{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:41:19Z","timestamp":1755823279309,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":44,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1145\/3589334.3645538","type":"proceedings-article","created":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T07:08:13Z","timestamp":1715152093000},"page":"2965-2975","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["MatchNAS: Optimizing Edge AI in Sparse-Label Data Contexts via Automating Deep Neural Network Porting for Mobile Deployment"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-1239-1286","authenticated-orcid":false,"given":"Hongtao","family":"Huang","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, University of New South Wales, Sydney, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7778-8807","authenticated-orcid":false,"given":"Xiaojun","family":"Chang","sequence":"additional","affiliation":[{"name":"Faculty of Engineering &amp; Information Technology, University of Technology Sydney, Sydeny, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4076-1811","authenticated-orcid":false,"given":"Wen","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of New South Wales, Sydney, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4149-839X","authenticated-orcid":false,"given":"Lina","family":"Yao","sequence":"additional","affiliation":[{"name":"CSIRO's Data61 and University of New South Wales, Sydney, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"Philip Bachman Ouais Alsharif and Doina Precup. 2014. Learning with Pseudo-Ensembles. In NIPS. https:\/\/api.semanticscholar.org\/CorpusID:8307266"},{"key":"e_1_3_2_2_2_1","volume-title":"Designing neural network architectures using reinforcement learning. arXiv preprint arXiv:1611.02167","author":"Baker Bowen","year":"2016","unstructured":"Bowen Baker, Otkrist Gupta, Nikhil Naik, and Ramesh Raskar. 2016. Designing neural network architectures using reinforcement learning. arXiv preprint arXiv:1611.02167 (2016)."},{"key":"e_1_3_2_2_3_1","volume-title":"ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring. In International Conference on Learning Representations. https:\/\/api.semanticscholar.org\/CorpusID:213757781","author":"Berthelot David","year":"2020","unstructured":"David Berthelot, Nicholas Carlini, Ekin Dogus Cubuk, Alexey Kurakin, Kihyuk Sohn, Han Zhang, and Colin Raffel. 2020. ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring. In International Conference on Learning Representations. https:\/\/api.semanticscholar.org\/CorpusID:213757781"},{"key":"e_1_3_2_2_4_1","volume-title":"MixMatch: A Holistic Approach to Semi-Supervised Learning. ArXiv","author":"Berthelot David","year":"2019","unstructured":"David Berthelot, Nicholas Carlini, Ian J. Goodfellow, Nicolas Papernot, Avital Oliver, and Colin Raffel. 2019. MixMatch: A Holistic Approach to Semi-Supervised Learning. ArXiv, Vol. abs\/1905.02249 (2019). https:\/\/api.semanticscholar.org\/CorpusID:146808485"},{"key":"e_1_3_2_2_5_1","volume-title":"Once for All: Train One Network and Specialize it for Efficient Deployment. ArXiv","author":"Cai Han","year":"2019","unstructured":"Han Cai, Chuang Gan, and Song Han. 2019. Once for All: Train One Network and Specialize it for Efficient Deployment. ArXiv, Vol. abs\/1908.09791 (2019). https:\/\/api.semanticscholar.org\/CorpusID:201666112"},{"key":"e_1_3_2_2_6_1","volume-title":"ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware. ArXiv","author":"Cai Han","year":"2018","unstructured":"Han Cai, Ligeng Zhu, and Song Han. 2018. ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware. ArXiv, Vol. abs\/1812.00332 (2018). https:\/\/api.semanticscholar.org\/CorpusID:54438210"},{"key":"e_1_3_2_2_7_1","volume-title":"Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective. ArXiv","author":"Chen Wuyang","year":"2021","unstructured":"Wuyang Chen, Xinyu Gong, and Zhangyang Wang. 2021. Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective. ArXiv, Vol. abs\/2102.11535 (2021). https:\/\/api.semanticscholar.org\/CorpusID:232013680"},{"key":"e_1_3_2_2_8_1","volume-title":"ChamNet: Towards Efficient Network Design Through Platform-Aware Model Adaptation. 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Dai Xiaoliang","year":"2018","unstructured":"Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, Marat Dukhan, Yunqing Hu, Yiming Wu, Yangqing Jia, P\u00e9ter Vajda, Matthew Uyttendaele, and Niraj Kumar Jha. 2018. ChamNet: Towards Efficient Network Design Through Platform-Aware Model Adaptation. 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2018), 11390--11399. https:\/\/api.semanticscholar.org\/CorpusID:56657862"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_3_2_2_10_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. ArXiv","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. ArXiv, Vol. abs\/1810.04805 (2019). https:\/\/api.semanticscholar.org\/CorpusID:52967399"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583540"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-014-0733-5"},{"key":"e_1_3_2_2_13_1","volume-title":"MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks. 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2017","author":"Gordon A.","year":"2065","unstructured":"A. Gordon, Elad Eban, Ofir Nachum, Bo Chen, Tien-Ju Yang, and E. Choi. 2017. MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks. 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2017), 1586--1595. https:\/\/api.semanticscholar.org\/CorpusID:206596875"},{"key":"e_1_3_2_2_14_1","volume-title":"Single Path One-Shot Neural Architecture Search with Uniform Sampling. In European Conference on Computer Vision. https:\/\/api.semanticscholar.org\/CorpusID:90262841","author":"Guo Zichao","year":"2019","unstructured":"Zichao Guo, Xiangyu Zhang, Haoyuan Mu, Wen Heng, Zechun Liu, Yichen Wei, and Jian Sun. 2019. Single Path One-Shot Neural Architecture Search with Uniform Sampling. In European Conference on Computer Vision. https:\/\/api.semanticscholar.org\/CorpusID:90262841"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3062319"},{"key":"e_1_3_2_2_16_1","volume-title":"Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015","author":"He Kaiming","year":"2015","unstructured":"Kaiming He, X. Zhang, Shaoqing Ren, and Jian Sun. 2015. Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015), 770--778. https:\/\/api.semanticscholar.org\/CorpusID:206594692"},{"key":"e_1_3_2_2_17_1","volume-title":"Distilling the Knowledge in a Neural Network. ArXiv","author":"Hinton Geoffrey E.","year":"2015","unstructured":"Geoffrey E. Hinton, Oriol Vinyals, and Jeffrey Dean. 2015. Distilling the Knowledge in a Neural Network. ArXiv, Vol. abs\/1503.02531 (2015)."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00140"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2013.77"},{"key":"e_1_3_2_2_20_1","unstructured":"Alex Krizhevsky. 2009. Learning Multiple Layers of Features from Tiny Images. https:\/\/api.semanticscholar.org\/CorpusID:18268744"},{"key":"e_1_3_2_2_21_1","unstructured":"Dong-Hyun Lee. 2013. Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks. https:\/\/api.semanticscholar.org\/CorpusID:18507866"},{"key":"e_1_3_2_2_22_1","volume-title":"Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition. 2021 IEEE\/CVF International Conference on Computer Vision (ICCV)","author":"Lin Ming","year":"2021","unstructured":"Ming Lin, Pichao Wang, Zhenhong Sun, Hesen Chen, Xiuyu Sun, Qi Qian, Hao Li, and Rong Jin. 2021. Zen-NAS: A Zero-Shot NAS for High-Performance Image Recognition. 2021 IEEE\/CVF International Conference on Computer Vision (ICCV) (2021), 337--346. https:\/\/api.semanticscholar.org\/CorpusID:245835451"},{"key":"e_1_3_2_2_23_1","volume-title":"Decoupled Weight Decay Regularization. In International Conference on Learning Representations. https:\/\/api.semanticscholar.org\/CorpusID:53592270","author":"Loshchilov Ilya","year":"2017","unstructured":"Ilya Loshchilov and Frank Hutter. 