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; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1]
Primal-Dual Rates and Certificates
Authors: Celestine Dünner, Simone Forte, Martin Takac, Martin Jaggi
ICML 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Here we illustrate the usefulness of our framework by showcasing it for two important applications, each one showing two algorithm examples for optimizing (A). The top row of Figure 2 shows the primal-dual convergence of Algorithm 1 (CD) as well as the accelerated variant of CD (APPROX, Fercoq & Richt arik (2015)), both applied to the Lasso problem (A). On the bottom row of Figure 2 we compare CD with its accelerated variant on two benchmark datasets.5 We have chosen λ = 1/n. |
| Researcher Affiliation | Collaboration | Celestine D unner EMAIL IBM Research, Z urich, Switzerland Simone Forte EMAIL ETH Z urich, Switzerland Martin Tak aˇc EMAIL Lehigh University, USA Martin Jaggi EMAIL ETH Z urich, Switzerland |
| Pseudocode | Yes | Algorithm 1 Coordinate Descent on D(α) |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. |
| Open Datasets | Yes | On the bottom row of Figure 2 we compare CD with its accelerated variant on two benchmark datasets.5 We have chosen λ = 1/n. Footnote 5: Available from csie.ntu.edu.tw/ cjlin/libsvmtools/datasets. |
| Dataset Splits | No | The paper mentions using benchmark datasets but does not specify exact training/validation/test split percentages, sample counts, or explicitly reference predefined splits with citations. |
| 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 (e.g., library or solver names with version numbers) needed to replicate the experiments. |
| Experiment Setup | Yes | On the bottom row of Figure 2 we compare CD with its accelerated variant on two benchmark datasets.5 We have chosen λ = 1/n. |