Search Results for "multi-objective optimization" - Page 5

Showing 169 open source projects for "multi-objective optimization"

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  • 1
    Selefra

    Selefra

    The open-source policy-as-code software that provides analysis

    Selefra is an open-source policy-as-code and infrastructure analysis tool that helps engineering and security teams gain visibility into complex multi-cloud and SaaS environments by treating infrastructure data as queryable information. The core idea behind Selefra is “select * from infrastructure,” meaning you can write flexible SQL-style queries against cloud configuration and inventory data assembled from dozens of services such as AWS, Azure, GCP, Kubernetes, GitHub, Slack, and more, bringing auditing, security, compliance, cost optimization, and architecture insights into one place. ...
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  • 2
    TensorFlow Ranking

    TensorFlow Ranking

    Learning to rank in TensorFlow

    ...Commonly used loss functions including pointwise, pairwise, and listwise losses. Commonly used ranking metrics like Mean Reciprocal Rank (MRR) and Normalized Discounted Cumulative Gain (NDCG). Multi-item (also known as groupwise) scoring functions. LambdaLoss implementation for direct ranking metric optimization. Unbiased Learning-to-Rank from biased feedback data. We envision that this library will provide a convenient open platform for hosting and advancing state-of-the-art ranking models based on deep learning techniques, and thus facilitate both academic research and industrial applications. ...
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  • 3
    FasterTransformer

    FasterTransformer

    Transformer related optimization, including BERT, GPT

    FasterTransformer is a high-performance inference library designed to accelerate transformer-based models such as BERT, GPT, and T5 on NVIDIA GPUs. It provides optimized implementations of transformer encoder and decoder layers using CUDA, cuBLAS, and custom kernels to maximize throughput and minimize latency. The library supports multiple deep learning frameworks, including TensorFlow, PyTorch, and Triton, allowing developers to integrate it into existing pipelines without major changes. It...
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  • 4
    GeneticSharp

    GeneticSharp

    GeneticSharp is a fast, extensible, multi-platform and multithreading

    GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs). Can be used in any kind of .NET 6, .NET Standard and .NET Framework apps, like ASP .NET MVC, ASP .NET Core, Blazor, Web Forms, UWP, Windows Forms, GTK#, Xamarin, MAUI and Unity3D games. GeneticSharp and extensions (TSP, AutoConfig, Bitmap equality, Equality equation, Equation solver, Function builder, etc). A Blazor...
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  • 5
    EnCodec

    EnCodec

    State-of-the-art deep learning based audio codec

    Encodec is a neural audio codec developed by Meta for high-fidelity, low-bitrate audio compression using end-to-end deep learning. Unlike traditional codecs (like MP3 or Opus), Encodec uses a learned quantizer and decoder to reconstruct complex waveforms with remarkable accuracy at bitrates as low as 1.5 kbps. It employs a convolutional encoder–decoder architecture trained with perceptual loss functions that optimize for human auditory quality rather than raw waveform distance. The model can...
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  • 6
    Bullet Physics SDK

    Bullet Physics SDK

    Real-time collision detection and multi-physics simulation for VR

    This is the official C++ source code repository of the Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc. We are developing a new differentiable simulator for robotics learning, called Tiny Differentiable Simulator, or TDS. The simulator allows for hybrid simulation with neural networks. It allows different automatic differentiation backends, for forward and reverse mode gradients.
    Downloads: 3 This Week
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  • 7
    Auto-PyTorch

    Auto-PyTorch

    Automatic architecture search and hyperparameter optimization

    While early AutoML frameworks focused on optimizing traditional ML pipelines and their hyperparameters, another trend in AutoML is to focus on neural architecture search. To bring the best of these two worlds together, we developed Auto-PyTorch, which jointly and robustly optimizes the network architecture and the training hyperparameters to enable fully automated deep learning (AutoDL). Auto-PyTorch is mainly developed to support tabular data (classification, regression) and time series...
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  • 8
    Mycat2

    Mycat2

    MySQL Proxy using Java NIO based on Sharding SQL, Calcite

    Open source intermediate for the MySQL database network protocol written in Java language, open source of GPLv3 protocol. Custom Calcite distributed query engine, edit SQL to relationship algebra expression, rule optimization engine, and cost optimization engine, generate physical execution plan, support logic view. Any cross-currant cross-table join query, support cross-currant cross-table non-associated query, support cross-currant cross-table association query, support cross-currant...
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  • 9
    Apache MXNet (incubating)

    Apache MXNet (incubating)

    A flexible and efficient library for deep learning

    Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable.
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  • 10
    Fecshop (Yii2 Fecshop)

    Fecshop (Yii2 Fecshop)

    yii2 (PHP) fecmal (fecshop) core code used for ecommerce shop

    Yii2 Fecshop is an open-source e-commerce application built on the Yii2 framework. It is designed to provide a complete solution for building scalable and customizable online stores. Fecshop offers features like multi-language support, multi-currency options, SEO optimization, and integration with third-party payment gateways. The modular architecture makes it flexible, allowing developers to extend and customize the store as needed.
    Downloads: 0 This Week
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  • 11
    Cuda Simulated Annealing GPU Route Plan

