public marks

PUBLIC MARKS from ogrisel with tags optimization & python

May 2008

CVXMOD – Convex optimization software in Python

CVXMOD is a Python-based tool for expressing and solving convex optimization problems. It uses CVXOPT as its solver. It is developed by Jacob Mattingley, as PhD work under Stephen Boyd at Stanford University. CVXMOD is primarily a modeling layer for CVXOPT. While it is possible to use CVXOPT directly, CVXMOD makes it faster and easier to build and solve problems. Advanced users who want to see or manipulate how their problems are being solved should consider using CVXOPT directly. Additional features are being added to CVXMOD beyond just modeling. These are currently experimental. CVXMOD has a similar design philosophy to CVX, a convex optimization modeling language for Matlab®, and uses the principles of disciplined convex programming, as developed by Michael Grant, Stephen Boyd and Yinyu Ye.

July 2007

CVXOPT: A Python Package for Convex Optimization — CVXOPT

CVXOPT is a free software package for convex optimization based on the Python programming language. It can be used with the interactive Python interpreter, on the command line by executing Python scripts, or integrated in other software via Python extension modules. Its main purpose is to make the development of software for convex optimization applications straightforward by building on Python's extensive standard library and on the strengths of Python as a high-level programming language.

August 2006

EvoGrid - Evolutionary Computation framework for Python in Launchpad

EvoGrid is a componentized framework based on the Zope3 interfaces / adapters system to build Evolutionary Algorithms (aka Genetic Algorithms) by pluging python components together.

Introducing the EvoGrid system

EvoGrid is a component-based python framework to build Evolutionary Computation-based Machine Learning algorithms sometime also known as Genetic Algorithms The EvoGrid design is inspired by the idea of "replicators" introduced by Richard Dawkins in his book The Selfish Gene. EvoGrid's replicators can evolve through both classical undirected darwinian evolution or through "intelligent" lamarckian evolution or by a combination of both. In this respect, EvoGrid can be considered a Memetic Computational framework.