{"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/mihash-online-hashing-with-mutual-information","title":"MIHash: Online Hashing with Mutual Information","arxiv_id":"1703.08919","date":"2017-03-27","proceeding":"ICCV 2017 10","authors":["Fatih Cakir","Kun He","Sarah Adel Bargal","Stan Sclaroff"],"abstract":"Learning-based hashing methods are widely used for nearest neighbor\nretrieval, and recently, online hashing methods have demonstrated good\nperformance-complexity trade-offs by learning hash functions from streaming\ndata. In this paper, we first address a key challenge for online hashing: the\nbinary codes for indexed data must be recomputed to keep pace with updates to\nthe hash functions. We propose an efficient quality measure for hash functions,\nbased on an information-theoretic quantity, mutual information, and use it\nsuccessfully as a criterion to eliminate unnecessary hash table updates. Next,\nwe also show how to optimize the mutual information objective using stochastic\ngradient descent. We thus develop a novel hashing method, MIHash, that can be\nused in both online and batch settings. Experiments on image retrieval\nbenchmarks (including a 2.5M image dataset) confirm the effectiveness of our\nformulation, both in reducing hash table recomputations and in learning\nhigh-quality hash functions.","url_abs":"http://arxiv.org/abs/1703.08919v2","url_pdf":"http://arxiv.org/pdf/1703.08919v2.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":"mihash-online-hashing-with-mutual-information","repo_url":"https://github.com/fcakir/mihash","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"image-retrieval","task_name":"Image Retrieval"},{"task_slug":"retrieval","task_name":"Retrieval"}],"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}