{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T07:46:42Z","timestamp":1767772002932,"version":"3.28.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"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":[[2023,4]]},"DOI":"10.23919\/date56975.2023.10136901","type":"proceedings-article","created":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T19:32:57Z","timestamp":1685734377000},"page":"1-6","source":"Crossref","is-referenced-by-count":11,"title":["FSL-HD: Accelerating Few-Shot Learning on ReRAM using Hyperdimensional Computing"],"prefix":"10.23919","author":[{"given":"Weihong","family":"Xu","sequence":"first","affiliation":[{"name":"University of California San Diego,La Jolla,CA,USA,92093"}]},{"given":"Jaeyoung","family":"Kang","sequence":"additional","affiliation":[{"name":"University of California San Diego,La Jolla,CA,USA,92093"}]},{"given":"Tajana","family":"Rosing","sequence":"additional","affiliation":[{"name":"University of California San Diego,La Jolla,CA,USA,92093"}]}],"member":"263","reference":[{"key":"ref13","first-page":"1","article-title":"A 40nm 64kb 26. 56 tops\/w 2. 37 mb\/mm 2 rram binary\/compute-in-memory macro with 4. 23 x improvement in density and$ 75% use of sensing dynamic range","volume":"65","author":"spetalnick","year":"2022","journal-title":"ISSCC"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.335"},{"key":"ref15","first-page":"496","article-title":"Offset-canceling current-sampling sense amplifier for resistive nonvolatile memory in 65 nm cmos","volume":"52","author":"na","year":"2016","journal-title":"JSSC"},{"key":"ref14","article-title":"A 22nm 4mb 8b-precision reram computing-in-memory macro with 11. 91 to 195. 7 tops\/w for tiny ai edge devices","author":"xue","year":"2021","journal-title":"ISSCC"},{"key":"ref20","article-title":"Tadam: Task dependent adaptive metric for improved few-shot learning","author":"oreshkin","year":"2018","journal-title":"NeurIPS"},{"key":"ref11","article-title":"Locality-based encoder and model quantization for efficient hyper-dimensional computing","author":"morris","year":"2021","journal-title":"TCAD"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1126\/science.aab3050"},{"key":"ref10","article-title":"Floatpim: In-memory acceleration of deep neural network training with high precision","author":"imani","year":"2019","journal-title":"ISCA"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.461"},{"key":"ref2","article-title":"Matching networks for one shot learning","author":"vinyals","year":"2016","journal-title":"NeurIPS"},{"key":"ref1","article-title":"Prototypical networks for few-shot learning","author":"snell","year":"2017","journal-title":"NeurIPS"},{"key":"ref17","article-title":"Meta-dataset: A dataset of datasets for learning to learn from few examples","author":"triantafillou","year":"2019","journal-title":"ArXiv Preprint"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref19","article-title":"Caltech-UCSD Birds 200","author":"welinder","year":"2010","journal-title":"CalTech Tech Rep"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2013.6706807"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-22364-0"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TED.2021.3110464"},{"key":"ref9","article-title":"Attention-in-memory for few-shot learning with configurable ferroelectric fet arravs","author":"reis","year":"2021","journal-title":"ASP-DAC"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00931"},{"key":"ref3","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","author":"finn","year":"2017","journal-title":"ICML"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58568-6_16"},{"key":"ref5","article-title":"A closer look at few-shot classification","author":"chen","year":"2019","journal-title":"ICLRE"}],"event":{"name":"2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)","start":{"date-parts":[[2023,4,17]]},"location":"Antwerp, Belgium","end":{"date-parts":[[2023,4,19]]}},"container-title":["2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10136870\/10136706\/10136901.pdf?arnumber=10136901","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,7]],"date-time":"2023-08-07T17:36:49Z","timestamp":1691429809000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10136901\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4]]},"references-count":22,"URL":"https:\/\/doi.org\/10.23919\/date56975.2023.10136901","relation":{},"subject":[],"published":{"date-parts":[[2023,4]]}}}