Stochastic Dual Coordinate Ascent with Adaptive Probabilities
Authors: Dominik Csiba, Zheng Qu, Peter Richtarik
ICML 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We also propose Ada SDCA+: a practical variant which in our experiments outperforms existing non-adaptive methods. |
| Researcher Affiliation | Academia | Dominik Csiba CDOMINIK@GMAIL.COM University of Edinburgh Zheng Qu ZHENG.QU@ED.AC.UK University of Edinburgh Peter Richt arik PETER.RICHTARIK@ED.AC.UK University of Edinburgh |
| Pseudocode | Yes | Algorithm 1 Ada SDCA |
| Open Source Code | No | The paper does not provide explicit statements or links indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | We used 5 different datasets: w8a, dorothea, mushrooms, cov1 and ijcnn1 (see Table 2). |
| Dataset Splits | No | The paper mentions using datasets (w8a, dorothea, mushrooms, cov1, ijcnn1) but does not provide specific details on how these datasets were split into training, validation, and test sets, or reference standard splits. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., CPU, GPU models, memory, or cloud instance types) used to run the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies or version numbers for any libraries, frameworks, or tools used in the experiments. |
| Experiment Setup | Yes | In all our experiments we used γ = 1 and λ = 1/n. |