Geometric convergence of elliptical slice sampling
Authors: Viacheslav Natarovskii, Daniel Rudolf, Björn Sprungk
ICML 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We illustrate our result for Gaussian posteriors as they appear in Gaussian process regression, as well as in a setting of a multi-modal distribution. Remarkably, our numerical experiments indicate a dimension-independent performance of elliptical slice sampling even in situations where our ergodicity result does not apply. |
| Researcher Affiliation | Academia | 1Institute for Mathematical Stochastics, Georg-August Universit at G ottingen, G ottingen, Germany 2Faculty of Mathematics and Computer Science, Technische Universit at Bergakademie Freiberg, Germany. |
| Pseudocode | Yes | Algorithm 1 Elliptical Slice Sampler |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper discusses 'Gaussian process regression' and 'logistic regression' with data, but does not provide specific access information (link, DOI, citation) for any publicly available dataset used in its experiments. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types, or memory amounts) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library names with version numbers, needed to replicate the experiment. |
| Experiment Setup | Yes | For each algorithm we set the initial state to be 0 Rd and compute the ESS for f(x) := log(1 + x ), n0 := 105 and n := 106. Both Metropolis algorithms (the RWM and the p CN Metropolis) were tuned to an averaged acceptance probability of approximately 0.25. |