Article Instance

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{
    "pk": 30562,
    "title": "Using Fast Weights to Deblur Old Memories",
    "subtitle": null,
    "abstract": "Connectionist models usually have a single weight on each connection. Some interesting newproperties emerge if each connection has two weights: A slowly changing, plastic weight which stores long-term knowledge and a fast-changing, elastic weight which stores temporary knowledge and spontaneously decays towards zero. If a network learns a set of associations and then these associationsare \"blurred\" by subsequent learning, all the original associations can be \"deblurred\" by rehearsing on just a few of them. The rehearsal allows the fast weights to take on values that temporarily cancel outthe changes in the slow weights caused by the subsequent learning.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Connectionism I",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/0570j1dp",
    "frozenauthors": [
        {
            "first_name": "Geoffrey",
            "middle_name": "E.",
            "last_name": "Hinton",
            "name_suffix": "",
            "institution": "Carnegie-Mellon University",
            "department": ""
        },
        {
            "first_name": "David",
            "middle_name": "C.",
            "last_name": "Plaut",
            "name_suffix": "",
            "institution": "Carnegie-Mellon University",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1987-01-01T21:00:00+03:00",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/30562/galley/20411/download/"
        }
    ]
}