Open Source Algorithms - Page 13

A branch-and-prune method to find all solutions to systems of nonlinear equations. The number of variables must equal the number of equations. The variables must have proper lower and upper bounds. The solver has an interface to the AMPL environment.

AVL Array is a sequence container (like std::vector or std::list) that allows fast insert/remove AND fast random access. Shiftable Files offers the usual file primitives plus fast insert/remove. Get the latest version via BZR in the Develop section.

This is a program for compute the dimension of the Hochschild homology k-vector spaces of a k-algebra A.

Active Learning is a Python-based research framework developed by Google for experimenting with and benchmarking various active learning algorithms. It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. The main experiment runner (run_experiment.py) supports a wide range of configurations, including batch sizes, dataset subsets, model selection, and data preprocessing options. It includes several established active learning strategies such as uncertainty sampling, k-center greedy selection, and bandit-based methods, while also allowing for custom algorithm implementations. The framework integrates with both classical machine learning models (SVM, logistic regression) and neural networks.

This is an Ada implementation of the Dancing Links X Algorithm as in Donald E. Knuth paper. AdaDLX is used to solve the Eight-Queens puzzle, Sudoku grids and Blocs in Box puzzle.

A Java implementation of a cubic B-spline curve smoothing function. Allows an arbitary number of points with a variable number of dimensions to have a cubic B-spline curve "fitted". Useful in finance for analysing bond or swap yield and discount curves.

Agenda desenvolvida em Java, utilizando banco PostGreSQL. Itens: Cadastro de Contatos Cadastro de Tarefas

A rudimentary 3D computer game that utilises artificial neural networks to enable computer agents to anticipate a target's location and shoot (bullets) in the corresponding direction.

Project description and support moved to : https://github.com/Zeus64/alcinoe However you can use the source you prefer, the SVN here or the GIT on github, both are synchronized (just that GIT don't support large file > 100 mo so some minor files used only as references are missing from GIT)

Aleph is both a multi-platform machine learning framework aimed at simplicity and performance, and a library of selected state-of-the-art algorithms.

AlgART Java libraries for processing arrays and matrices are open-source product, distributed under MIT license. So, anyone can use them for free without any restrictions. Main features: 63-bit addressing of array elements (64-bit long int indexes), memory model concept (allowing storing data in different schemes from RAM to mapped disk files), wide usage of lazy evaluations, built-in multithreading optimization for multi-core processors, wide set of image processing algorithms over matrices, etc. - please see at the site. Almost all classes and methods are thoroughly documented via JavaDoc (you may read full JavaDoc at the site).

--> Now available in English! Click "Browse All Files" to get it. <--- AlgDomes is a free, open source, educational application, designed to visually project and explain known algorithms in data structures. Designed & Created by: Konstantinos Kourmousis and Pavlos Paschalidis. ====================================== Η εφαρμογή AlgDomes είναι μια δωρεάν, ανοιχτού κώδικα εκπαιδευτική εφαρμογή οπτικοποίησης και επεξήγησης γνωστών αλγορίθμων σε δομές δεδομένων. Δημιουργήθηκε από τους Κουρμούση Κωνσταντίνο και Πασχαλίδη Παύλο, υπό την εποπτεία του Τομέα Υπολογιστικών Τεχνικών και Συστημάτων του Τμήματος Πληροφορικής του Τ.Ε.Ι. Σερρών, στα πλαίσια της πτυχιακής τους εργασίας.

This project is no longer supported. We are working on a new algorithmic trading platform with extreme fast execution speed and lots of cool features. Please visit http://www.algospace.com/ for more detail.

AlgoExplorer is a dynamic data structures viewer for Java. It allows the visualization of data structure of a Java program, allowing you to see how objects, handled by the algorithms, interact with each other and how they are related and linked. The project has been moved on: http://code.google.com/p/algoexplorer/

The Aim of this project is to provide a collection of reusable Algorithms which can be used effectively in different scenarios. Algorithm implementations are in Java. Objective here is to implement algorithms which should be more efficient than the JDK implementation and also to create a platform for the researchers who works on Data Mining, Encryption algorithms, ect.. to collaborate and contribute to this project.

An Algorithm Library written in .Net 2.0 which includes common algorithms.

The goal: to provide implementations of as many algorithms (sorting, searching, ...) and data structures (lists, trees, ...) as possible, accompanied by discussion of big O run time and memory limits and references to sources of further study.

An algorithm is represented by a .h file and placed under include. (one .header file per algorithm.) The demo program for the algorithm demonstration is placed under src. (one demo per algorithm.) After the program passes correctly, please initiate Pull Requests, the code is verified and stored in the library, and the new algorithm implementation is published in the README. TAB = 4 space. set ts=4 in vim. Graph output format is Graphviz Dot format. (the output format of the graph is in dot of graphviz.)

This will help a new data structure learner to learn data structures quickly.

This code is the translation into C++ of part of the Matlab code from Mark Veillette available at: http://www.mathworks.com/matlabcentral/fileexchange/37514-stbl--alpha-stable-distributions-for-matlab

AlphaTensor, developed by Google DeepMind, is the research codebase accompanying the 2022 Nature publication “Discovering faster matrix multiplication algorithms with reinforcement learning.” The project demonstrates how reinforcement learning can be used to automatically discover efficient algorithms for matrix multiplication — a fundamental operation in computer science and numerical computation. The repository is organized into four main components: algorithms, benchmarking, nonequivalence, and recombination. These contain implementations of the discovered matrix multiplication algorithms, tools to benchmark their real-world performance, proofs of nonequivalence among thousands of solutions, and methods for decomposing larger problems into smaller factorizations. Users can explore AlphaTensor’s discovered algorithms interactively using Colab notebooks or Python scripts.

A .Net library coded in C# language that inplements some sort of functions I found useful.

The Gene Expression Programming Framework in Java. It separates the process of evolution from the process of interpretation of the chromosome, allowing the use of various schemes in the chromosome.

A complete library of high-speed java collection classes to complement existing classes with new and advanced algorithms. Complements standard J2SE classes and Jakarta commons classes

AIS is an Development Platform providing a high-speed JIT compiler for LISP and JavaScript, web server, object repositories, MySQL integration and libraries supporting a wide variety of advanced genetic programming and symbolic regression techniques.