Computer Science, Paderborn University, Germany. |
| Pseudocode | Yes | Algorithm 1 TRCB algorithm; Algorithm 2 CBR-algorithm |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for its methodology is openly available. |
| Open Datasets | No | We investigate the performance of TRCB (Algorithm 1) as well as CBR (Algorithm 2) on synthetic data for some specific scenarios... The score parameters θ = (θi)i [n] are drawn uniformly at random from the n-simplex... |
| Dataset Splits | No | The paper states it uses 'randomly generated restricted Pre-Bandit instances' and 'randomly generated flexible Pre-Bandit instances' but does not specify any dataset splits (e.g., training, validation, test percentages or counts). |
| Hardware Specification | No | The authors gratefully acknowledge financial support by the Germany Research Foundation (DFG). Moreover, the authors would like to thank the Paderborn Center for Parallel Computation (PC2) for the use of the OCu LUS cluster. |
| Software Dependencies | No | The paper does not specify any software names with version numbers used for implementation or dependencies. |
| Experiment Setup | Yes | We consider the case n = 10, l = 3, and time horizons T ∈ {i · 2000}i=1. The degree of preciseness is γ = 1 throughout, and the score parameters θ = (θi)i∈[n] are drawn uniformly at random from the n-simplex... In the right picture of Figure 1, the results are displayed for the CBR resp. DTS algorithm on 1000 repetitions, respectively, with n ∈ {5, 10, 15}, T ∈ {i · 2000}5 i=1 , and σ(x) = (1 − x)1[0,)(x). |