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{ "pk": 28306, "title": "Semi-supervised learning in infancy: Infants integrate labeled and unlabeledexemplars to learn new categories", "subtitle": null, "abstract": "Labels facilitate infants category learning. Providing the same label for a set of distinct individuals enhances infantsability to identify the underlying category. In infants daily life, however, many category exemplars will go unlabeled, andinfants will inevitably receive a mix of labeled and unlabeled exemplars when learning real-world object categories. Here,we ask whether 2-year-old infants can integrate these labeled and unlabeled exemplars when learning a novel category.To do so, we draw on machine learning research in semi-supervised learning, a class of algorithms designed to learnfrom just such mixed data. Our results suggest infants do engage in semi-supervised category learning. Infants learnedcategories as successfully in a semi-supervised condition as in a fully-labeled conditionand more successfully than in anunlabeled condition. These findings reveal that the power of labels extends beyond the exemplars being labeled: labelingalso promotes infants learning from subsequent, unlabeled exemplars.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [], "section": "Abstracts-Posters", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/8mh7d3t9", "frozenauthors": [ { "first_name": "Alexander", "middle_name": "", "last_name": "LaTourrette", "name_suffix": "", "institution": "Northwestern University", "department": "" }, { "first_name": "Sandra", "middle_name": "", "last_name": "Waxman", "name_suffix": "", "institution": "Northwestern University", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2018-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28306/galley/17977/download/" } ] }