Search Results for "multi-objective optimization"
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11 projects for "multi-objective optimization" with 2 filters applied:
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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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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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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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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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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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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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