Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation:
A Performance Guarantee for Spectral Clustering

Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation: A Performance Guarantee for Spectral Clustering

29 June 2018

Thomas Strohmer

Papers citing "Certifying Global Optimality of Graph Cuts via Semidefinite Relaxation: A Performance Guarantee for Spectral Clustering"

6 / 6 papers shown

Title
On the Exactness of SDP Relaxation for Quadratic Assignment Problem Shuyang Ling 38 4 0 12 Aug 2024
A Performance Guarantee for Spectral Clustering M. Boedihardjo Shaofeng Deng Thomas Strohmer 14 7 0 10 Jul 2020
Diffusion $K$ -means clustering on manifolds: provable exact recovery via semidefinite relaxations Xiaohui Chen Yun Yang 24 16 0 11 Mar 2019
Geometric structure of graph Laplacian embeddings Nicolas García Trillos Franca Hoffmann Bamdad Hosseini 33 23 0 30 Jan 2019
Learning by Unsupervised Nonlinear Diffusion Mauro Maggioni James M. Murphy DiffM 30 40 0 15 Oct 2018
When Do Birds of a Feather Flock Together? k-Means, Proximity, and Conic Programming Xiaodong Li Yang Li Shuyang Ling Thomas Strohmer Ke Wei 27 36 0 16 Oct 2017