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..
Closing the convergence gap of SGD without replacement
Authors: Shashank Rajput, Anant Gupta, Dimitris Papailiopoulos
ICML 2020 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | To verify our lower bound of Theorem 2, we ran SGDo on the function described in Eq. (5) with L = 4. The step size regimes that were considered were α = 1 T , 2 log T T , 4 log T T , 8 log T n. The plot for α = 4 log T T is shown in Figure 2. |
| Researcher Affiliation | Academia | 1University of Wisconsin Madison. Correspondence to: Shashank Rajput <EMAIL>. |
| Pseudocode | No | The paper does not contain any clearly labeled pseudocode or algorithm blocks. |
| Open Source Code | Yes | The code for these experiments is available at https://github.com/shashankrajput/SGDo. |
| Open Datasets | No | The paper uses a custom function described in Eq. (5) for numerical verification and does not mention or provide access to a publicly available or open dataset. 'To verify our lower bound of Theorem 2, we ran SGDo on the function described in Eq. (5) with L = 4.' |
| Dataset Splits | No | The paper describes experiments on a constructed function by varying parameters (K, n) but does not specify training, validation, or test dataset splits in the conventional sense. |
| Hardware Specification | No | The paper does not provide any specific hardware details such as GPU models, CPU models, or memory specifications used for running experiments. |
| Software Dependencies | No | The paper does not list any specific software dependencies with version numbers (e.g., programming languages, libraries, or solvers). |
| Experiment Setup | Yes | The step size regimes that were considered were α = 1 T , 2 log T T , 4 log T T , 8 log T n. ... For each value of K, say K = 50, we set α = T = 4 log(n K) n K = 4 log(500 50) 500 50 and ran SGDo with this constant step size α on the sum of n = 500 functions for K = 50 epochs, and the final error was recorded. ... The optimization was initialized at the origin, that is x1 0 = 0. |