{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/hybrid-inexact-bcd-for-coupled-structured","title":"Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-Resolution","arxiv_id":"1909.09183","date":"2020-02-20","proceeding":null,"authors":[],"abstract":"This paper develops a first-order optimization method for coupled structured\nmatrix factorization (CoSMF) problems that arise in the context of\nhyperspectral super-resolution (HSR) in remote sensing. To best leverage the\nproblem structures for computational efficiency, we introduce a hybrid inexact\nblock coordinate descent (HiBCD) scheme wherein one coordinate is updated via\nthe fast proximal gradient (FPG) method, while another via the Frank-Wolfe (FW)\nmethod. The FPG-type methods are known to take less number of iterations to\nconverge, by numerical experience, while the FW-type methods can offer lower\nper-iteration complexity in certain cases; and we wish to take the best of\nboth. We show that the limit points of this HiBCD scheme are stationary. Our\nproof treats HiBCD as an optimization framework for a class of multi-block\nstructured optimization problems, and our stationarity claim is applicable not\nonly to CoSMF but also to many other problems. Previous optimization research\nshowed the same stationarity result for inexact block coordinate descent with\neither FPG or FW updates only. Numerical results indicate that the proposed\nHiBCD scheme is computationally much more efficient than the state-of-the-art\nCoSMF schemes in HSR.","url_abs":"http://arxiv.org/abs/1909.09183v3","url_pdf":"http://arxiv.org/pdf/1909.09183v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"hybrid-inexact-bcd-for-coupled-structured","repo_url":"https://github.com/REIYANG/HiBCD","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"computational-efficiency","task_name":"Computational Efficiency"},{"task_slug":"super-resolution","task_name":"Super-Resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}