Learning doubly stochastic and nearly idempotent affinity matrix for graph-based clustering-Reference-Cited by-同舟云学术

Learning doubly stochastic and nearly idempotent affinity matrix for graph-based clustering

Published:2021-12 Issue: Volume: Page:
ISSN:0377-2217
Container-title:European Journal of Operational Research
language:en
Short-container-title:European Journal of Operational Research

Author:

Ah-Pine Julien^ORCID

Publisher

Elsevier BV

Subject

Information Systems and Management,Management Science and Operations Research,Modeling and Simulation,General Computer Science,Industrial and Manufacturing Engineering

Reference41 articles.

1. An operation partitioning problem for automated assembly system design;Ahmadi;Operations Research,1991

2. NP-hardness of euclidean sum-of-squares clustering;Aloise;Machine learning,2009

3. On projection algorithms for solving convex feasibility problems;Bauschke;SIAM Review,1996

4. Distributed optimization and statistical learning via the alternating direction method of multipliers;Boyd,2011

5. A polynomial algorithm for balanced clustering via graph partitioning;Caraballo;European Journal of Operational Research,2021

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