There are 1 repository under frank-wolfe topic.
Algorithms for Routing and Solving the Traffic Assignment Problem
Program for obtaining the user equilibrium solution with Frank-Wolfe Algorithm in urban traffic assignment
Julia implementation for various Frank-Wolfe and Conditional Gradient variants
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.
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks (AAAI'20)
Implementation of the Stochastic Frank Wolfe algorithm in TensorFlow and Pytorch.
Differentiable wrapper for FrankWolfe.jl convex optimization routines
Frank-Wolfe Algorithm : Find User Equilibrium in Traffic Assignment
Constrained Optimization using Frank-Wolfe Method
This is the repo for Fast Pure Exploration via Frank-Wolfe (NeurIPS 2021).
Implementation of Frank Wolfe algoritm on python
Library of Semi-Relaxed Optimal Transport
Implementation of a novel 'helicality' algorithm that quantifies the octave equivalence of frequency sub-bands in an audio dataset.
This julia package addresses the membership problem for local polytopes: it constructs Bell inequalities and local models in multipartite Bell scenarios with binary outcomes.
Blind Image Deconvolution and Frank-Wolfe's algorithm to deblur a license plate for Crime Scene Investigation (CSI)
Routines for submodular set function minimization
Implementation of three variants of the Frank-Wolfe method for solving the Minimum Enclosing Ball problem, and application to anomaly detection.
Python package designed to provide the essentials tools for off-the-grid inverse problem. This is the bedrock for future GUI implementation.
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.
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.
The final project created for Optimization for Data Science course
Code for the paper: [Wirth, E., Kera, H., and Pokutta, S. (2022). Approximate vanishing ideal computations at scale.](https://arxiv.org/abs/2207.01236)
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/
Study of four first order Frank Wolfe algorithms to solve constrained non-convex problems in the context of white box adversarial attacks.
Code for the paper Accelerated Affine-Invariant Vonvergence Rates of the Frank-Wolfe Algorithm with Open-Loop Step-Sizes