Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs
Authors: Vu Viet Hoang, Quoc Anh Hoang Nguyen, Hung The Tran
AAAI 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we show that our proposed algorithm outperforms comparable baselines across a wide range of benchmarks. We conducted an empirical evaluation of our proposed algorithm s performance against baseline methods across a variety of experimental conditions. This included testing on both synthetic and real-world datasets, specifically a plant growth dataset and an airfoil self-noise dataset, which are relevant to the precision agriculture and advanced manufacturing applications discussed earlier. |
| Researcher Affiliation | Collaboration | 1FPT Software AI Center 2Hanoi University of Science and Technology |
| Pseudocode | Yes | Algorithm 1: Proposed method |
| Open Source Code | No | The paper does not contain any explicit statements about providing open-source code, nor does it include links to a code repository. |
| Open Datasets | Yes | (d) a simulator built from the airfoil self-noise dataset (5-D) from the UCI Machine Learning Repository (Dua, Graff et al. 2017). |
| Dataset Splits | No | The paper mentions using synthetic and real-world datasets but does not specify any training, validation, or test dataset splits, percentages, or methodology for splitting the data. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used to run the experiments, such as GPU models, CPU types, or memory specifications. |
| Software Dependencies | No | The paper discusses concepts like Gaussian Processes and Multi-Armed Bandits and mentions specific algorithms such as UCB, TS-PSQ, UCB-PSQ, and UCB-CVS. However, it does not provide specific version numbers for any software libraries, frameworks, or programming languages used in the implementation. |
| Experiment Setup | Yes | In the proposed method, we spend 60 units of cost for the exploration phase. The parameter α at the beginning of the exploitation phase is set to 0.1 and is halved after d function evaluations. |