SAGA with Arbitrary Sampling
Authors: Xun Qian, Zheng Qu, Peter Richtárik
ICML 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We tested SAGA-AS to solve the logistic regression problem (23) on 3 different datasets: w8a, a9a and ijcnn14. The experiments presented in Section 5.1 and 5.2 are tested for λ1 = 0 and λ2 = 1e 5, which is of the same order as the number of samples in the three datasets. In Section 5.3 we test on the unregularized problem with λ1 = λ2 = 0. In all the plots, the x-axis records the number of pass of the dataset. More experiments can be found in the Suppl. |
| Researcher Affiliation | Academia | 1King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia 2University of Hong Kong, Hong Kong 3Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia. |
| Pseudocode | Yes | Algorithm 1 SAGA with Arbitrary Sampling (SAGA-AS) |
| Open Source Code | No | The paper does not provide any explicit statement about releasing source code for the SAGA-AS method, nor does it include a link to a code repository. |
| Open Datasets | Yes | We tested SAGA-AS to solve the logistic regression problem (23) on 3 different datasets: w8a, a9a and ijcnn14. ... 4https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/ |
| Dataset Splits | No | The paper mentions using specific datasets but does not explicitly describe the training, validation, or test dataset splits (e.g., percentages or sample counts). |
| Hardware Specification | No | The paper does not specify any particular hardware used for running the experiments, such as CPU or GPU models, or cloud computing instances. |
| Software Dependencies | No | The paper mentions “libsvmtools/datasets/” as a source for datasets but does not provide specific version numbers for any software dependencies, libraries, or programming languages used for the implementation or experiments. |
| Experiment Setup | Yes | The experiments presented in Section 5.1 and 5.2 are tested for λ1 = 0 and λ2 = 1e 5, which is of the same order as the number of samples in the three datasets. In Section 5.3 we test on the unregularized problem with λ1 = λ2 = 0. ... We compare uniform sampling SAGA (SAGA-UNI) with importance sampling SAGA (SAGA-IP), as described in Section 3.3 , on three values of τ {1, 10, 50}. |