Search Results for "optimizer windows"
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Showing 8 open source projects for "optimizer windows"
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Functors.jl
Parameterise all the things
Functors.jl provides tools to express a powerful design pattern for dealing with large/ nested structures, as in machine learning and optimization. For large machine learning models, it can be cumbersome or inefficient to work with parameters as one big, flat vector, and structs help manage complexity; but it is also desirable to easily operate over all parameters at once, e.g. for changing precision or applying an optimizer update step. -
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EAGO.jl
A development environment for robust and global optimization
EAGO is an open-source development environment for robust and global optimization in Julia. EAGO is a deterministic global optimizer designed to address a wide variety of optimization problems, emphasizing nonlinear programs (NLPs), by propagating McCormick relaxations along the factorable structure of each expression in the NLP. Most operators supported by modern automatic differentiation (AD) packages (e.g., +, sin, cosh) are supported by EAGO and a number of utilities for sanitizing... -
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PyTorch Forecasting
Time series forecasting with PyTorch
PyTorch Forecasting aims to ease state-of-the-art time series forecasting with neural networks for both real-world cases and research alike. The goal is to provide a high-level API with maximum flexibility for professionals and reasonable defaults for beginners. A time series dataset class that abstracts handling variable transformations, missing values, randomized subsampling, multiple history lengths, etc. A base model class that provides basic training of time series models along with... -
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Greenplum Database
Massive parallel data platform for analytics, machine learning and AI
Rapidly create and deploy models for complex applications in cybersecurity, predictive maintenance, risk management, fraud detection, and many other areas. With its unique cost-based query optimizer designed for large-scale data workloads, Greenplum scales interactive and batch-mode analytics to large datasets in the petabytes without degrading query performance and throughput. Based on PostgreSQL, Greenplum provides you with more control over the software you deploy, reducing vendor... -
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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fastPTOptimizer
a fork of the Panorama Tools / libpano13 with a fast PTOptimizer
This is a fork of Panorama Tools / libpano13-2.9.21 Mercurial. PTOptimizer is part of panorama tools, a great software for aligning and stitching several partially overlapping photos in order to get a bigger photo. When you have only a small or medium number of images and control points, the original PTOptimizer does the optimization in a fairly short time. However if you have a large number of images (several hundrets or more than thousand) and control points, PTOptimizer typically... -
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NASH OS
Nash Operating System for Modern Ecommerce
The all-built-in-one, automatic, ready-to-go out-of-box, easy-to-use state-of-the-art, and really awesome NASH OS! Over 25,000+ flexible features and controls and all scalable!! The most powerful solution ever built to instantly deliver new heights of online ecommerce enterprise to you. -
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ICE (Interval Calculator for Engineer)
Interval Calculator for Engineer
ICE is a simple mathematical calculator with very useful shortcuts for Engineer: works natively with tolerance, can run Monte Carlo analysis, uses engineer notation, includes most of the day by day functions used by engineers. -
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PortOpt
A portfolio-optimizer using Markowitz(1952) mean-variance model
PortOpt [Portfolio Optimizer] is a C++ program (with Python binding) implementing the Markowitz(1952) mean-variance model with agent's linear indifference curves toward risk in order to find the optimal assets portfolio under risk. You have to provide PortOpt (in text files or - if you use the api - using your own code) the variance/covariance matrix of the assets, their average returns and the agent risk preference. It returns the vector of assets' shares that composes the optimal...
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