%0 Conference Paper %1 conf/sensys/TaoTDB19 %A Tao, Jin %A Thakker, Urmish %A Dasika, Ganesh %A Beu, Jesse G. %B SenSys-ML %D 2019 %I ACM %K dblp %P 31-36 %T Skipping RNN State Updates without Retraining the Original Model. %U http://dblp.uni-trier.de/db/conf/sensys/ml2019.html#TaoTDB19 %@ 978-1-4503-7011-0

@inproceedings{conf/sensys/TaoTDB19, added-at = {2019-10-28T00:00:00.000+0100}, author = {Tao, Jin and Thakker, Urmish and Dasika, Ganesh and Beu, Jesse G.}, biburl = {https://www.bibsonomy.org/bibtex/20bcd6b5f8446797f1448e7d97579ebc2/dblp}, booktitle = {SenSys-ML}, crossref = {conf/sensys/2019ml}, ee = {https://doi.org/10.1145/3362743.3362965}, interhash = {dbb0e7519bcc585ea9d5ac39f7253ba7}, intrahash = {0bcd6b5f8446797f1448e7d97579ebc2}, isbn = {978-1-4503-7011-0}, keywords = {dblp}, pages = {31-36}, publisher = {ACM}, timestamp = {2019-10-29T11:37:51.000+0100}, title = {Skipping RNN State Updates without Retraining the Original Model.}, url = {http://dblp.uni-trier.de/db/conf/sensys/ml2019.html#TaoTDB19}, year = 2019 }