{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:10:22Z","timestamp":1772907022555,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T00:00:00Z","timestamp":1737331200000},"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":[[2025,1,20]]},"DOI":"10.1145\/3658617.3697784","type":"proceedings-article","created":{"date-parts":[[2025,3,4]],"date-time":"2025-03-04T14:23:57Z","timestamp":1741098237000},"page":"43-50","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["LightCL: Compact Continual Learning with Low Memory Footprint For Edge Device"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-0585-9914","authenticated-orcid":false,"given":"Zeqing","family":"Wang","sequence":"first","affiliation":[{"name":"Xidian Univ., Xi'an, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1359-1957","authenticated-orcid":false,"given":"Fei","family":"Cheng","sequence":"additional","affiliation":[{"name":"Xidian Univ., Xi'an, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2763-3114","authenticated-orcid":false,"given":"Kangye","family":"Ji","sequence":"additional","affiliation":[{"name":"Xidian Univ., Xi'an, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0978-482X","authenticated-orcid":false,"given":"Bohu","family":"Huang","sequence":"additional","affiliation":[{"name":"Xidian Univ., Xi'an, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,3,4]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01219-9_9"},{"key":"e_1_3_2_1_2_1","volume-title":"International Conference on Learning Representations.","author":"Benjamin Ari","year":"2019","unstructured":"Ari Benjamin, David Rolnick, and Konrad Kording. 2019. Measuring and regularizing networks in function space. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_3_1","first-page":"15920","article-title":"Dark Experience for General Continual Learning: a Strong, Simple Baseline","volume":"33","author":"Buzzega Pietro","year":"2020","unstructured":"Pietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, and SIMONE CALDERARA. 2020. Dark Experience for General Continual Learning: a Strong, Simple Baseline. In Advances in Neural Information Processing Systems, Vol. 33. 15920--15930.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00938"},{"key":"e_1_3_2_1_5_1","volume-title":"Philip H. S. Torr, and Marc'Aurelio Ranzato.","author":"Chaudhry Arslan","year":"2019","unstructured":"Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet Kumar Dokania, Philip H. S. Torr, and Marc'Aurelio Ranzato. 2019. Continual Learning with Tiny Episodic Memories. CoRR abs\/1902.10486 (2019)."},{"key":"e_1_3_2_1_6_1","unstructured":"Patryk Chrabaszcz Ilya Loshchilov and Frank Hutter. 2017. A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets. arXiv:1707.08819 [cs.CV]"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/MM.2024.3373763"},{"key":"e_1_3_2_1_9_1","volume-title":"Bourdev","author":"Gong Yunchao","year":"2014","unstructured":"Yunchao Gong, Liu Liu, Ming Yang, and Lubomir D. Bourdev. 2014. Compressing Deep Convolutional Networks using Vector Quantization. CoRR abs\/1412.6115 (2014). arXiv:1412.6115"},{"key":"e_1_3_2_1_10_1","volume-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding. ICLR","author":"Han Song","year":"2016","unstructured":"Song Han, Huizi Mao, and William J Dally. 2016. Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding. ICLR (2016)."},{"key":"e_1_3_2_1_11_1","volume-title":"Advances in Neural Information Processing Systems","volume":"28","author":"Han Song","year":"2015","unstructured":"Song Han, Jeff Pool, John Tran, and William Dally. 2015. Learning both Weights and Connections for Efficient Neural Network. In Advances in Neural Information Processing Systems, Vol. 28."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58598-3_28"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611835114"},{"key":"e_1_3_2_1_15_1","unstructured":"Alex Krizhevsky Geoffrey Hinton et al. 2009. Learning multiple layers of features from tiny images. https:\/\/www.cs.toronto.edu\/kriz\/learning-features-2009-TR.pdf (2009)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW51313.2020.00103"},{"key":"e_1_3_2_1_17_1","volume-title":"Pruning Filters for Efficient ConvNets. In International Conference on Learning Representations.","author":"Li Hao","year":"2017","unstructured":"Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, and Hans Peter Graf. 2017. Pruning Filters for Efficient ConvNets. