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Welcome to CVXPY — CVXPY 0.4.11 documentation

For the best CVXPY support! Try the new, improved CVXPY 1.0, available. Please report any bugs you find! CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers. For example, the following code solves a least-squares problem where the variable is constrained by lower and upper bounds:. The optimal objective is returned by prob.solve().

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Welcome to CVXPY — CVXPY 0.4.11 documentation | cvxpy.org Reviews

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For the best CVXPY support! Try the new, improved CVXPY 1.0, available. Please report any bugs you find! CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers. For example, the following code solves a least-squares problem where the variable is constrained by lower and upper bounds:. The optimal objective is returned by prob.solve().

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Welcome to CVXPY — CVXPY 0.4.11 documentation | cvxpy.org Reviews

https://cvxpy.org

For the best CVXPY support! Try the new, improved CVXPY 1.0, available. Please report any bugs you find! CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers. For example, the following code solves a least-squares problem where the variable is constrained by lower and upper bounds:. The optimal objective is returned by prob.solve().

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cvxpy.org

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Citing CVXPY — CVXPY 0.4.3 documentation

http://www.cvxpy.org/en/latest/citing/index.html

If you use CVXPY for published work, we encourage you to cite the accompanying JMLR MLOSS paper. Use the following BibTeX citation:. Article{cvxpy, author = {Steven Diamond and Stephen Boyd}, title = { CVXPY}: A {P}ython-Embedded Modeling Language for Convex Optimization}, journal = {Journal of Machine Learning Research}, year = {2016}, volume = {17}, number = {83}, pages = {1- 5}, }. Google Summer of Code. Enter search terms or a module, class or function name. Alabaster 0.7.9.

2

Install Guide — CVXPY 0.4.3 documentation

http://www.cvxpy.org/en/latest/install/index.html

To update CVXPY, first update NumPy and SciPy separately. Then run. Can cause errors, especially if you’re using Anaconda. The following instructions assume you already have Python installed. CVXPY supports both Python 2 and Python 3. We recommend using Anaconda. Rather than the Python that comes with the Mac and installing pip, nose, NumPy, SciPy, and CVXOPT through Anaconda. But it is not necessary to have Anaconda. To install CVXPY, and the instructions below assume you do not have Anaconda. There are...

3

How to Help — CVXPY 0.4.3 documentation

http://www.cvxpy.org/en/latest/community/index.html

We welcome all contributors to CVXPY. You don’t need to be an expert in convex optimization to help out! Mailing list is for CVXPY users. Join this mailing list if you have questions about CVXPY or want to track CVXPY’s progress. If you’re interested in contributing to CVXPY, join the Gitter chat. To talk with developers. We use GitHub to track our source code and for tracking and discussing issues. The open issues are a rough list of what needs to be done in developing CVXPY. Google Summer of Code.

4

FAQ — CVXPY 0.4.3 documentation

http://www.cvxpy.org/en/latest/faq/index.html

Where can I get help with CVXPY? Where can I learn more about convex optimization? How do I know which version of CVXPY I’m using? What do I do if I get a. How do I find DCP errors? What do I do if I get a. What solvers does CVXPY support? What are the differences between CVXPY’s solvers? What do I do if I get “Exception: Cannot evaluate the truth value of a constraint”? What do I do if I get “RuntimeError: maximum recursion depth exceeded”? Can I use NumPy functions on CVXPY objects? How does CVXPY work?

5

Examples — CVXPY 0.4.3 documentation

http://www.cvxpy.org/en/latest/examples/index.html

These examples show many different ways to use CVXPY. The Basic Examples. Section shows how to solve some common optimization problems in CVXPY. The Advanced Examples. Sections contains more complex examples aimed at experts in convex optimization. SVM classifier with regularization. Allocating interdiction effort to catch a smuggler. Computing a sparse solution of a set of linear inequalities. Optimal power and bandwidth allocation in a Gaussian broadcast channel. Predicting NBA game wins.

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Install Guide — ProxImaL 0.1.3 documentation

http://www.proximal-lang.org/en/latest/install/index.html

The easiest way to install ProxImaL and its dependencies is using Anaconda. To install ProxImaL without Anaconda. See the section on installation from source. On Linux and Mac OS X, install all Python dependencies by running. Conda install numpy scipy pil pip opencv. On Windows, install all Python dependencies by running. Conda install numpy scipy pil pip conda install -c https:/ conda.binstar.org/menpo opencv. Environment variable to point to the installation. Also, add the Halide. For Mac OS X.

cvxopt.org

Applications and extensions — CVXOPT

http://cvxopt.org/applications/index.html

Building CVXOPT with ATLAS. Building CVXOPT for Windows. A solver for sparse matrix cone programs. Other projects that use CVXOPT. A convex optimization modeling package. A Python Interface for Conic Optimization Solvers. A free alternative to Magma, Maple, Mathematica and Matlab. A general platform for numerical optimization. A collection of iterative solvers for CVXOPT. A python package for sigmoidal programming. Provided by Read the Docs.

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cvxpy.org

Welcome to CVXPY — CVXPY 0.4.11 documentation

For the best CVXPY support! Try the new, improved CVXPY 1.0, available. Please report any bugs you find! CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers. For example, the following code solves a least-squares problem where the variable is constrained by lower and upper bounds:. The optimal objective is returned by prob.solve().

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CVX Research, Inc. Software for Disciplined Convex Programming. CVX: a Matlab-based convex modeling framework. Is a popular modeling framework for disciplined convex programming. That CVX turns Matlab. Disciplined convex programs (MIDCPs). CVX. Is free for use in academic and commercial applications when paired with one of the included free solvers, SeDuMi or SDPT3. A CVX Professional. Unlocks the ability to use CVX with commercial solvers Gurobi. TFOCS: Templates for First-Order Conic Solvers. It has be...

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