SGDLibrary: A MATLAB library for stochastic optimization algorithms
Authors: Hiroyuki Kasai
JMLR 2017 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Illustrative results additionally including SQN and SVRG-LBFGS are presented in Figure 1, which are generated by display_graph(), and display_classification_result() specialized for classification problems. Thus, SGDLibrary provides rich visualization tools as well. |
| Researcher Affiliation | Academia | Hiroyuki Kasai EMAIL Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo, 182-8585, Japan |
| Pseudocode | Yes | Listing 1: Demonstration code for logistic regression problem. 1 % generate synthetic 300 samples of dimension 3 for logistic regression 2 d = logistic_regression_data_generator (300 ,3); 3 % define logistic regression problem 4 problem = logistic_regression (d.x_train ,d.y_train ,d.x_test ,d.y_test); 6 options.w_init = d.w_init; % set initial value 7 options.step_init = 0.01; % set initial stepsize 8 options.verbose = 1; % set verbose mode 9 [w_sgd , info_sgd] = sgd(problem , options); % perform SGD solver 10 [w_svrg , info_svrg] = svrg(problem , options); % perform SVRG solver 11 [w_svrg , info_svrg] = sqn(problem , options); % perform SQN solver 12 % display cost vs. number of gradient evaluations 13 display_graph( grad_calc_count , cost ,{ SGD , SVRG } ,... 14 {w_sgd ,w_svrg },{info_sgd ,info_svrg }); |
| Open Source Code | Yes | The code is available at https://github.com/hiroyuki-kasai/SGDLibrary. |
| Open Datasets | No | First, we generate train/test datasets d using logistic_regression_data_generator(), where the input feature vector is with n = 300 and d = 3. |
| Dataset Splits | No | The paper mentions generating synthetic train/test datasets for logistic regression with n=300 and d=3, but does not specify the split ratio or counts for these datasets. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used for the experiments. |
| Software Dependencies | No | The paper mentions that SGDLibrary is a 'pure-MATLAB library' and is 'operable on GNU Octave', but it does not specify any version numbers for MATLAB, Octave, or any other software dependencies. |
| Experiment Setup | Yes | options.w_init = d.w_init; % set initial value options.step_init = 0.01; % set initial stepsize options.verbose = 1; % set verbose mode |