iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.crossref.org/works/10.1109/ICDCS57875.2023.00083
{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T21:45:37Z","timestamp":1730238337006,"version":"3.28.0"},"reference-count":54,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"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":[[2023,7]]},"DOI":"10.1109\/icdcs57875.2023.00083","type":"proceedings-article","created":{"date-parts":[[2023,10,11]],"date-time":"2023-10-11T17:40:36Z","timestamp":1697046036000},"page":"511-522","source":"Crossref","is-referenced-by-count":3,"title":["Hierarchical, Distributed and Brain-Inspired Learning for Internet of Things Systems"],"prefix":"10.1109","author":[{"given":"Mohsen","family":"Imani","sequence":"first","affiliation":[{"name":"UC Irvine"}]},{"given":"Yeseong","family":"Kim","sequence":"additional","affiliation":[{"name":"DGIST"}]},{"given":"Behnam","family":"Khaleghi","sequence":"additional","affiliation":[{"name":"Qualcomm"}]},{"given":"Justin","family":"Morris","sequence":"additional","affiliation":[{"name":"California State University San Marcos"}]},{"given":"Haleh","family":"Alimohamadi","sequence":"additional","affiliation":[{"name":"UC Los Angeles"}]},{"given":"Farhad","family":"Imani","sequence":"additional","affiliation":[{"name":"University of Connecticut"}]},{"given":"Hugo","family":"Latapie","sequence":"additional","affiliation":[{"name":"CISCO"}]}],"member":"263","reference":[{"year":"0","journal-title":"Huawei ai chip","key":"ref13"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1145\/3297858.3304011"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1109\/HotWeb.2015.22"},{"year":"2017","author":"huynh","journal-title":"Deepmon-building mobile gpu deep learning models for continuous vision applications","key":"ref14"},{"year":"2016","author":"abadi","journal-title":"ArXiv Preprint","article-title":"Tensorflow: Large-scale machine learning on heteroge-neous distributed systems","key":"ref53"},{"key":"ref52","article-title":"Vivado design suite","volume":"5","author":"feist","year":"2012","journal-title":"White Paper"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1145\/3297858.3304036"},{"year":"2016","author":"konecny","journal-title":"ArXiv Preprint","article-title":"Federated learning: Strategies for improving communication efficiency","key":"ref10"},{"year":"2011","author":"pedregosa","journal-title":"JMLR","article-title":"Scikit-learn: Machine learning in python","key":"ref54"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1109\/FiCloud.2014.83"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1109\/ISSNIP.2014.6827673"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1145\/3458817.3480958"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1007\/s12559-009-9009-8"},{"key":"ref51","first-page":"527","article-title":"Network simulations with the ns-3 simulator","volume":"14","author":"henderson","year":"2008","journal-title":"SIGCOMM Demonstration"},{"doi-asserted-by":"publisher","key":"ref50","DOI":"10.1109\/ICCAD.2017.8203843"},{"doi-asserted-by":"publisher","key":"ref46","DOI":"10.1109\/CVPR.2005.283"},{"doi-asserted-by":"publisher","key":"ref45","DOI":"10.1109\/MPRV.2017.3971131"},{"doi-asserted-by":"publisher","key":"ref48","DOI":"10.1109\/ISWC.2012.13"},{"year":"0","journal-title":"Pecan Street Dataport","key":"ref47"},{"year":"2012","author":"ciregan","journal-title":"CVPR","article-title":"Multi-column deep neural networks for image classification","key":"ref42"},{"doi-asserted-by":"publisher","key":"ref41","DOI":"10.1109\/5.726791"},{"doi-asserted-by":"publisher","key":"ref44","DOI":"10.1007\/978-3-642-35395-6_30"},{"year":"0","journal-title":"UCI Machine Learning Repository","key":"ref43"},{"doi-asserted-by":"publisher","key":"ref49","DOI":"10.1145\/2934664"},{"year":"2018","author":"bagdasaryan","journal-title":"ArXiv Preprint","article-title":"How to backdoor federated learning","key":"ref8"},{"year":"2017","author":"smith","journal-title":"NIPS","article-title":"Federated multi-task learning","key":"ref7"},{"year":"2018","author":"wang","journal-title":"ArXiv Preprint","article-title":"In-edge ai: Intelligentizing mobile edge computing, caching and communication by federated learning","key":"ref9"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/INFCOMW.2016.7562226"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1109\/MC.2017.9"},{"year":"2019","author":"gan","journal-title":"ASPLOS","article-title":"An open-source benchmark suite for micro services and their hardware-software implications for cloud & edge systems","key":"ref6"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/JIOT.2017.2750180"},{"key":"ref40","article-title":"Random indexing of text samples for latent semantic analysis","volume":"1036","author":"kanerva","year":"0","journal-title":"Annual conference of the Cognitive Science Society"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1109\/78.650102"},{"key":"ref34","first-page":"1177","article-title":"Random features for large-scale kernel machines","author":"rahimi","year":"2008","journal-title":"Advances in neural information processing systems"},{"year":"2017","author":"rahimi","journal-title":"Mobile Networks and Applications","article-title":"Hyperdimensional computing for blind and one-shot clas-sification of eeg error-related potentials","key":"ref37"},{"key":"ref36","first-page":"108","article-title":"Hierarchical hyperdimensional computing for energy efficient classification","author":"imani","year":"2018","journal-title":"DAC"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1038\/s41598-022-11073-3"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1126\/scirobotics.aaw6736"},{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1145\/3079856.3080246"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.23919\/DATE51398.2021.9474107"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1145\/3093336.3037698"},{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1145\/2831347.2831354"},{"year":"2021","author":"frady","journal-title":"Computing on functions using randomized vector representations","key":"ref39"},{"doi-asserted-by":"publisher","key":"ref38","DOI":"10.1145\/2934583.2934624"},{"year":"2022","author":"ni","journal-title":"ArXiv Preprint","article-title":"Qhd: A brain-inspired hyperdimensional reinforcement learning algorithm","key":"ref24"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1145\/3489517.3530668"},{"doi-asserted-by":"publisher","key":"ref26","DOI":"10.3389\/fnins.2022.757125"},{"key":"ref25","first-page":"1","article-title":"Darl: Distributed reconfigurable accelerator for hyperdi-mensional reinforcement learning","author":"chen","year":"0","journal-title":"Proceedings of the 41st IEEEIACM International Conference on Computer-Aided Design"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1145\/3277593.3277617"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1145\/3470496.3527422"},{"year":"2021","author":"moin","journal-title":"Nature Electronics","article-title":"A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition","key":"ref21"},{"doi-asserted-by":"publisher","key":"ref28","DOI":"10.1109\/CLOUD.2019.00076"},{"doi-asserted-by":"publisher","key":"ref27","DOI":"10.1109\/JPROC.2018.2871163"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.3389\/fnins.2022.858329"}],"event":{"name":"2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)","start":{"date-parts":[[2023,7,18]]},"location":"Hong Kong, Hong Kong","end":{"date-parts":[[2023,7,21]]}},"container-title":["2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10272385\/10272393\/10272435.pdf?arnumber=10272435","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,30]],"date-time":"2023-10-30T18:39:11Z","timestamp":1698691151000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10272435\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7]]},"references-count":54,"URL":"http:\/\/dx.doi.org\/10.1109\/icdcs57875.2023.00083","relation":{},"subject":[],"published":{"date-parts":[[2023,7]]}}}