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2773081"},{"key":"e_1_3_2_1_19_1","first-page":"22941","article-title":"On-Device Training Under 256KB Memory","volume":"35","author":"Lin Ji","year":"2022","unstructured":"Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, and Song Han. 2022. On-Device Training Under 256KB Memory. In Advances in Neural Information Processing Systems, Vol. 35. 22941--22954.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCAS.2023.3302182"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00810"},{"key":"e_1_3_2_1_22_1","volume-title":"Cohen","author":"McCloskey Michael","year":"1989","unstructured":"Michael McCloskey and Neal J. Cohen. 1989. Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem. Psychology of Learning and Motivation - Advances in Research and Theory 24, C (1 Jan. 1989), 109--165."},{"key":"e_1_3_2_1_23_1","volume-title":"Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics. In International Conference on Learning Representations.","author":"Ramasesh Vinay Venkatesh","year":"2021","unstructured":"Vinay Venkatesh Ramasesh, Ethan Dyer, and Maithra Raghu. 2021. Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_24_1","volume-title":"Honavar","author":"Ren Weijieying","year":"2024","unstructured":"Weijieying Ren and Vasant G. Honavar. 2024. EsaCL: An Efficient Continual Learning Algorithm. In Proceedings of the 2024 SIAM International Conference on Data Mining, SDM 2024, Houston, TX, USA, April 18--20, 2024, Shashi Shekhar, Vagelis Papalexakis, Jing Gao, Zhe Jiang, and Matteo Riondato (Eds.). SIAM, 163--171."},{"key":"e_1_3_2_1_25_1","volume-title":"Progressive Neural Networks. arXiv e-prints (June","author":"Rusu Andrei A.","year":"2016","unstructured":"Andrei A. Rusu, Neil C. Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell. 2016. Progressive Neural Networks. arXiv e-prints (June 2016). arXiv:1606.04671"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2022.3226481"},{"key":"e_1_3_2_1_27_1","volume-title":"3rd International Conference on Learning Representations, ICLR","author":"Simonyan Karen","year":"2015","unstructured":"Karen Simonyan and Andrew Zisserman. 2015. Very Deep Convolutional Networks for Large-Scale Image Recognition. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings."},{"key":"e_1_3_2_1_28_1","volume-title":"Learn-Prune-Share for Lifelong Learning. In 2020 IEEE International Conference on Data Mining (ICDM). 641--650","author":"Wang Zifeng","year":"2020","unstructured":"Zifeng Wang, Tong Jian, Kaushik Chowdhury, Yanzhi Wang, Jennifer Dy, and Stratis Ioannidis. 2020. Learn-Prune-Share for Lifelong Learning. In 2020 IEEE International Conference on Data Mining (ICDM). 641--650."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.2307.09218"},{"key":"e_1_3_2_1_30_1","first-page":"20366","article-title":"SparCL: Sparse Continual Learning on the Edge","volume":"35","author":"Wang Zifeng","year":"2022","unstructured":"Zifeng Wang, Zheng Zhan, Yifan Gong, Geng Yuan, Wei Niu, Tong Jian, Bin Ren, Stratis Ioannidis, Yanzhi Wang, and Jennifer Dy. 2022. SparCL: Sparse Continual Learning on the Edge. In Advances in Neural Information Processing Systems, Vol. 35. 20366--20380.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_31_1","volume-title":"Proceedings of the 34th International Conference on Machine Learning (Proceedings of Machine Learning Research","volume":"3995","author":"Zenke Friedemann","year":"2017","unstructured":"Friedemann Zenke, Ben Poole, and Surya Ganguli. 2017. Continual Learning Through Synaptic Intelligence. In Proceedings of the 34th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 70). PMLR, 3987--3995."}],"event":{"name":"ASPDAC '25: 30th Asia and South Pacific Design Automation Conference","location":"Tokyo Japan","acronym":"ASPDAC '25","sponsor":["SIGDA ACM Special Interest Group on Design Automation","IEICE","IPSJ","IEEE CAS","IEEE CEDA"]},"container-title":["Proceedings of the 30th Asia and South Pacific Design Automation Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3658617.3697784","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3658617.3697784","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:17:53Z","timestamp":1750295873000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3658617.3697784"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,20]]},"references-count":31,"alternative-id":["10.1145\/3658617.3697784","10.1145\/3658617"],"URL":"https:\/\/doi.org\/10.1145\/3658617.3697784","relation":{},"subject":[],"published":{"date-parts":[[2025,1,20]]},"assertion":[{"value":"2025-03-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}