{"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"14205","month":"02","language":[{"iso":"eng"}],"article_processing_charge":"No","author":[{"first_name":"Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","last_name":"Locatello"},{"full_name":"Khanna, Rajiv","first_name":"Rajiv","last_name":"Khanna"},{"last_name":"Tschannen","full_name":"Tschannen, Michael","first_name":"Michael"},{"full_name":"Jaggi, Martin","first_name":"Martin","last_name":"Jaggi"}],"publication_status":"published","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.1702.06457","open_access":"1"}],"date_updated":"2023-09-13T09:49:10Z","publisher":"ML Research Press","volume":54,"intvolume":" 54","page":"860-868","type":"conference","status":"public","oa":1,"day":"21","extern":"1","conference":{"name":"AISTATS: Conference on Artificial Intelligence and Statistics","start_date":"2017-04-20","end_date":"2017-04-22","location":"Fort Lauderdale, FL, United States"},"year":"2017","date_published":"2017-02-21T00:00:00Z","external_id":{"arxiv":["1702.06457"]},"abstract":[{"text":"Two of the most fundamental prototypes of greedy optimization are the matching pursuit and Frank-Wolfe algorithms. In this paper, we take a unified view on both classes of methods, leading to the first explicit convergence rates of matching pursuit methods in an optimization sense, for general sets of atoms. We derive sublinear (1/t) convergence for both classes on general smooth objectives, and linear convergence on strongly convex objectives, as well as a clear correspondence of algorithm variants. Our presented algorithms and rates are affine invariant, and do not need any incoherence or sparsity assumptions.","lang":"eng"}],"quality_controlled":"1","title":"A unified optimization view on generalized matching pursuit and Frank-Wolfe","date_created":"2023-08-22T14:17:19Z","publication":"Proceedings of the 20th International Conference on Artificial Intelligence and Statistics","department":[{"_id":"FrLo"}],"oa_version":"Preprint","citation":{"chicago":"Locatello, Francesco, Rajiv Khanna, Michael Tschannen, and Martin Jaggi. “A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe.” In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 54:860–68. ML Research Press, 2017.","short":"F. Locatello, R. Khanna, M. Tschannen, M. Jaggi, in:, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, ML Research Press, 2017, pp. 860–868.","ieee":"F. Locatello, R. Khanna, M. Tschannen, and M. Jaggi, “A unified optimization view on generalized matching pursuit and Frank-Wolfe,” in Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, Fort Lauderdale, FL, United States, 2017, vol. 54, pp. 860–868.","ista":"Locatello F, Khanna R, Tschannen M, Jaggi M. 2017. A unified optimization view on generalized matching pursuit and Frank-Wolfe. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics vol. 54, 860–868.","mla":"Locatello, Francesco, et al. “A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe.” Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, vol. 54, ML Research Press, 2017, pp. 860–68.","ama":"Locatello F, Khanna R, Tschannen M, Jaggi M. A unified optimization view on generalized matching pursuit and Frank-Wolfe. In: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics. Vol 54. ML Research Press; 2017:860-868.","apa":"Locatello, F., Khanna, R., Tschannen, M., & Jaggi, M. (2017). A unified optimization view on generalized matching pursuit and Frank-Wolfe. In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (Vol. 54, pp. 860–868). Fort Lauderdale, FL, United States: ML Research Press."}}