Search Results for "algorithm" - Page 5
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Showing 339 open source projects for "algorithm"
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clzw
Implementation of LZW compression algorithm in C
Simple, fast implementation of LZW (Lempel–Ziv–Welch) data compression algorithm in C. - Console encoder/decoder tools - OS independent - Could be used in embedded projects - Works with raw code-stream LZW features: - Hardcoded dictionary size - Variable code size - Code search is performed by hash table and embedded in dictionary linked lists (encoder) - No dynamic memory allocation -
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Base62 Encode/Decode Utility
A tool for encoding/decoding to base62
...the base62 program has been written to encode/decode files into this format. The syntax is similar to the popular base64 command line program. Inside the package there is a working c++ version of the base62 algorithm. the sources are inside the package. Note that from release 2.0.0 the algorithm is different from the one used before. If you have coded a file using base62 < 2.0.0 DO NOT USE base62 >= 2.0.0 to decode it. The 2.0.1 release has a new algorithm for chew, we have a compat flag -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
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Supervised Reptile
Code for the paper "On First-Order Meta-Learning Algorithms"
...Because Reptile is a first-order algorithm, it avoids computing second derivatives or full meta-gradients, making it computationally simpler while retaining good performance. The repo includes training scripts, dataset fetchers (Omniglot, Mini-ImageNet), and modules for defining the Reptile update logic, variables, and hyperparameters. -
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shadowsocks-libev
Bug-fix-only libev port of shadowsocks
Shadowsocks-libev is a lightweight secured SOCKS5 proxy for embedded devices and low-end boxes. Shadowsocks-libev is written in pure C and depends on libev. It's designed to be a lightweight implementation of shadowsocks protocol, in order to keep the resource usage as low as possible. Snap is the recommended way to install the latest binaries. You can build shadowsocks-libev and all its dependencies by script. The latest shadowsocks-libev has provided a redir mode. You can configure your... -
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HungarianAlgorithm
An Ada implementation of the Hungarian Algorithm to minimize cost
The Hungarian algorithm can be described as optimally solving a workers versus jobs assignment problem that minimizes total cost. This implementation assumes a square cost matrix, i.e. the number of jobs equals the number of workers to do them. -
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Smart Algorithm
Repository implementing a variety of intelligent algorithms
Smart-Algorithm is a repository implementing a variety of intelligent / metaheuristic optimization algorithms (e.g. Genetic Algorithm, Ant Colony, Particle Swarm, Immune Algorithm). The implementations are provided in multiple languages (Java, Python, MATLAB). The repository’s aim is to offer reference implementations of “smart” algorithms for tasks like route planning, optimization, or algorithm learning. -
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Machine Learning Octave
MatLab/Octave examples of popular machine learning algorithms
This repository contains MATLAB / Octave implementations of popular machine learning algorithms, along with explanatory code and mathematical derivations, intended as educational material rather than production code. Implementations of supervised learning algorithms (linear regression, logistic regression, neural nets). The author’s goal is to help users understand how each algorithm works “from scratch,” avoiding black-box library calls. Code written so as to expose and comment on mathematical steps. The repository includes clustering, regression, classification, neural networks, anomaly detection, and other standard ML topics. Does not rely heavily on specialized toolboxes or library shortcuts. -
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Jobber
An alternative to cron, with sophisticated status-reporting
...Sophisticated error handling: you can control whether and when a job is run again after it fails. For example, after an initial failure of a job, Jobber can schedule future runs using an exponential backoff algorithm. Sophisticated error reporting: you can control whether Jobber notifies you about each failed run, or only about jobs that have been disabled due to repeated failures. -
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java-string-similarity
Implementation of various string similarity and distance algorithms
...This was published by Masek in 1980 ("A Faster Algorithm Computing String Edit Distances"). -
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SwiftOCR
Fast and simple OCR library written in Swift
SwiftOCR is a fast and simple OCR library written in Swift. It uses a neural network for image recognition. As of now, SwiftOCR is optimized for recognizing short, one-line long alphanumeric codes (e.g. DI4C9CM). We currently support iOS and OS X. If you want to recognize normal text like a poem or a news article, go with Tesseract, but if you want to recognize short, alphanumeric codes (e.g. gift cards), I would advise you to choose SwiftOCR because that's where it exceeds. Tesseract is... -
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MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in cooperative, competitive, and mixed settings. The code is built on top of TensorFlow and integrates with the Multiagent Particle Environments (MPE) for benchmarking. ... -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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Carbon library
