{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T22:28:47Z","timestamp":1772490527636,"version":"3.50.1"},"reference-count":42,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7,18]]},"DOI":"10.1109\/ijcnn55064.2022.9892663","type":"proceedings-article","created":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T19:56:04Z","timestamp":1664567764000},"page":"1-9","source":"Crossref","is-referenced-by-count":3,"title":["R-Net: Robustness Enhanced Financial Time-Series Prediction with Differential Privacy"],"prefix":"10.1109","author":[{"given":"Shuo","family":"Wang","sequence":"first","affiliation":[{"name":"CSIRO&#x0027;s Data61 &#x0026; Cybersecurity CRC,Australia"}]},{"given":"Jinyuan","family":"Qin","sequence":"additional","affiliation":[{"name":"University of Melbourne,Australia"}]},{"given":"Carsten","family":"Rudolph","sequence":"additional","affiliation":[{"name":"Monash University,Australia"}]},{"given":"Surya","family":"Nepal","sequence":"additional","affiliation":[{"name":"CSIRO&#x0027;s Data61 &#x0026; Cybersecurity CRC,Australia"}]},{"given":"Marthie","family":"Grobler","sequence":"additional","affiliation":[{"name":"CSIRO&#x0027;s Data61 &#x0026; Cybersecurity CRC,Australia"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/660"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00044"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2017.2698369"},{"key":"ref32","article-title":"A multimodal event-driven lstm model for stock prediction using online news","author":"li","year":"2020","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2838731"},{"key":"ref30","article-title":"Umap: Uniform manifold approximation and projection for dimension reduction","author":"mcinnes","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref37","article-title":"Parametric noise injection: Trainable randomness to improve deep neural network robustness against adversarial attack","author":"rakin","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-79228-4_1"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1137\/07070111X"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2811377"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2003.03.023"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.1990.137535"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1111\/j.1540-6261.2008.01362.x"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2003.1209017"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2010.12.007"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2006.115"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/S0957-4174(01)00058-6"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/S0957-4174(02)00079-9"},{"key":"ref17","first-page":"1","article-title":"Differential privacy","author":"cynthia","year":"2006","journal-title":"Automata Languages and Programming"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1250790.1250803"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1561\/0400000042","article-title":"The algorithmic foundations of differential privacy","volume":"9","author":"dwork","year":"2014","journal-title":"Foundations and Trends\ufffd in Theoretical Computer Science"},{"key":"ref28","author":"wang","year":"2018","journal-title":"Novel approaches to sentiment analysis for stock prediction"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-2312(01)00702-0"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2582924"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2005.09.002"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.06.032"},{"key":"ref29","article-title":"Universal sentence encoder","author":"cer","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.10.034"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.04.030"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93034-3_22"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-2312(00)00364-7"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2003.05.001"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2005.06.024"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.1968.sp008455"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/11681878_14"},{"key":"ref42","article-title":"Deep learning for event-driven stock prediction","author":"ding","year":"0","journal-title":"Twenty-Fourth International Joint Conference on Artificial Intelligence"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9236(03)00092-7"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.11.028"},{"key":"ref23","author":"bouvrie","year":"2006","journal-title":"Notes on convolutional neural networks"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/BF02523391"},{"key":"ref25","author":"sak","year":"2014","journal-title":"Long short-term memory recurrent neural network architectures for large scale acoustic modeling"}],"event":{"name":"2022 International Joint Conference on Neural Networks (IJCNN)","location":"Padua, Italy","start":{"date-parts":[[2022,7,18]]},"end":{"date-parts":[[2022,7,23]]}},"container-title":["2022 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9891857\/9889787\/09892663.pdf?arnumber=9892663","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T22:58:01Z","timestamp":1667516281000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9892663\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,18]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/ijcnn55064.2022.9892663","relation":{},"subject":[],"published":{"date-parts":[[2022,7,18]]}}}