{"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/multiview-boosting-by-controlling-the","title":"Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters","arxiv_id":"1808.05784","date":"2018-08-17","proceeding":null,"authors":["Anil Goyal","Emilie Morvant","Pascal Germain","Massih-Reza Amini"],"abstract":"In this paper we propose a boosting based multiview learning algorithm,\nreferred to as PB-MVBoost, which iteratively learns i) weights over\nview-specific voters capturing view-specific information; and ii) weights over\nviews by optimizing a PAC-Bayes multiview C-Bound that takes into account the\naccuracy of view-specific classifiers and the diversity between the views. We\nderive a generalization bound for this strategy following the PAC-Bayes theory\nwhich is a suitable tool to deal with models expressed as weighted combination\nover a set of voters. Different experiments on three publicly available\ndatasets show the efficiency of the proposed approach with respect to\nstate-of-art models.","url_abs":"http://arxiv.org/abs/1808.05784v2","url_pdf":"http://arxiv.org/pdf/1808.05784v2.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":"multiview-boosting-by-controlling-the","repo_url":"https://github.com/goyalanil/PB-MVBoost","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"multiview-boosting-by-controlling-the","repo_url":"https://github.com/goyalanil/Multiview_Dataset_MNIST","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"diversity","task_name":"Diversity"},{"task_slug":"document-classification","task_name":"Document Classification"},{"task_slug":"multilingual-text-classification","task_name":"Multilingual text classification"},{"task_slug":"multiview-learning","task_name":"Multiview Learning"},{"task_slug":"text-classification","task_name":"Text Classification"}],"methods":[],"datasets_introduced":[{"slug":"mnist-multiview-datasets","name":"MNIST Multiview Datasets","full_name":"MNIST Multiview Datasets"}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}