frank-wolfe

There are 31 repositories under frank-wolfe topic.

  • vlarmet/cppRouting

    Algorithms for Routing and Solving the Traffic Assignment Problem

    Language:C++1115249

  • ZhengLi95/User-Equilibrium-Solution

    Program for obtaining the user equilibrium solution with Frank-Wolfe Algorithm in urban traffic assignment

    Language:Python986324

  • ZIB-IOL/FrankWolfe.jl

    Julia implementation for various Frank-Wolfe and Conditional Gradient variants

    Language:Julia97512220

  • ZIB-IOL/Boscia.jl

    Mixed-Integer Convex Programming: Branch-and-bound with Frank-Wolfe-based convex relaxations

    Language:Julia262625

  • microsoft/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 Notebook14504

  • uclaml/Frank-Wolfe-AdvML

    A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks (AAAI'20)

    Language:Python11405

  • ZIB-IOL/StochasticFrankWolfe

    Implementation of the Stochastic Frank Wolfe algorithm in TensorFlow and Pytorch.

    Language:Python10127

  • saezlab/DOT

    DOT

    Language:R8260

  • JuliaDecisionFocusedLearning/DifferentiableFrankWolfe.jl

    Differentiable wrapper for FrankWolfe.jl convex optimization routines

    Language:Julia7310

  • icezimmer/ConstrainedOptimization

    Constrained Optimization using Frank-Wolfe Method

    Language:MATLAB6100

  • regenesis90/UE_traffic_assignment

    Frank-Wolfe Algorithm : Find User Equilibrium in Traffic Assignment

    Language:Jupyter Notebook6111

  • churnikov/social-economics-models-course

    Implementation of Frank Wolfe algoritm on python

    Language:Jupyter Notebook4200

  • rctzeng/NeurIPS2021-FWS

    This is the repo for Fast Pure Exploration via Frank-Wolfe (NeurIPS 2021).

    Language:Julia4102

  • ZIB-IOL/BellPolytopes.jl

    This julia package addresses the membership problem for local polytopes: it constructs Bell inequalities and local models in multipartite Bell scenarios with binary outcomes.

    Language:Julia4131

  • hiroyuki-kasai/SROT

    Library of Semi-Relaxed Optimal Transport

    3210

  • sripathisridhar/sridhar2020ismir

    Implementation of a novel 'helicality' algorithm that quantifies the octave equivalence of frequency sub-bands in an audio dataset.

    Language:Jupyter Notebook3160

  • ZIB-IOL/CGAVI

    Code 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:Python3100
  • 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 Notebook2100

  • liacov/OPTproj

    Zeroth order Frank Wolfe algorithm. Project for the Optimization for Data Science exam.

    Language:Jupyter Notebook2000

  • tlrmchlsmth/tms_submod

    Routines for submodular set function minimization

    Language:C++2200

  • Agno94/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:HTML1100

  • Di40/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:Python1000

  • XeBasTeX/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 Notebook1201

  • andrea3425/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 Notebook0100

  • camilobetanieto/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 Notebook0100

  • maxkokot/Optimization-For-DS-project

    The final project created for Optimization for Data Science course

    Language:Jupyter Notebook0100

  • TannerAGraves/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 Notebook0201

  • ZIB-IOL/AffineInvariantOLFW

    Code for the paper Accelerated Affine-Invariant Vonvergence Rates of the Frank-Wolfe Algorithm with Open-Loop Step-Sizes

    Language:Python0100

  • ZIB-IOL/avi_at_scale

    Code for the paper: [Wirth, E., Kera, H., and Pokutta, S. (2022). Approximate vanishing ideal computations at scale.](https://arxiv.org/abs/2207.01236)

    Language:Python0200

  • giorgiarinaldi/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 Notebook10

  • luismarcoslc/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 Notebook10