2017. Decoupled Weight Decay Regularization. In International Conference on Learning Representations. https:\/\/api.semanticscholar.org\/CorpusID:53592270"},{"key":"e_1_3_2_2_24_1","volume-title":"Deep Learning at the Mobile Edge: Opportunities for 5G Networks. Applied Sciences","author":"Cervell\u00f3-Pastor Cristina","year":"2020","unstructured":"Miranda. McClellan, Cristina Cervell\u00f3-Pastor, and Sebasti\u00e0 Sallent. 2020. Deep Learning at the Mobile Edge: Opportunities for 5G Networks. Applied Sciences (2020). https:\/\/api.semanticscholar.org\/CorpusID:225525817"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1975.10479874"},{"key":"e_1_3_2_2_26_1","volume-title":"Crowley","author":"Mellor Joseph Charles","year":"2020","unstructured":"Joseph Charles Mellor, Jack Turner, Amos J. Storkey, and Elliot J. Crowley. 2020. Neural Architecture Search without Training. ArXiv, Vol. abs\/2006.04647 (2020). https:\/\/api.semanticscholar.org\/CorpusID:219531078"},{"key":"e_1_3_2_2_27_1","volume-title":"Machine Learning, and Deep Learning. Iraqi Journal for Computer Science and Mathematics","author":"Mijwil Maad M.","year":"2022","unstructured":"Maad M. Mijwil. 2022. Has the Future Started? The Current Growth of Artificial Intelligence, Machine Learning, and Deep Learning. Iraqi Journal for Computer Science and Mathematics (2022). https:\/\/api.semanticscholar.org\/CorpusID:249688145"},{"key":"e_1_3_2_2_28_1","unstructured":"Adam Paszke Sam Gross Soumith Chintala Gregory Chanan Edward Yang Zachary DeVito Zeming Lin Alban Desmaison Luca Antiga and Adam Lerer. 2017. Automatic differentiation in PyTorch. (2017)."},{"key":"e_1_3_2_2_29_1","volume-title":"Jie Tan, Quoc V. Le, and Alexey Kurakin.","author":"Real Esteban","year":"2017","unstructured":"Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Jie Tan, Quoc V. Le, and Alexey Kurakin. 2017. Large-Scale Evolution of Image Classifiers. ArXiv, Vol. abs\/1703.01041 (2017)."},{"key":"e_1_3_2_2_30_1","volume-title":"CompOFA: Compound Once-For-All Networks for Faster Multi-Platform Deployment. ArXiv","author":"Sahni Manas","year":"2021","unstructured":"Manas Sahni, Shreya Varshini, Alind Khare, and Alexey Tumanov. 2021. CompOFA: Compound Once-For-All Networks for Faster Multi-Platform Deployment. ArXiv, Vol. abs\/2104.12642 (2021). https:\/\/api.semanticscholar.org\/CorpusID:232286427"},{"key":"e_1_3_2_2_31_1","unstructured":"Samsung. [n. d.]. Samsung Remote Test Lab. https:\/\/developer.samsung.com\/remote-test-lab"},{"key":"e_1_3_2_2_32_1","volume-title":"Claudiu Cristian Musat, and Mathieu Salzmann","author":"Sciuto Christian","year":"2019","unstructured":"Christian Sciuto, Kaicheng Yu, Martin Jaggi, Claudiu Cristian Musat, and Mathieu Salzmann. 2019. Evaluating the Search Phase of Neural Architecture Search. ArXiv, Vol. abs\/1902.08142 (2019)."},{"key":"e_1_3_2_2_33_1","volume-title":"Alexey Kurakin, Han Zhang, and Colin Raffel.","author":"Sohn Kihyuk","year":"2020","unstructured":"Kihyuk Sohn, David Berthelot, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin Dogus Cubuk, Alexey Kurakin, Han Zhang, and Colin Raffel. 2020. FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. ArXiv, Vol. abs\/2001.07685 (2020). https:\/\/api.semanticscholar.org\/CorpusID:210839228"},{"key":"e_1_3_2_2_34_1","volume-title":"MnasNet: Platform-Aware Neural Architecture Search for Mobile. 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2018","author":"Tan Mingxing","year":"1891","unstructured":"Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, and Quoc V. Le. 2018. MnasNet: Platform-Aware Neural Architecture Search for Mobile. 