{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T21:50:21Z","timestamp":1725054621905},"reference-count":0,"publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AAAI"],"abstract":"\n \n We present an interactive learning method that enables a user to iteratively refine a regression model. The user examines the output of the model, visualized as the vertical axis of a 2D scatterplot, and provides corrections by repositioning individual data instances to the correct output level. Each repositioned data instance acts as a control point for altering the learned model, using the geometry underlying the data. We capture the underlying structure of the data as a manifold, on which we compute a set of basis functions as the foundation for learning. Our results show that manifold-based interactive learning improves performance monotonically with each correction, outperforming alternative approaches.\n \n <\/jats:p>","DOI":"10.1609\/aaai.v24i1.7688","type":"journal-article","created":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T05:04:37Z","timestamp":1663045477000},"page":"437-443","source":"Crossref","is-referenced-by-count":2,"title":["Interactive Learning Using Manifold Geometry"],"prefix":"10.1609","volume":"24","author":[{"given":"Eric","family":"Eaton","sequence":"first","affiliation":[]},{"given":"Gary","family":"Holness","sequence":"additional","affiliation":[]},{"given":"Daniel","family":"McFarlane","sequence":"additional","affiliation":[]}],"member":"9382","published-online":{"date-parts":[[2010,7,3]]},"container-title":["Proceedings of the AAAI Conference on Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/7688\/7549","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/7688\/7549","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T05:04:37Z","timestamp":1663045477000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/7688"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,7,3]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2010,7,15]]}},"URL":"https:\/\/doi.org\/10.1609\/aaai.v24i1.7688","relation":{},"ISSN":["2374-3468","2159-5399"],"issn-type":[{"value":"2374-3468","type":"electronic"},{"value":"2159-5399","type":"print"}],"subject":[],"published":{"date-parts":[[2010,7,3]]}}}