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{ "pk": 27248, "title": "Analogies Emerge from Learning Dyamics in Neural Networks", "subtitle": null, "abstract": "When a neural network is trained on multiple analogous tasks,previous research has shown that it will often generate rep-resentations that reflect the analogy. This may explain thevalue of multi-task training, and also may underlie the powerof human analogical reasoning – awareness of analogies mayemerge naturally from gradient-based learning in neural net-works. We explore this issue by generalizing linear analysistechniques to explore two sets of analogous tasks, show thatanalogical structure is commonly extracted, and address somepotential implications.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [ { "word": "neural networks; structure learning; representa-tion; analogy; transfer;" } ], "section": "Posters: Papers", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/5s8259wx", "frozenauthors": [ { "first_name": "Andrew", "middle_name": "", "last_name": "Lampinen", "name_suffix": "", "institution": "Stanford University", "department": "" }, { "first_name": "Shaw", "middle_name": "", "last_name": "Hsu", "name_suffix": "", "institution": "Stanford University", "department": "" }, { "first_name": "James", "middle_name": "L.", "last_name": "McClelland", "name_suffix": "", "institution": "Stanford University", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2017-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27248/galley/16884/download/" } ] }