Search Results for "yaffs2-source"
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Showing 1445 open source projects for "yaffs2-source"
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LZ4
Extremely fast compression algorithm
...It features an extremely fast decoder, with speed in multiple GB/s per core (~1 Byte/cycle). A high compression derivative, called LZ4_HC, is available, trading customizable CPU time for compression ratio. LZ4 library is provided as open-source software using a BSD license. This benchmark simulates simple "static content transfer" scenario such as OS Kernel compression or video game's static assets (text/images/tables/scripts/etc) which loading from Flash Memory / HDD / SSD. In this case, compression time is completely ignored. Because only content developers compress the data at once and usually they don't care about its computational cost. ... -
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Zstandard
Zstandard - Fast real-time compression algorithm
...The reference library offers a very wide range of speed / compression trade-off, and is backed by an extremely fast decoder (see benchmarks below). Zstandard library is provided as open source software using a BSD license. Its format is stable and published as IETF RFC 8478. The negative compression levels, specified with --fast=#, offer faster compression and decompression speed in exchange for some loss in compression ratio compared to level 1, as seen in the table above. Zstd can trade compression speed for stronger compression ratios. ... -
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PlatEMO
Evolutionary multi-objective optimization platform
Evolutionary multi-objective optimization platform. PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. Most of them are representative algorithms... -
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++) and optimized for highly distributed computing environments. This makes them hardly accessible for students, researchers and hackers. Many simple Python implementations can be found on Github, but none of them is able to beat a reasonable baseline on games such as Othello or Connect Four. ... -
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Swift Algorithms
Commonly used sequence and collection algorithms for Swift
Swift Algorithms is an open-source package of sequence and collection algorithms, along with their related types. Algorithms are powerful tools for thought because they encapsulate difficult-to-read and error-prone raw loops. The Algorithms package includes a host of powerful, generic algorithms frequently found in other popular programming languages. We hope this new package will help people embrace algorithms, improving the correctness and performance of their code. -
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X's Recommendation Algorithm
Source code for the X Recommendation Algorithm
The Algorithm is Twitter’s open source release of the core ranking system that powers the platform’s home timeline. It provides transparency into how tweets are selected, prioritized, and surfaced to users, reflecting Twitter’s move toward openness in recommendation algorithms. The repository contains the recommendation pipeline, which incorporates signals such as engagement, relevance, and content features, and demonstrates how they combine to form ranked outputs. -
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Exclusively Dark Image Dataset
ExDARK dataset is the largest collection of low-light images
...It has been widely used in studies of low-light image enhancement, deep learning approaches, and domain adaptation for vision models. Researchers can also explore its associated source code for low-light image enhancement tasks, making it an essential resource for advancing work in night-time and low-light visual recognition. -
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The Algorithms Python
All Algorithms implemented in Python
The Algorithms-Python project is a comprehensive collection of Python implementations for a wide range of algorithms and data structures. It serves primarily as an educational resource for learners and developers who want to understand how algorithms work under the hood. Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting,... -
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TBOX
A glib-like multi-platform c library
...The project focuses on making C development easier and provides many modules (.e.g stream, coroutine, regex, container, algorithm ...), so that any developer can quickly pick it up and enjoy the productivity boost when developing in C language. It supports the following platforms: Windows, Macosx, Linux, Android, iOS, BSD and etc. Supports file, data, http and socket source. Supports the stream filter for gzip, charset. etc. Implements stream transfer. Implements the static buffer stream for parsing data. Supports coroutine and implements asynchronous operation. The coroutine library. Provides high-performance coroutine switch. Supports arm, arm64, x86, x86_64. Provides channel interfaces. Provides semaphore and lock interfaces. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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C# Algorithms
Plug-and-play class-library project of standard data structures
A plug-and-play class-library project of standard Data Structures and Algorithms, written in C#. It contains 75+ Data Structures and Algorithms, designed as Object-Oriented isolated components. Even though this project started for educational purposes, the implemented Data Structures and Algorithms are standard, efficient, stable and tested. This is a C#.NET solution-project, and it contains three subprojects. Algorithms, a class library project which contains the Algorithms implementations.... -
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YAPF
A formatter for Python files
YAPF is a Python code formatter that automatically rewrites source to match a chosen style, using a clang-format–inspired algorithm to search for the “best” layout under your rules. Instead of relying on a fixed set of heuristics, it explores formatting decisions and chooses the lowest-cost result, aiming to produce code a human would write when following a style guide. You can run it as a command-line tool or call it as a library via FormatCode / FormatFile, making it easy to embed in editors, CI, and custom tooling. ... -
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Swift Algorithm Club
Algorithms and data structures in Swift, with explanations
Swift Algorithm Club is a project that implements a broad collection of algorithms and data structures in the Swift programming language, with clear commentary and educational intent. Its purpose is not primarily to be a utility library, but rather to teach the how and why behind algorithms—readers can study implementations, complexity, and design choices in a Swift context. The repository includes common classic algorithms (sorting, searching, trees, graphs, dynamic programming, etc.) and... -
