Media Summary: Time Stamps: 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to ... Real-world problems require sophisticated methodologies providing feasible and efficient solutions. Metaheuristics are We will show off some new features in Convex.jl, solve a few example problems, and discuss development plans for the future.

Juliacon 2020 Optimization Algorithms In - Detailed Analysis & Overview

Time Stamps: 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to ... Real-world problems require sophisticated methodologies providing feasible and efficient solutions. Metaheuristics are We will show off some new features in Convex.jl, solve a few example problems, and discuss development plans for the future. Lessons learned while achieving a 100x speedup of TrajectoryOptimization.jl by eliminating allocations. Memory allocations can ... Find Juan Pablo Vielma's slides here: Contents 00:00 ... In this presentation, we give an overview of the recent progress regarding the continuous nonlinear nonconvex

In this talk, we describe a Julia implementation of RipQP, a regularized interior-point method for convex quadratic MetaheuristicsAlgorithms.jl by Abdelazim Hussien PreTalx link: From logistics to bioinformatics or web analytics, graphs are versatile abstractions for modelling problems and solving them with ...

Photo Gallery

JuliaCon 2020 | Optimization Algorithms in Julia for GPUs | Michel Schanen
Calculating with Sets: Interval Methods in Julia | Workshop | JuliaCon 2020
JuliaCon 2020 | Auto-Optimization and Parallelism in DifferentialEquations.jl | Chris Rackauckas
Using Optimization.jl to Seek the Optimal Optimiser in SciML | Vaibhav Dixit | JuliaCon 2022
Metaheuristics.jl: Towards Any Optimization | Jesús Mejía | JuliaCon 2022
JuliaCon 2020 | Convex.jl: where are we and where do we want to go? | Eric P. Hanson
JuliaCon 2020 | Adventures in Avoiding Allocations | Brian Jackson
Keynote: Conic Optimization in Julia and JuMP | Juan Pablo Vielma | JuliaCon 2020
Optimization Solvers in JuliaSmoothOptimizers | Tangi Migot | JuliaCon 2023
JuliaCon 2020 | Probabilistic Optimization with the Koopman Operator | Adam R. Gerlach
A Multi-precision Algorithm for Convex Quadratic Optimization | Geoffroy Leconte | JuliaCon 2022
MetaheuristicsAlgorithms.jl | Hussien | JuliaCon Global 2025
View Detailed Profile
JuliaCon 2020 | Optimization Algorithms in Julia for GPUs | Michel Schanen

JuliaCon 2020 | Optimization Algorithms in Julia for GPUs | Michel Schanen

Time Stamps: 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to ...

Calculating with Sets: Interval Methods in Julia | Workshop | JuliaCon 2020

Calculating with Sets: Interval Methods in Julia | Workshop | JuliaCon 2020

Sign up for JuliaCon: https://www.eventbrite.com/e/

JuliaCon 2020 | Auto-Optimization and Parallelism in DifferentialEquations.jl | Chris Rackauckas

JuliaCon 2020 | Auto-Optimization and Parallelism in DifferentialEquations.jl | Chris Rackauckas

You might not know all of the latest

Using Optimization.jl to Seek the Optimal Optimiser in SciML | Vaibhav Dixit | JuliaCon 2022

Using Optimization.jl to Seek the Optimal Optimiser in SciML | Vaibhav Dixit | JuliaCon 2022

Optimization

Metaheuristics.jl: Towards Any Optimization | Jesús Mejía | JuliaCon 2022

Metaheuristics.jl: Towards Any Optimization | Jesús Mejía | JuliaCon 2022

Real-world problems require sophisticated methodologies providing feasible and efficient solutions. Metaheuristics are

JuliaCon 2020 | Convex.jl: where are we and where do we want to go? | Eric P. Hanson

JuliaCon 2020 | Convex.jl: where are we and where do we want to go? | Eric P. Hanson

We will show off some new features in Convex.jl, solve a few example problems, and discuss development plans for the future.

JuliaCon 2020 | Adventures in Avoiding Allocations | Brian Jackson

JuliaCon 2020 | Adventures in Avoiding Allocations | Brian Jackson

Lessons learned while achieving a 100x speedup of TrajectoryOptimization.jl by eliminating allocations. Memory allocations can ...

Keynote: Conic Optimization in Julia and JuMP | Juan Pablo Vielma | JuliaCon 2020

Keynote: Conic Optimization in Julia and JuMP | Juan Pablo Vielma | JuliaCon 2020

Find Juan Pablo Vielma's slides here: https://juan-pablo-vielma.github.io/presentations/JULIACON_2020.pdf Contents 00:00 ...

Optimization Solvers in JuliaSmoothOptimizers | Tangi Migot | JuliaCon 2023

Optimization Solvers in JuliaSmoothOptimizers | Tangi Migot | JuliaCon 2023

In this presentation, we give an overview of the recent progress regarding the continuous nonlinear nonconvex

JuliaCon 2020 | Probabilistic Optimization with the Koopman Operator | Adam R. Gerlach

JuliaCon 2020 | Probabilistic Optimization with the Koopman Operator | Adam R. Gerlach

The probabilistic

A Multi-precision Algorithm for Convex Quadratic Optimization | Geoffroy Leconte | JuliaCon 2022

A Multi-precision Algorithm for Convex Quadratic Optimization | Geoffroy Leconte | JuliaCon 2022

In this talk, we describe a Julia implementation of RipQP, a regularized interior-point method for convex quadratic

MetaheuristicsAlgorithms.jl | Hussien | JuliaCon Global 2025

MetaheuristicsAlgorithms.jl | Hussien | JuliaCon Global 2025

MetaheuristicsAlgorithms.jl by Abdelazim Hussien PreTalx link: https://pretalx.com/

Building and Analyzing Graphs at Scale | Workshop | JuliaCon 2020

Building and Analyzing Graphs at Scale | Workshop | JuliaCon 2020

From logistics to bioinformatics or web analytics, graphs are versatile abstractions for modelling problems and solving them with ...