Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains
Authors: Katharina Blechschmidt, Joachim Giesen, Soeren Laue
ICML 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results for kernelized support vector machines and the elastic net confirm the theoretical complexity analysis. |
| Researcher Affiliation | Academia | Friedrich-Schiller-Universit at Jena, Germany |
| Pseudocode | No | Section 4 describes the algorithm's steps in prose ('Initialization.' and 'Iteration.') rather than in a structured pseudocode or algorithm block. |
| Open Source Code | No | The paper states 'In our implementation of the adaptive algorithm from Section 4 we used the LIBSVM package, see (Fan et al., 2005), to compute a near optimal dual solution at a given grid vertex...' and 'In our implementation of the adaptive algorithm from Section 4 we used GLMNET, see (Friedman et al., 2010), for solving the primal optimization problem...' but does not provide a link to the authors' own source code for the described methodology. |
| Open Datasets | Yes | The data sets that have been used in our experiments were obtained from the LIBSVM website, see (Lin) for a description. (Lin) LIBSVM Tools. Data sets available at www.csie.ntu.edu.tw/~cjlin/ libsvmtools/datasets/. |
| Dataset Splits | Yes | In Figure 2(middle) a 10-fold cross-validation plot is shown for the same data set. In Figure 3(middle/left) a 10-fold cross-validation RMSE plot is shown for the same data set. |
| Hardware Specification | No | The paper does not provide any specific hardware details (e.g., GPU/CPU models, memory amounts) used for running its experiments. |
| Software Dependencies | No | The paper mentions using 'LIBSVM package' and 'GLMNET' but does not specify version numbers for these or any other software dependencies. |
| Experiment Setup | Yes | We considered the two-dimensional parameter space (c, γ) with c [2^10, 2^10] and γ [2^10, 2^10], and a uniform grid with vertices at (2^i, 2^j), where i and j were incremented in steps of 0.05, i.e., the grid had 400 x 400 = 160,000 vertices. We considered parameter values λ [0, 1] and c [2^10, 2^5]. |