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..
Failure-Aware Gaussian Process Optimization with Regret Bounds
Authors: Shogo Iwazaki, Shion Takeno, Tomohiko Tanabe, Mitsuru Irie
NeurIPS 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate the effectiveness of F-GP-UCB in several benchmark functions, including the simulation function motivated by material synthesis experiments. |
| Researcher Affiliation | Collaboration | Shogo Iwazaki MI-6 Ltd., Tokyo, Japan EMAIL Shion Takeno RIKEN AIP, Tokyo, Japan EMAIL Tomohiko Tanabe MI-6 Ltd., Tokyo, Japan EMAIL Mitsuru Irie MI-6 Ltd., Tokyo, Japan EMAIL |
| Pseudocode | Yes | Algorithm 1 The F-GP-UCB algorithm ... Algorithm 4 in Appendix E.3 shows the pseudo-code of our modified strategy. |
| Open Source Code | No | The paper does not provide an explicit link to open-source code for the methodology presented in this paper. It mentions GPy (a third-party library) in its references, but no code for their specific F-GP-UCB implementation. |
| Open Datasets | Yes | Synthetic experiments with the Branin function. ... We perform a numerical experiment involving quasicrystals in the Al-Cu-Mn system. ... The feasible region is the composition values that form quasicrystals based on data [16]. |
| Dataset Splits | No | The paper does not explicitly provide training/test/validation dataset splits or cross-validation details for the experiments. It describes how the GP model is updated with successful observations during the optimization process. |
| Hardware Specification | No | The paper does not specify any hardware used for running the experiments (e.g., GPU models, CPU models, memory). |
| Software Dependencies | No | The paper mentions software like GPy and NLopt, but does not provide specific version numbers for these or other libraries, which are necessary for reproducible software dependencies. |
| Experiment Setup | Yes | We set βt = 2 ln(2t) as in [24] for GP-UCB and F-GP-UCB. The other parameters in F-GP-UCB are fixed as described in Sec. 5. For example, we set w = 0.75, hσ = 0.02, q = 3, θmin = 0.0001, and θmax = 0.5. ... We also fix the noise variance hyperparameter of the GP model for f to 0.0001. |