Optimization problems[ edit ] In a genetic algorithm, a population of candidate solutions called individuals, creatures, or phenotypes to an optimization problem is evolved toward better solutions. Each candidate solution has a set of properties its chromosomes or genotype which can be mutated and altered; traditionally, solutions are represented in binary as strings of 0s and 1s, but other encodings are also possible.
Generally, these are sites and files I have seen mentioned on comp. My selection is pretty random and certainly doesn't cover everything. In particular, I haven't tried to include everything already included in other people's lists of libraries.
It is becoming less and less possible to do justice to the vast amount of material out there and I have given up trying to update the links so don't forget the search engines: For the rest of my web site go to http: Msdos uncompressors can be found under compression or archivers in the msdos program archives.
Use uncompress or gzip -d on unix machines to uncompress.
Compressed files should be downloaded in binary mode; text files in ascii mode. Shiva's site links, book recommendations etc http: Rules and Recommendations http: Here is a list of publications and tools to browse through: Commercial product with free trial.
Includes stl and ANSI-like string class now out of date ftp: Make ODBC recordsets look like an STL container; move through our containers using standard STL iterators; and if you inserterase or replace records in our containers changes are automatically committed to the database.
Barton and Lee R. Reingold's Calendar Papers and Code http: This seems to have vanished - they're back! Linear algebra and arrays. A full-featured class library for MPI. Message passing interface for parallel processors http: Expect Linux version soon. Javadoc-like documentation tool; other development tools http: Fully functional 15 day trial is available for download http:Gaussian Processes and Kernel Methods Gaussian processes are non-parametric distributions useful for doing Bayesian inference and learning on unknown functions.
They can be used for non-linear regression, time-series modelling, classification, and many other problems.
A genetic algorithm (GA) is a method for solving both constrained and unconstrained optimization problems based on a natural selection process that mimics biological evolution.
The algorithm repeatedly modifies a population of individual solutions. JuliaCon Berkeley, CA. Over the last few years we have seen Deep Learning rise to prominence not just in academia with state-of-the-art results for well-established tasks, but also in industry to leverage an ever-increasing amount of data becoming available.
The post defines the peak to average power ratio (PAPR) and using matlab/octave script, computes the cumulative distribuition function (CDF) of PAPR for a specification. In this post, we take a tour of the most popular machine learning algorithms. It is useful to tour the main algorithms in the field to get a feeling of what methods are available.
There are so many algorithms available that it can feel overwhelming when algorithm names are thrown around and you are.
What is SCIP? A similar technique is used for solving both Integer Programs and Constraint Programs: the problem is successively divided into smaller subproblems (branching) that are solved recursively.