Continuous-time Models for Stochastic Optimization Algorithms
Authors: Antonio Orvieto, Aurelien Lucchi
NeurIPS 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We verify this result on a one dimensional quadratic, under the choice of parameters in our example, using Euler-Maruyama simulation (i.e. PGD) with h = 10 3, σ = 5. In Fig. 1 we show the mean and standard deviation relative to 20 realization of the Gaussian noise. |
| Researcher Affiliation | Academia | Antonio Orvieto Department of Computer Science ETH Zurich, Switzerland Aurelien Lucchi Department of Computer Science ETH Zurich, Switzerland |
| Pseudocode | No | The paper presents mathematical equations and descriptions of algorithms (e.g., MB-PGD, VR-PGD) but does not include any formally labeled 'Pseudocode' or 'Algorithm' blocks. |
| Open Source Code | No | The paper does not provide an explicit statement about releasing source code or a link to a code repository for the described methodology. |
| Open Datasets | No | The empirical verification is performed on 'a one dimensional quadratic', which is a synthetic function used for simulation and not a publicly available dataset with concrete access information. |
| Dataset Splits | No | The paper describes a simulation on a synthetic one-dimensional quadratic function and does not provide details about training, validation, or test dataset splits. |
| Hardware Specification | No | The paper mentions 'using Euler-Maruyama simulation' but does not provide any specific hardware details (e.g., GPU/CPU models, memory) used for running this simulation. |
| Software Dependencies | No | The paper mentions 'Euler-Maruyama simulation' as the method used, but does not provide specific software dependencies or version numbers (e.g., programming languages, libraries, or simulation software with versions) needed to replicate the experiment. |
| Experiment Setup | Yes | We verify this result on a one dimensional quadratic, under the choice of parameters in our example, using Euler-Maruyama simulation (i.e. PGD) with h = 10 3, σ = 5. |