Towards closing the gap between the theory and practice of SVRG
Authors: Othmane Sebbouh, Nidham Gazagnadou, Samy Jelassi, Francis Bach, Robert Gower
NeurIPS 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We performed a series of experiments on data sets from LIBSVM [5] and the UCI repository [3], to validate our theoretical findings. We tested l2 regularized logistic regression on ijcnn1 and real-sim, and ridge regression on slice and Year Prediction MSD. We used two choices for the regularizer: λ = 10 1 and λ = 10 3. All of our code is implemented in Julia 1.0. Due to lack of space, most figures have been relegated to Section G in the supplementary material. |
| Researcher Affiliation | Academia | Othmane Sebbouh LTCI, T el ecom Paris Institut Polytechnique de Paris othmane.sebbouh@gmail.com Nidham Gazagnadou LTCI, T el ecom Paris Institut Polytechnique de Paris nidham.gazagnadou@telecom-paris.fr Samy Jelassi ORFE Department Princeton University sjelassi@princeton.edu Francis Bach INRIA Ecole Normale Sup erieure PSL Research University francis.bach@inria.fr Robert M. Gower LTCI, T el ecom Paris Institut Polytechnique de Paris robert.gower@telecom-paris.fr |
| Pseudocode | Yes | Algorithm 1 Free-SVRG Algorithm 2 L-SVRG-D |
| Open Source Code | No | The information is insufficient. The paper states 'All of our code is implemented in Julia 1.0.' but does not provide a link or explicit statement of open-source availability for the described methodology. |
| Open Datasets | Yes | We performed a series of experiments on data sets from LIBSVM [5] and the UCI repository [3] |
| Dataset Splits | No | The information is insufficient. The paper does not explicitly provide details about training, validation, or test dataset splits. It mentions 'training problems' and 'training sets' in a general context but not specific data partitioning for experiments. |
| Hardware Specification | No | The information is insufficient. The paper does not provide any specific hardware details (e.g., CPU/GPU models, memory, or cloud instance types) used for running the experiments. |
| Software Dependencies | No | The information is insufficient. The paper only states 'All of our code is implemented in Julia 1.0.' without specifying any versioned libraries or solvers. |
| Experiment Setup | Yes | We used two choices for the regularizer: λ = 10 1 and λ = 10 3. |