awesome-repositories.com
المدونة
awesome-repositories.com

اكتشف أفضل مستودعات المصادر المفتوحة باستخدام بحث مدعوم بالذكاء الاصطناعي.

استكشفعمليات بحث منسقةبدائل مفتوحة المصدربرمجيات ذاتية الاستضافةالمدونةخريطة الموقع
المشروعحولكيفية ترتيب النتائجالصحافةخادم MCP
قانونيالخصوصيةالشروط
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

2 مستودعات

Awesome GitHub RepositoriesOptimization Objectives

Strategies for balancing multiple competing performance metrics during model training.

Distinct from GraphQL Performance Optimizers: Distinct from GraphQL performance optimizers: focuses on multi-objective hyperparameter tuning.

Explore 2 awesome GitHub repositories matching software engineering & architecture · Optimization Objectives. Refine with filters or upvote what's useful.

Awesome Optimization Objectives GitHub Repositories

اعثر على أفضل المستودعات باستخدام الذكاء الاصطناعي.سنبحث عن أفضل المستودعات المطابقة باستخدام الذكاء الاصطناعي.
  • optuna/optunaالصورة الرمزية لـ optuna

    optuna/optuna

    14,388عرض على GitHub↗

    Optuna is a Python-based hyperparameter optimization framework designed to automate the search for optimal machine learning model configurations. It functions as a Bayesian optimization library that systematically tests parameter combinations to maximize or minimize objective functions, streamlining the model development process through iterative evaluation. The project distinguishes itself through a define-by-run dynamic construction model, which allows users to build complex, conditional search spaces using standard programming logic. Its architecture is highly modular, featuring a pluggabl

    Finds optimal parameter sets that balance multiple competing performance metrics simultaneously during model training.

    Pythondistributedhyperparameter-optimizationmachine-learning
    عرض على GitHub↗14,388
  • penrose/penroseالصورة الرمزية لـ penrose

    penrose/penrose

    7,949عرض على GitHub↗

    Penrose is a compiler that transforms structured mathematical notation into optimized SVG diagrams. It uses a three-stage pipeline of separate domain, substance, and style files to define mathematical objects, relationships, and visual presentation, then solves continuous optimization problems with user-defined spatial constraints and objectives to automatically arrange diagram elements. The system separates diagram content from visual style using distinct declarative languages, and provides a typed domain language with subtype hierarchies for mathematical objects. It supports embedding compi

    Defines continuous objective functions encoding spatial relationships for diagram optimization.

    TypeScriptdiagramsdomain-specific-languagemathematics
    عرض على GitHub↗7,949
  1. Home
  2. Software Engineering & Architecture
  3. Performance and Reliability
  4. Performance Optimization
  5. GraphQL Performance Optimizers
  6. Optimization Objectives

استكشف الوسوم الفرعية

  • Spatial Objective FunctionsDefines continuous badness functions whose minima encode desired spatial relationships like repulsion. **Distinct from Optimization Objectives:** Distinct from Optimization Objectives: focuses on spatial layout objectives for diagrams, not model training hyperparameters.