frank-wolfe
There are 1 repository under frank-wolfe topic.
vlarmet / cppRouting
Algorithms for Routing and Solving the Traffic Assignment Problem
Language:C++ 113ZIB-IOL / FrankWolfe.jl
Julia implementation for various Frank-Wolfe and Conditional Gradient variants
Language:Julia 100ZhengLi95 / User-Equilibrium-Solution
Program for obtaining the user equilibrium solution with Frank-Wolfe Algorithm in urban traffic assignment
Language:Python 98Mixed-Integer Convex Programming: Branch-and-bound with Frank-Wolfe-based convex relaxations
Language:Julia 27microsoft / workspace-optimizer
The Workspace Planning Tool helps facilities managers and other workspace planners optimize seating arrangements and floorplans using Workplace Analytics collaboration data. This stand-alone tool is a series of Jupyter notebooks you can run locally on your machine.
Language:Jupyter Notebook 14uclaml / Frank-Wolfe-AdvML
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks (AAAI'20)
Language:Python 11Implementation of the Stochastic Frank Wolfe algorithm in TensorFlow and Pytorch.
Language:Python 10- Language:R 8
icezimmer / ConstrainedOptimization
Constrained Optimization using Frank-Wolfe Method
Language:MATLAB 7JuliaDecisionFocusedLearning / DifferentiableFrankWolfe.jl
Differentiable wrapper for FrankWolfe.jl convex optimization routines
Language:Julia 7regenesis90 / UE_traffic_assignment
Frank-Wolfe Algorithm : Find User Equilibrium in Traffic Assignment
Language:Jupyter Notebook 6churnikov / social-economics-models-course
Implementation of Frank Wolfe algoritm on python
Language:Jupyter Notebook 4rctzeng / NeurIPS2021-FWS
This is the repo for Fast Pure Exploration via Frank-Wolfe (NeurIPS 2021).
Language:Julia 4Bell inequalities and local models via Frank-Wolfe algorithms
Language:Julia 4hiroyuki-kasai / SROT
Library of Semi-Relaxed Optimal Transport
sripathisridhar / sridhar2020ismir
Implementation of a novel 'helicality' algorithm that quantifies the octave equivalence of frequency sub-bands in an audio dataset.
Language:Jupyter Notebook 3Code for the paper: Wirth, E.S. and Pokutta, S., 2022, May. Conditional gradients for the approximately vanishing ideal. In International Conference on Artificial Intelligence and Statistics (pp. 2191-2209). PMLR.
Language:Python 3- CSI-using-Blind-Image-Deconvolution-and-Frank-Wolfe-algorithm
EliaFantini / CSI-using-Blind-Image-Deconvolution-and-Frank-Wolfe-algorithm
Blind Image Deconvolution and Frank-Wolfe's algorithm to deblur a license plate for Crime Scene Investigation (CSI)
Language:Jupyter Notebook 2 liacov / OPTproj
Zeroth order Frank Wolfe algorithm. Project for the Optimization for Data Science exam.
Language:Jupyter Notebook 2tlrmchlsmth / tms_submod
Routines for submodular set function minimization
Language:C++ 2Agno94 / frankwolfe_thesis
Algorithms developed during my master thesis at the Universita' degli Studi di Padova. In order to run the tests, you can follow my the instructions at page 31. Download the thesis here: http://tesi.cab.unipd.it/65265/
Language:HTML 1Di40 / MEB-Anomaly-FW-Optimization
Implementation of three variants of the Frank-Wolfe method for solving the Minimum Enclosing Ball problem, and application to anomaly detection.
Language:Python 1XeBasTeX / SFW-python
Python package designed to provide the essentials tools for off-the-grid inverse problem. This is the bedrock for future GUI implementation.
Language:Jupyter Notebook 1andrea3425 / markowitz_portfolio_optimization
This project was carried out as the final assignment for the Mathematical Optimization for Data Science course. The goal of the analysis was to compare two variants of the Frank-Wolfe Method with the Projected Gradient Method on the Markowitz portfolio optimization problem.
Language:Jupyter Notebook 0camilobetanieto / OptimizationDataScience
Implementation of unconstrained and constrained convex optimization algorithms in Python, focusing on solving data science problems such as semi-supervised learning and Support Vector Machines.
Language:Jupyter Notebook 0maxkokot / Optimization-For-DS-project
The final project created for Optimization for Data Science course
Language:Jupyter Notebook 0TannerAGraves / FW-variants-for-WB-Adversarial-Attacks
Final Project for Optimization for Datascence, UNIPD MSc program 23/24. Uses variants of Frank-Wolfe algorithms for projection-free white-box adversarial attacks on convolutional neural networks.
Language:Jupyter Notebook 0Code for the paper Accelerated Affine-Invariant Vonvergence Rates of the Frank-Wolfe Algorithm with Open-Loop Step-Sizes
Language:Python 0Code for the paper: [Wirth, E., Kera, H., and Pokutta, S. (2022). Approximate vanishing ideal computations at scale.](https://arxiv.org/abs/2207.01236)
Language:Python 0an-eve / frank-wolfe-recommender-systems
Application of the Frank-Wolfe algorithm to optimize recommendation systems. Focus on the implementation of matrix completion to predict user-item interactions in sparse datasets.
Language:Jupyter Notebookgiorgiarinaldi / markowitz-portfolio-using-frank-wolfe-algorithms
This project was conducted as the final assignment for the Mathematical Optimization for Data Science course. The objective was to analyze and compare two variants of the Frank-Wolfe Method with the Projected Gradient Method in solving the Markowitz portfolio optimization problem.
Language:Jupyter Notebookluismarcoslc / white_box_attacks_using_FW_optimization_algorithms
Study of four first order Frank Wolfe algorithms to solve constrained non-convex problems in the context of white box adversarial attacks.
Language:Jupyter Notebook