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trackers
Multi-object tracking algorithms
trackers is a plug-and-play multi-object tracking library designed to work with virtually any object detection model, enabling developers to follow objects across video frames with minimal setup. The library provides clean, modular implementations of leading tracking algorithms and can be used either from the command line or embedded directly into Python pipelines. It supports inputs such as videos, webcams, RTSP streams, or image directories and produces annotated tracking outputs that... -
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DomainBed
DomainBed is a suite to test domain generalization algorithms
DomainBed is a PyTorch-based research suite created by Facebook Research for benchmarking and evaluating domain generalization algorithms. It provides a unified framework for comparing methods that aim to train models capable of performing well across unseen domains, as introduced in the paper In Search of Lost Domain Generalization. The library includes a wide range of well-known domain generalization algorithms, from classical baselines such as Empirical Risk Minimization (ERM) and... -
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OpenSpiel
Environments and algorithms for research in general reinforcement
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. OpenSpiel supports n-player (single- and multi- agent) zero-sum, cooperative and general-sum, one-shot and sequential, strictly turn-taking and simultaneous-move, perfect and imperfect information games, as well as traditional multiagent environments such as (partially- and fully- observable) grid worlds and social dilemmas. OpenSpiel also includes tools to... -
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JCTools
Java Concurrency Tools for the JVM
Java Concurrency Tools for the JVM. This project aims to offer some concurrent data structures currently missing from the JDK. There’s more to come and contributions/suggestions are most welcome. JCTools has enjoyed support from the community and contributions in the form of issues/tests/documentation/code have helped it grow. JCTools offers excellent performance at a reasonable price (FREE! under the Apache 2.0 License). It’s stable and in use by such distinguished frameworks as Netty,... -
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FATE
An industrial grade federated learning framework
...FATE became open-source in February 2019. FATE TSC was established to lead FATE open-source community, with members from major domestic cloud computing and financial service enterprises. FedAI is a community that helps businesses and organizations build AI models effectively and collaboratively, by using data in accordance with user privacy protection, data security, data confidentiality and government regulations. -
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PRML
PRML algorithms implemented in Python
PRML repository is a respected and well-maintained project that implements the foundational algorithms from the famous textbook Pattern Recognition and Machine Learning by Christopher M. Bishop, providing a practical and accessible Python reference for both students and professionals. Rather than just summarizing concepts, the repository includes working code that demonstrates linear regression and classification, kernel methods, neural networks, graphical models, mixture models with EM... -
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Flatbush
A very fast static spatial index for 2D points and rectangles in JS
A really fast static spatial index for 2D points and rectangles in JavaScript. An efficient implementation of the packed Hilbert R-tree algorithm. Enables fast spatial queries on a very large number of objects (e.g. millions), which is very useful in maps, data visualizations and computational geometry algorithms. -
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Rubix ML
A high-level machine learning and deep learning library for PHP
Rubix ML is a free open-source machine learning (ML) library that allows you to build programs that learn from your data using the PHP language. We provide tools for the entire machine learning life cycle from ETL to training, cross-validation, and production with over 40 supervised and unsupervised learning algorithms. In addition, we provide tutorials and other educational content to help you get started using ML in your projects. -
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X For You Feed Algorithm
Algorithm powering the For You feed on X
X For You Feed Algorithm is the open-sourced core recommendation system that powers the For You feed on X (the social network formerly known as Twitter), and it represents one of the first times a major social platform has published production-level ranking code for public review and experimentation. The repository contains the full pipeline that ingests user engagement and content candidate data, processes it through retrieval, hydration, filtering, scoring, and selection layers, and... -
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DualPipe
A bidirectional pipeline parallelism algorithm
DualPipe is a bidirectional pipeline parallelism algorithm open-sourced by DeepSeek, introduced in their DeepSeek-V3 technical framework. The main goal of DualPipe is to maximize overlap between computation and communication phases during distributed training, thus reducing idle GPU time (i.e. “pipeline bubbles”) and improving cluster efficiency. Traditional pipeline parallelism methods (e.g. 1F1B or staggered pipelining) leave gaps because forward and backward phases can’t fully overlap... -
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Interpolations.jl
Fast, continuous interpolation of discrete datasets in Julia
This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time. -
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TextDistance
Compute distance between sequences
Python library for comparing the distance between two or more sequences by many algorithms. For main algorithms, text distance try to call known external libraries (fastest first) if available (installed in your system) and possible (this implementation can compare this type of sequences). Install text distance with extras for this feature. Textdistance use benchmark results for algorithm optimization and try to call the fastest external lib first (if possible). TextDistance show benchmarks... -
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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...