Search Results for "multi-objective optimization"
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Showing 17 open source projects for "multi-objective optimization"
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BayesianOptimization
A Python implementation of global optimization with gaussian processes
BayesianOptimization is a Python library that helps find the maximum (or minimum) of expensive or unknown objective functions using Bayesian optimization. This technique is especially useful for hyperparameter tuning in machine learning, where evaluating the objective function is costly. The library provides an easy-to-use API for defining bounds and optimizing over parameter spaces using probabilistic models like Gaussian Processes. -
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DeepSeed
Deep learning optimization library making distributed training easy
...With just a single GPU, ZeRO-Offload of DeepSpeed can train models with over 10B parameters, 10x bigger than the state of arts, democratizing multi-billion-parameter model training such that many deep learning scientists can explore bigger and better models. Sparse attention of DeepSpeed powers an order-of-magnitude longer input sequence and obtains up to 6x faster execution comparing with dense transformers. -
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XZ Utils
Open-source compression utility and library
...The project is known for delivering strong compression performance while maintaining reasonable memory usage, making it suitable for software distribution, backups, and archival workflows. xz is commonly included in Unix-like operating systems and is often used as a standard packaging format in Linux ecosystems. The toolkit supports streaming, multi-threaded operation, and integrity checking to ensure reliable data handling. Overall, xz serves as a foundational compression technology for modern open-source software distribution and storage optimization. -
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rtabmap
RTAB-Map library and standalone application
RTAB-Map (Real-Time Appearance-Based Mapping) is a RGB-D, Stereo and Lidar Graph-Based SLAM approach based on an incremental appearance-based loop closure detector. The loop closure detector uses a bag-of-words approach to determine how likely a new image comes from a previous location or a new location. When a loop closure hypothesis is accepted, a new constraint is added to the map’s graph, then a graph optimizer minimizes the errors in the map. A memory management approach is used to... -
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5
TBOX
A glib-like multi-platform c library
TBOX is a glib-like cross-platform C library that is simple to use yet powerful in nature. 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... -
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BentoCache
Bentocache is a robust multi-tier caching library for Node.js app
Bentocache is a flexible caching library for Python that supports multiple backends like memory, disk, and Redis. It offers decorators for easy function-level caching and is designed to be lightweight, extensible, and developer-friendly. Bentocache is well-suited for performance optimization in web apps, scripts, and data pipelines. -
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Tunix
A JAX-native LLM Post-Training Library
Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation, letting practitioners swap components without rewriting the whole stack. Examples and reference configs demonstrate end-to-end runs for common model families, helping teams reproduce baselines before customizing. ... -
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DeepXDE
A library for scientific machine learning & physics-informed learning
...NN-arbitrary polynomial chaos (NN-aPC): solving forward/inverse stochastic PDEs (sPDEs) [J. Comput. Phys.] PINN with hard constraints (hPINN): solving inverse design/topology optimization [SIAM J. Sci. Comput.] Residual-based adaptive sampling [SIAM Rev., arXiv] Gradient-enhanced PINN (gPINN) [Comput. Methods Appl. Mech. Eng.] PINN with multi-scale Fourier features [Comput. Methods Appl. Mech. Eng.] -
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cuDF
GPU DataFrame Library
Built based on the Apache Arrow columnar memory format, cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data. cuDF provides a pandas-like API that will be familiar to data engineers & data scientists, so they can use it to easily accelerate their workflows without going into the details of CUDA programming. For additional examples, browse our complete API documentation, or check out our more detailed notebooks. cuDF can be installed... -
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warp-yg
Warp multi-function one-click script, supports warp-go and wgcf
warp-yg is a script-based toolkit designed to automate the deployment and optimization of Cloudflare WARP networking configurations for enhanced privacy and performance. It focuses on simplifying the integration of WireGuard-based WARP connections into proxy environments, allowing users to route traffic through optimized Cloudflare endpoints. The project includes functionality for selecting optimal endpoints and improving connection speed by dynamically identifying efficient routes. It is... -
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EKS Best Practices
A best practices guide for day 2 operations
...Rather than a code library, it serves as a reference catalogue of patterns, anti-patterns, checklists and architectures across domains such as security, reliability, scalability, networking, cost optimization and hybrid cloud deployments. The repository is maintained by AWS but open to contributions from the community, making it a living document that evolves as Kubernetes and AWS features evolve. Each section dives into operational details—for example, how to manage IAM roles for service accounts, secure the EKS endpoint, handle node auto-scaling, and design for multi-AZ resilience. ... -
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Hasktorch
Tensors and neural networks in Haskell
Hasktorch is a powerful Haskell library for tensor computation and neural network modeling, built on top of libtorch (the backend of PyTorch). It brings differentiable programming, automatic differentiation, and efficient tensor operations into Haskell’s strongly typed functional paradigm. This project is in active development, so expect changes to the library API as it evolves. We would like to invite new users to join our Hasktorch discord space for questions and discussions.... -
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Browser diet
The definitive front-end performance guide
Browser diet is a community-driven front-end performance guide presented as a fun, colorful website that explains how to make web pages faster and “lighter.” It collects advice from experienced front-end developers and organizes it into practical sections covering HTML, CSS, JavaScript, images, server configuration, and general best practices. The project was built as a static site powered by DocPad, with content written in Markdown and translated into multiple languages, making it... -
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iOS Tech Frontier
Tanslates high-quality iOS technology, open source libraries
...Instead of simple how-to recipes, the project collects detailed explanations, system internals analyses, and real-world insights into core subsystems like memory management (ARC), threading and Grand Central Dispatch, Objective-C/Swift runtime behavior, UIKit rendering pipelines, and effective use of concurrency. It also covers architectural and performance topics such as dynamic layout optimization, view lifecycle subtleties, Swift language pitfalls, and integration with low-level APIs such as Metal or CoreAnimation. By aggregating authoritative references, experiments, and code snippets, the guide helps developers reason through tradeoffs, debug subtle issues, and architect large-scale iOS systems. -
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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AlgART Java Libraries
Open source library for processing arrays and matrices
...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). -
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Single header, templatized epxression tree. Assign functors to branches and values to leaves, then call evaluate(). Requires C++11's function<T>. Optional multi-threaded evaluation is dependent on header <future>.
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