{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T15:46:01Z","timestamp":1725723961179},"reference-count":46,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T00:00:00Z","timestamp":1702598400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T00:00:00Z","timestamp":1702598400000},"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":[[2023,12,15]]},"DOI":"10.1109\/bigdata59044.2023.10386319","type":"proceedings-article","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T13:28:47Z","timestamp":1705930127000},"page":"1754-1763","source":"Crossref","is-referenced-by-count":0,"title":["NNCR: Revising Classifications using Embedding Based K-Nearest-Neighbor Search"],"prefix":"10.1109","author":[{"given":"Yu-Hsuan","family":"Kuo","sequence":"first","affiliation":[{"name":"Amazon,CA,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saaransh","family":"Gulati","sequence":"additional","affiliation":[{"name":"Amazon,CA,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyu","family":"Chu","sequence":"additional","affiliation":[{"name":"Amazon,CA,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pulkit","family":"Garg","sequence":"additional","affiliation":[{"name":"Amazon,CA,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"A no-regret generalization of hierarchical softmax to extreme multi-label classification","author":"Wydmuch","year":"2018","journal-title":"NeurIPS"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDAR.1995.598994"},{"key":"ref3","article-title":"Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter","author":"Sanh","year":"2019","journal-title":"arXiv preprint arXiv:1910.01108"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3097987"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3185998"},{"key":"ref6","article-title":"Attentionxml: Label tree-based attention-aware deep model for high-performance extreme multi-label text classification","author":"You","year":"2019","journal-title":"NeurIPS"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3542629"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i9.16974"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3206025.3206030"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080834"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271798"},{"key":"ref12","article-title":"Deep nearest neighbor anomaly detection","author":"Bergman","year":"2020","journal-title":"arXiv preprint"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.2991\/cmsa-18.2018.65"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/tbdata.2019.2921572"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-009-9124-7"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-47578-3_1"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/335191.335388"},{"key":"ref18","article-title":"Algorithms for mining distance-based outliers in large datasets","author":"Knorr","year":"1998","journal-title":"VLDB"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/335191.335437"},{"key":"ref20","article-title":"Rapid distance-based outlier detection via sampling","author":"Sugiyama","year":"2013","journal-title":"NeurIPS"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.17"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICDSP.2015.7251924"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1177\/17483026221078111"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-24271-8_56"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1142\/s0218194020500114"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-4048(02)00514-X"},{"key":"ref27","article-title":"Detecting anomalous data using auto-encoders","author":"Andrews","year":"2016","journal-title":"IJMLC"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2935975"},{"key":"ref29","article-title":"Anomaly detection using one-class neural networks","author":"Chalapathy","year":"2018","journal-title":"arXiv preprint"},{"key":"ref30","article-title":"Deep one-class classification","author":"Ruff","year":"2018","journal-title":"ICML"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68474-1_3"},{"key":"ref32","doi-asserted-by":"crossref","DOI":"10.1017\/9781108684163","volume-title":"Mining of massive data sets","author":"Leskovec","year":"2020"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2889473"},{"article-title":"Accelerating large-scale inference with anisotropic vector quantization","volume-title":"International Conference on Machine Learning","author":"Guo","key":"ref34"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2016.90"},{"key":"ref36","article-title":"Learning transferable visual models from natural language supervision","author":"Radford","year":"2021","journal-title":"ICML"},{"key":"ref37","article-title":"Vilt: Vision-and-language transformer without convolution or region supervision","author":"Kim","year":"2021","journal-title":"ICML"},{"key":"ref38","article-title":"Align before fuse: Vision and language representation learning with momentum distillation","author":"Li","year":"2021","journal-title":"NeurIPS"},{"key":"ref39","article-title":"Distributed representations of words and phrases and their compositionality","author":"Mikolov","year":"2013","journal-title":"NeurIPS"},{"key":"ref40","article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018","journal-title":"arXiv preprint"},{"key":"ref41","article-title":"Xlnet: Generalized autoregressive pretraining for language understanding","author":"Yang","year":"2019","journal-title":"NeurIPS"},{"key":"ref42","article-title":"Roberta: A robustly optimized bert pretraining approach","author":"Liu","year":"2019","journal-title":"arXiv preprint"},{"key":"ref43","article-title":"Llama: Open and efficient foundation language models","author":"Touvron","year":"2023","journal-title":"arXiv preprint arXiv:2302.13971"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2953897"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/509907.509965"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"}],"event":{"name":"2023 IEEE International Conference on Big Data (BigData)","start":{"date-parts":[[2023,12,15]]},"location":"Sorrento, Italy","end":{"date-parts":[[2023,12,18]]}},"container-title":["2023 IEEE International Conference on Big Data (BigData)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10385234\/10386078\/10386319.pdf?arnumber=10386319","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T12:06:47Z","timestamp":1706011607000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10386319\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,15]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/bigdata59044.2023.10386319","relation":{},"subject":[],"published":{"date-parts":[[2023,12,15]]}}}