CVXPY: A Python-Embedded Modeling Language for Convex Optimization
Authors: Steven Diamond, Stephen Boyd
JMLR 2016 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | CVXPY is a domain-speciļ¬c language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math, rather than in the restrictive standard form required by solvers. CVXPY makes it easy to combine convex optimization with high-level features of Python such as parallelism and object-oriented design. |
| Researcher Affiliation | Academia | Steven Diamond EMAIL Stephen Boyd EMAIL Departments of Computer Science and Electrical Engineering Stanford University Stanford, CA 94305, USA |
| Pseudocode | No | The paper includes Python code snippets demonstrating the use of CVXPY, such as for constructing and solving a least squares problem or a LASSO problem, and for defining object-oriented optimization problems. However, these are direct code examples, not abstracted pseudocode or algorithm blocks. |
| Open Source Code | Yes | CVXPY is available at http://www.cvxpy.org/ under the GPL license, along with documentation and examples. |
| Open Datasets | No | The paper describes a software tool for convex optimization and provides example problems (e.g., least squares, LASSO). It does not use specific named datasets for empirical evaluation or provide access information for any datasets. |
| Dataset Splits | No | The paper introduces a software tool for convex optimization and demonstrates its syntax with examples. It does not perform experiments on specific datasets that would require reporting dataset splits. |
| Hardware Specification | No | The paper describes a software tool (CVXPY) and its features. It does not conduct experiments that would require specific hardware specifications to be reported. It mentions that SCS, a solver that CVXPY interfaces with, 'uses Open MP to target multiple cores', but this is a feature of the solver, not a hardware specification for experiments performed in this paper. |
| Software Dependencies | No | The paper states that 'CVXPY is an ordinary Python library' and mentions 'Num Py ndarrays'. It also mentions interfacing with 'open-source cone solvers CVXOPT, ECOS, and SCS'. However, it does not provide specific version numbers for Python, NumPy, or these solvers within the main text. |
| Experiment Setup | No | The paper focuses on describing a domain-specific language for convex optimization and its features. It does not present empirical experiments with hyperparameters, training configurations, or system-level settings. |