Convex relaxation techniques applied to clustering
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Updated
Sep 25, 2022 - Jupyter Notebook
Convex relaxation techniques applied to clustering
Code for designing sigma delta modulator loop filters with optimal properties.
This code can be used to reproduce most results from the paper " Exact Worst-case Performance of First-order Methods for Composite Convex Optimization" (Published in SIAM Journal on Optimization). (newer version available in the PESTO toolbox!)
Tools to compute the minimum semidefinite rank of a simple undirected graph
Codes for the paper: Theoretical bounds on the network community profile from low-rank semi-definite programming
Fix and Bound: An efficient approach for solving large-scale BoxQPs
Computational appendix of arXiv:2403.02376
Code for symbolic validations of the PEP-based proofs for the article " Worst-case convergence analysis of gradient and Newton methods through semidefinite programming performance estimation" authored by E. de Klerk, F. Glineur and A. Taylor
Max Edge Weighted Clique Problem with multiple choice contrants solved with semidefinite programming
An Exact Solver for Semi-supervised Minimum Sum-of-Squares Clustering
Fork of SDPA-GMP allowing usage as a callable library
This repo involves research on quantum algorithms for various convex optimization problems.
A collection of semidefinite programs that can be randomly generated. Taken from various applications.
Code for paper "Searching for polarization in signed graphs: a local spectral approach" (published at WebConf 2020)
An accelerated active‑set algorithm for a quadratic semidefinite program with general constraints
A Julia package for the computation of hard, theoretically guaranteed bounds on the moments of jump-diffusion processes with polynomial data
Code to output SDP file for use in RDM mechanics.
Semidefinite Programming with Homotopy Conditional Gradient Method (HCGM) and Vu-Condat methods for solving two problems: Fashion-MNIST classification using k-means clustering and geometric embedding for the Sparsest Cut Problem.
This code can be used to reproduce all results from the paper "Smooth strongly convex interpolation and exact worst-case performance of first-order methods" (published in Mathematical Programming). (newer version available in the PESTO toolbox)
A Julia/JuMP Package for Maximizing Algebraic Connectivity of Undirected Weighted Graphs
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