{"pk":29255,"title":"Semi-supervised Learning with 2D Categories","subtitle":null,"abstract":"Research has shown that 1D category representations acquired through supervision change after unsupervised exposuresthat suggest a different boundary. However, it is unclear whether this effect generalizes to categories in which multipledimensions are relevant. To address this question, we trained participants on a 2D information integration structure (adiagonal boundary) under supervision. Participants then classified unsupervised items that implied either a steeper orflatter boundary than that established by supervision creating a conflict region where items should switch membership.Participants classified a grid of the stimulus space both immediately before (pretest) and after (posttest) unsupervisedlearning to assess for differences. We found that conflict-region items were more likely to be classified as members ofthe opposite class on the posttest, relative to pretest in a manner consistent with the unsupervised learning condition.Implications of these findings for semi-supervised learning research and theories of category learning are discussed.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Member Abstracts","is_remote":true,"remote_url":"https://escholarship.org/uc/item/938845vn","frozenauthors":[{"first_name":"John","middle_name":"","last_name":"Patterson","name_suffix":"","institution":"Binghamton University","department":""},{"first_name":"Kenneth","middle_name":"","last_name":"Kurtz","name_suffix":"","institution":"Binghamton University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2019-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/29255/galley/19126/download/"}]}