A declarative library for building component-based user interfaces
A declarative library for building component-based user interfaces in UITableView and UICollectionView. Provides a declarative design with the power of diffing algorithm for building list UIs. Declare the component once, it can be reused regardless kind of the list element. Solves the various problems by architecture and algorithm without destructing UIKit. Carbon is a library for building component-based user interfaces in UITableView and UICollectionView inspired by SwiftUI and React. This make it painless to build and maintain the complex UIs. ... -
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Zopfli
Zopfli Compression Algorithm is a compression library
Zopfli is a compression library and command-line tool that produces exceptionally small DEFLATE, zlib, and gzip streams by spending more CPU time to search for better encodings. It keeps strict compatibility with the ubiquitous DEFLATE format, so outputs can be decompressed by any standard tool or browser. The encoder performs exhaustive block splitting and greedy but thorough match searching to shave extra bytes off assets, which is ideal for web content and firmware where size matters more... -
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AES Everywhere
Cross Language AES 256 Encryption Library
AES Everywhere is Cross Language Encryption Library that provides the ability to encrypt and decrypt data using a single algorithm in different programming languages and on different platforms. This is an implementation of the AES algorithm, specifically CBC mode, with 256-bit key length and PKCS7 padding. It implements OpenSSL-compatible cryptography with randomly generated salt. -
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benchm-ml
A benchmark of commonly used open source implementations
...The benchmarks cover algorithms like logistic regression, random forest, gradient boosting, and deep neural networks, and they compare across toolkits such as scikit-learn, R packages, xgboost, H2O, Spark MLlib, etc. The repository is structured in logical folders, each corresponding to algorithm categories. -
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Hyperapp
Tiny framework for building hypertext applications
...Write what, not how—With a declarative API that's easy to read and fun to write, Hyperapp is the best way to build purely functional, feature-rich, browser-based apps in JavaScript. Smaller than a favicon—1 kB, give or take. Hyperapp is an ultra-lightweight Virtual DOM, highly-optimized diff algorithm, and state management library obsessed with minimalism. Official packages provide access to The Web Platform, and ensure that the APIs are exposed in a way that makes sense for Hyperapp, and the underlying code is stable. We already cover a decent amount of features, but you can always create your own effects and subscriptions if something is not available yet. -
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Coach
Enables easy experimentation with state of the art algorithms
Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments... -
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Dep
Go dependency management tool experiment
Dep was an official experiment to implement a package manager for Go. While dep has many discrete components and moving parts, all of these parts revolve around a central model. Dep is a tool intended primarily for use by developers, to support the work of actually writing and shipping code. It is not intended for end users who are installing Go software - that's what go get does. It is strongly recommended that you use a released version of dep. While tip is never purposefully broken, its... -
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Javaluator
A java infix evaluator based on "Shunting Yard" algorithm.
Evaluate an arithmetic expression is as simple as: Double result = new DoubleEvaluator().evaluate("(e^3-1)*sin(pi/4)*ln(pi^2)"). But Javaluator provides you with much more ... Key features: - Functions support, including variable argument count. - Constants support: e, pi, etc ... - Variables support: Example sin(x) for x = pi/4. - Highly configurable: Reduce the built-in operator or function sets, define your own brackets. - Extensible: Define your own grammar, or extends the... -
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Active Learning
Framework and examples for active learning with machine learning model
...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. -
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This is a recursive C++ source code of the Fast Fourier Transform algorithm allowing parallelization. Also a performance test and its results on my computer are provided. The Performance test suggest to use 4 threads for parallelization. With this one can beat the implementation in "Numerical Recipes in C++" for large signals with more than 2^16 / 2^17 / 2^18 samples depending on the hardware and software.
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mssolver
Automatic solver of a minesweeper game
This is an automatic algorithm, which solves a minesweeper game field -
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OpenDino
Open Source Java platform for Optimization, DoE, and Learning.
...It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing other programs (solvers) - parallel execution of problems - distributed execution of problems via socket connection between computers Others: - data storage - data analyser and viewer