    Cuda Simulated Annealing GPU Route Plan

    An Optimized GPU-Accelerated Route Planning of Multi-UAV Systems Using

    ...In addition to this, parallel programming approaches increase the computation performance. Therefore, this study focuses to discuss and solve the route planning problem for multi-UAV systems by using optimization techniques based on an evolutionary algorithm: simulated annealing. The travel cost and execution time are downsized in this work by optimization on algorithm and code. We implemented CPU based parallel solution to compare results with the GPU-accelerated one. The efficiency and the effectiveness of our parallelized and optimized solution
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  • 12
    Tweety
    ...In particular, it provides a general interface layer for doing research and working with different knowledge representation formalisms such as classical logics, conditional logics, probabilistic logics, and argumentation. Furthermore, Tweety contains libraries for dealing with agents, multi-agent systems, and dialog systems for agents, as well as belief revision, preference reasoning, preference aggregation, and action languages. A series of utility libraries that deal with e.g. mathematical optimization complement the collection.
    Downloads: 1 This Week
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  • 13
    NoisePage

    NoisePage

    Self-Driving Database Management System

    NoisePage is a relational database management system (DBMS) designed from the ground up for autonomous deployment. It uses integrated machine learning components to control its configuration, optimization, and tuning. The system will support automated physical database design (e.g., indexes, materialized views, sharding), knob configuration tuning, SQL tuning, and hardware capacity/scaling. Our research focuses on building the system components that support such self-driving operations with...
    Downloads: 0 This Week
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  • 14
    DeText

    DeText

    A Deep Neural Text Understanding Framework

    DeText is a Deep Text understanding framework for NLP-related ranking, classification, and language generation tasks. It leverages semantic matching using deep neural networks to understand member intents in search and recommender systems. As a general NLP framework, DeText can be applied to many tasks, including search & recommendation ranking, multi-class classification and query understanding tasks.
    Downloads: 0 This Week
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  • 15
    Browser diet

    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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  • 16
    Coach

    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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  • 17
    ELF (Extensive Lightweight Framework)

    ELF (Extensive Lightweight Framework)

    An End-To-End, Lightweight and Flexible Platform for Game Research

    ELF (Extensive, Lightweight, and Flexible) is a high-performance platform for reinforcement learning research that unifies simulation, data collection, and distributed training. A C++ core provides fast environments and concurrent actors, while Python bindings expose simple APIs for agents, replay, and optimization loops. It supports both single-agent and multi-agent settings, with batched stepping and shared-memory queues that keep GPUs saturated during training. ELF introduced widely used reference systems, most notably ELF OpenGo, demonstrating at-scale self-play with strong analysis tooling and public checkpoints. Its design emphasizes reproducibility: deterministic seeds, logging, and evaluation harnesses make large-scale experiments trackable and comparable. ...
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  • 18
    The Crux

    The Crux

    Experimental data modelling and simulation

    Parameter optimization program with objective functions for the quantitative estimation of biochemical/biophysical reaction parameters (equilibrium and rate constants, etc.)
    Downloads: 0 This Week
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  • 19
    archer

    archer

    An automated SQL operation platform based on inception

    An automated SQL operation platform based on inception, supports functions such as work order, audit, scheduled task, email, OSC, etc., and can also configure MySQL query, slow query management, session management, etc. Initiate SQL launch, submit work orders, and automatically audit by inception. After the audit is passed, manual audit by the auditor is required. The rollback statement can be displayed in the work order, and it supports one-click submission of rollback work orders. Query...
    Downloads: 0 This Week
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  • 20

    mdoptcli

    Multidimensional Optimizer for Command Line

    This program is a command-line interface to several multi-dimensional optimization algorithms coded in the *GNU Scientific Library -- GSL*. Namely the *Simplex* algorithm, which does not need a gradient, and from the gradient-based algorithms the *Conjugate Gradient -- CG* and the *Broyden-Fletcher-Goldfarb-Shanno -- BFGS* methods. The energy (and possibly energy gradient) is evaluated by a given command, which has to accept coordinates on standard input and returns the appropriate energy (or gradient) on standard output.
    Downloads: 0 This Week
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  • 21

    popt4jlib

    Parallel Optimization Library for Java

    popt4jlib is an open-source parallel optimization library for the Java programming language supporting both shared memory and distributed message passing models. Implements a number of meta-heuristic algorithms for Non-Linear Programming, including Genetic Algorithms, Differential Evolution, Evolutionary Algorithms, Simulated Annealing, Particle Swarm Optimization, Firefly Algorithm, Monte-Carlo Search, Local Search algorithms, Gradient-Descent-based algorithms, as well as some well-known network flow and other graph algorithms. ...
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  • 22
    JPFPSStatus

    JPFPSStatus

    Show FPS Status on StatusBar

    JPFPSStatus is a simple and lightweight tool that displays the frames per second (FPS) of an iOS app in real-time. Designed for performance debugging and optimization, it provides a floating overlay that shows the current FPS, helping developers monitor app responsiveness and rendering performance.
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  • 23

    GA-tools

    general genetic algorithms optimization fortran 95 routines

    High level optimization routines in Fortran 95 for optimization problems using a genetic algorithm with elitism, steady-state-reproduction, dynamic operator scoring by merit, no-duplicates-in-population. Chromosome representation may be integer-array, real-array, permutation-array, character-array. Single objective and multi-objective maximization routines are present.
    Downloads: 5 This Week
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  • 24
    jMetal
    jMetal is an object-oriented Java-based framework for solving multi-objective optimization problems with metaheuristics.
    Downloads: 0 This Week
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  • 25
    Priority Estimation Tool (AHP)

    Priority Estimation Tool (AHP)

    PriEsT is a decision making tool for Analytic Hierarchy Process (AHP).

    Priorty Estimation Tool (PriEsT) is a decision analysis tool. You can use it for ranking the options you have, or alternatively, you may use it for resource allocation (budgeting) problems. In PriEsT, you enter a list of available options and then define your criteria for prioritization. After defining criteria, PriEsT allows you to enter your judgements against each criterion, which are then used to calculate the final ranking (or weights). Please cite this if you find it...
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    Downloads: 34 This Week
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