{"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/unsupervised-submodular-rank-aggregation-on","title":"Unsupervised Submodular Rank Aggregation on Score-based Permutations","arxiv_id":"1707.01166","date":"2017-07-04","proceeding":null,"authors":["Jun Qi","Xu Liu","Javier Tejedor","Shunsuke Kamijo"],"abstract":"Unsupervised rank aggregation on score-based permutations, which is widely\nused in many applications, has not been deeply explored yet. This work studies\nthe use of submodular optimization for rank aggregation on score-based\npermutations in an unsupervised way. Specifically, we propose an unsupervised\napproach based on the Lovasz Bregman divergence for setting up linear\nstructured convex and nested structured concave objective functions. In\naddition, stochastic optimization methods are applied in the training process\nand efficient algorithms for inference can be guaranteed. The experimental\nresults from Information Retrieval, Combining Distributed Neural Networks,\nInfluencers in Social Networks, and Distributed Automatic Speech Recognition\ntasks demonstrate the effectiveness of the proposed methods.","url_abs":"http://arxiv.org/abs/1707.01166v3","url_pdf":"http://arxiv.org/pdf/1707.01166v3.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":"unsupervised-submodular-rank-aggregation-on","repo_url":"https://github.com/uwjunqi/Subrank","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"automatic-speech-recognition-2","task_name":"Automatic Speech Recognition"},{"task_slug":"automatic-speech-recognition","task_name":"Automatic Speech Recognition (ASR)"},{"task_slug":"information-retrieval","task_name":"Information Retrieval"},{"task_slug":"retrieval","task_name":"Retrieval"},{"task_slug":"speech-recognition","task_name":"Speech Recognition"},{"task_slug":"stochastic-optimization","task_name":"Stochastic Optimization"},{"task_slug":"speech-recognition-1","task_name":"speech-recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}