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2018), 2815--2823. https:\/\/api.semanticscholar.org\/CorpusID:51891697"},{"key":"e_1_3_2_2_35_1","volume-title":"Weight-averaged consistency targets improve semi-supervised deep learning results. ArXiv","author":"Tarvainen Antti","year":"2017","unstructured":"Antti Tarvainen and Harri Valpola. 2017. Weight-averaged consistency targets improve semi-supervised deep learning results. ArXiv, Vol. abs\/1703.01780 (2017). https:\/\/api.semanticscholar.org\/CorpusID:2759724"},{"key":"e_1_3_2_2_36_1","volume-title":"Technical Report CNS-TR-2011-001. California Institute of Technology.","author":"Wah C.","year":"2011","unstructured":"C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie. 2011.. Technical Report CNS-TR-2011-001. California Institute of Technology."},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00635"},{"key":"e_1_3_2_2_38_1","volume-title":"Le","author":"Xie Qizhe","year":"2019","unstructured":"Qizhe Xie, Zihang Dai, Eduard H. Hovy, Minh-Thang Luong, and Quoc V. Le. 2019. Unsupervised Data Augmentation for Consistency Training. arXiv: Learning (2019). https:\/\/api.semanticscholar.org\/CorpusID:195873898"},{"key":"e_1_3_2_2_39_1","volume-title":"The World Wide Web Conference","author":"Xu Mengwei","year":"2018","unstructured":"Mengwei Xu, Jiawei Liu, Yuanqiang Liu, Felix Xiaozhu Lin, Yunxin Liu, and Xuanzhe Liu. 2018. A First Look at Deep Learning Apps on Smartphones. The World Wide Web Conference (2018). https:\/\/api.semanticscholar.org\/CorpusID:59158795"},{"key":"e_1_3_2_2_40_1","volume-title":"GreedyNAS: Towards Fast One-Shot NAS With Greedy Supernet. 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)","author":"You Shan","year":"2020","unstructured":"Shan You, Tao Huang, Mingmin Yang, Fei Wang, Chen Qian, and Changshui Zhang. 2020. GreedyNAS: Towards Fast One-Shot NAS With Greedy Supernet. 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), 1996--2005."},{"key":"e_1_3_2_2_41_1","volume-title":"Le","author":"Yu Jiahui","year":"2020","unstructured":"Jiahui Yu, Pengchong Jin, Hanxiao Liu, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Thomas Huang, Xiaodan Song, and Quoc V. Le. 2020. BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models. In ECCV."},{"key":"e_1_3_2_2_42_1","volume-title":"Gao","author":"Zhao Rui","year":"2019","unstructured":"Rui Zhao, Ruqiang Yan, Zhenghua Chen, Kezhi Mao, Peng Wang, and Robert X. Gao. 2019. Deep learning and its applications to machine health monitoring. Mechanical Systems and Signal Processing (2019). https:\/\/api.semanticscholar.org\/CorpusID:125608550"},{"key":"e_1_3_2_2_43_1","volume-title":"Neural architecture search with reinforcement learning. arXiv preprint arXiv:1611.01578","author":"Zoph Barret","year":"2016","unstructured":"Barret Zoph and Quoc V Le. 2016. Neural architecture search with reinforcement learning. arXiv preprint arXiv:1611.01578 (2016)."},{"key":"e_1_3_2_2_44_1","volume-title":"Learning Transferable Architectures for Scalable Image Recognition. 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Zoph Barret","year":"2018","unstructured":"Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V. Le. 2018. Learning Transferable Architectures for Scalable Image Recognition. 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2018), 8697--8710."}],"event":{"name":"WWW '24: The ACM Web Conference 2024","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Singapore Singapore","acronym":"WWW '24"},"container-title":["Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645538","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589334.3645538","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:25:50Z","timestamp":1755822350000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645538"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":44,"alternative-id":["10.1145\/3589334.3645538","10.1145\/3589334"],"URL":"https:\/\/doi.org\/10.1145\/3589334.3645538","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}