LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration
Authors: Gellert Weisz, Andras Gyorgy, Csaba Szepesvari
ICML 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results on configuring a public SAT solver on a new benchmark dataset also stand witness to the superiority of our method. |
| Researcher Affiliation | Collaboration | 1DeepMind, London, UK. 2On leave from Imperial College London, London, UK. 3On leave from University of Alberta, Edmonton, AB, Canada. Correspondence to: Gell ert Weisz <gellert@google.com>, Andr as Gy orgy <agyorgy@google.com>, Csaba Szepesv ari <szepi@google.com>. |
| Pseudocode | Yes | Algorithm 1 LEAPSANDBOUNDS; Algorithm 2 The RUNTIMEEST subroutine; Algorithm 3 Stopping rules |
| Open Source Code | Yes | Finally, to facilitate further research and enable direct comparison to our results, our large-scale measurements on running times of the minisat solver are published together with the paper.2 https://github.com/deepmind/ leaps-and-bounds |
| Open Datasets | Yes | Finally, to facilitate further research and enable direct comparison to our results, our large-scale measurements on running times of the minisat solver are published together with the paper.2 https://github.com/deepmind/ leaps-and-bounds |
| Dataset Splits | No | The paper describes simulating algorithms on a benchmark dataset but does not specify explicit training, validation, or test splits for its own experiments. |
| Hardware Specification | No | The paper mentions 'one second of CPU time' and 'commodity hardware as of 2018' but does not provide specific CPU models, GPU details, or other precise hardware specifications used for experiments. |
| Software Dependencies | Yes | We used minisat9 (Sorensson & Een, 2005) as the SAT solver. ... We used version 2013/09/25. |
| Experiment Setup | Yes | We simulated LEAPSANDBOUNDS and Structured Procrastination on our benchmark dataset with parameters ε = 0.2, δ = 0.2, and ζ = 0.1. ... in the experiments below the value of the multiplier was set to 1.25 (see Appendix F for more details). |