{"id":"doi:10.1109/tvlsi.2017.2717950","kind":"article","title":"Accelerating Recurrent Neural Networks: A Memory-Efficient Approach","authors":["Zhisheng Wang","Jun Ting Lin","Zhongfeng Wang"],"author_count":3,"year":2017,"published":"2017-07-03","venue":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","cited_by":85,"doi":"10.1109/tvlsi.2017.2717950","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1109/tvlsi.2017.2717950","archive_url":"https://space-kitty.com/papers/doi:10.1109/tvlsi.2017.2717950","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2730834423","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":["Advanced Neural Network Applications"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0).","topics":[{"slug":"efficient-ai","name":"Efficient Training & Inference","domain_slug":"ai"}],"cited_in_dossiers":[]}