{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:12:56Z","timestamp":1750219976959,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":25,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NSF ASIC Center","award":["CNS-1822165"],"award-info":[{"award-number":["CNS-1822165"]}]},{"DOI":"10.13039\/100006602","name":"Air Force Research Laboratory","doi-asserted-by":"publisher","award":["FA8750-21-C-1511"],"award-info":[{"award-number":["FA8750-21-C-1511"]}],"id":[{"id":"10.13039\/100006602","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1145\/3589737.3605974","type":"proceedings-article","created":{"date-parts":[[2023,8,28]],"date-time":"2023-08-28T16:00:57Z","timestamp":1693238457000},"page":"1-8","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["SEnsitivity Modulated Importance Networking and Rehearsal for Spike Domain Incremental Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-0959-9696","authenticated-orcid":false,"given":"Zaidao","family":"Mei","sequence":"first","affiliation":[{"name":"Electrical Engineering & Computer Science, Syracuse University, Syracuse, New York, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5363-3425","authenticated-orcid":false,"given":"Boyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Electrical Engineering & Computer Science, Syracuse Univeristy, Syracuse, New York, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3644-7088","authenticated-orcid":false,"given":"Daniel","family":"Rider","sequence":"additional","affiliation":[{"name":"Electrical Engineering & Computer Science, Syracuse Univeristy, Syracuse, New York, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2546-0655","authenticated-orcid":false,"given":"Qinru","family":"Qiu","sequence":"additional","affiliation":[{"name":"Electrical Engineering & Computer Science, Syracuse Univeristy, Syracuse, New York, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,8,28]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Philip HS Torr, and Marc'Aurelio Ranzato","author":"Chaudhry Arslan","year":"2019","unstructured":"Arslan Chaudhry , Marcus Rohrbach , Mohamed Elhoseiny , Thalaiyasingam Ajanthan , Puneet K Dokania , Philip HS Torr, and Marc'Aurelio Ranzato . 2019 . On tiny episodic memories in continual learning. arXiv preprint arXiv:1902.10486 (2019). Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet K Dokania, Philip HS Torr, and Marc'Aurelio Ranzato. 2019. On tiny episodic memories in continual learning. arXiv preprint arXiv:1902.10486 (2019)."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2021.3067593"},{"key":"e_1_3_2_1_3_1","volume-title":"International Conference on Machine Learning. PMLR, 2621--2631","author":"Derakhshani Mohammad Mahdi","year":"2021","unstructured":"Mohammad Mahdi Derakhshani , Xiantong Zhen , Ling Shao , and Cees Snoek . 2021 . Kernel continual learning . In International Conference on Machine Learning. PMLR, 2621--2631 . Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao, and Cees Snoek. 2021. Kernel continual learning. In International Conference on Machine Learning. PMLR, 2621--2631."},{"key":"e_1_3_2_1_4_1","volume-title":"Pathnet: Evolution channels gradient descent in super neural networks. arXiv preprint arXiv:1701.08734","author":"Fernando Chrisantha","year":"2017","unstructured":"Chrisantha Fernando , Dylan Banarse , Charles Blundell , Yori Zwols , David Ha , Andrei A Rusu , Alexander Pritzel , and Daan Wierstra . 2017 . Pathnet: Evolution channels gradient descent in super neural networks. arXiv preprint arXiv:1701.08734 (2017). Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A Rusu, Alexander Pritzel, and Daan Wierstra. 2017. Pathnet: Evolution channels gradient descent in super neural networks. arXiv preprint arXiv:1701.08734 (2017)."},{"key":"e_1_3_2_1_5_1","volume-title":"An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks. 2nd International Conference on Learning Representations, ICLR 2014 - Conference Track Proceedings (dec","author":"Goodfellow I. J.","year":"2013","unstructured":"I. J. Goodfellow , M. Mirza , D. Xiao , A. Courville , and Y. Bengio . 2013 . An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks. 2nd International Conference on Learning Representations, ICLR 2014 - Conference Track Proceedings (dec 2013 ). arXiv:1312.6211 I. J. Goodfellow, M. Mirza, D. Xiao, A. Courville, and Y. Bengio. 2013. An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks. 2nd International Conference on Learning Representations, ICLR 2014 - Conference Track Proceedings (dec 2013). arXiv:1312.6211"},{"key":"e_1_3_2_1_6_1","volume-title":"Nispa: Neuroinspired stability-plasticity adaptation for continual learning in sparse networks. arXiv preprint arXiv:2206.09117","author":"Gurbuz Mustafa Burak","year":"2022","unstructured":"Mustafa Burak Gurbuz and Constantine Dovrolis . 2022 . Nispa: Neuroinspired stability-plasticity adaptation for continual learning in sparse networks. arXiv preprint arXiv:2206.09117 (2022). Mustafa Burak Gurbuz and Constantine Dovrolis. 2022. Nispa: Neuroinspired stability-plasticity adaptation for continual learning in sparse networks. arXiv preprint arXiv:2206.09117 (2022)."},{"key":"e_1_3_2_1_7_1","first-page":"3647","article-title":"Continual learning with node-importance based adaptive group sparse regularization","volume":"33","author":"Jung Sangwon","year":"2020","unstructured":"Sangwon Jung , Hongjoon Ahn , Sungmin Cha , and Taesup Moon . 2020 . Continual learning with node-importance based adaptive group sparse regularization . Advances in Neural Information Processing Systems 33 (2020), 3647 -- 3658 . Sangwon Jung, Hongjoon Ahn, Sungmin Cha, and Taesup Moon. 2020. Continual learning with node-importance based adaptive group sparse regularization. Advances in Neural Information Processing Systems 33 (2020), 3647--3658.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1611835114"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"e_1_3_2_1_10_1","volume-title":"Gradient episodic memory for continual learning. Advances in neural information processing systems 30","author":"Lopez-Paz David","year":"2017","unstructured":"David Lopez-Paz and Marc'Aurelio Ranzato . 2017. Gradient episodic memory for continual learning. Advances in neural information processing systems 30 ( 2017 ). David Lopez-Paz and Marc'Aurelio Ranzato. 2017. Gradient episodic memory for continual learning. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0079-7421(08)60536-8"},{"key":"e_1_3_2_1_12_1","first-page":"7308","article-title":"Understanding the role of training regimes in continual learning","volume":"33","author":"Mirzadeh Seyed Iman","year":"2020","unstructured":"Seyed Iman Mirzadeh , Mehrdad Farajtabar , Razvan Pascanu , and Hassan Ghasemzadeh . 2020 . Understanding the role of training regimes in continual learning . Advances in Neural Information Processing Systems 33 (2020), 7308 -- 7320 . Seyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, and Hassan Ghasemzadeh. 2020. Understanding the role of training regimes in continual learning. Advances in Neural Information Processing Systems 33 (2020), 7308--7320.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_13_1","volume-title":"Converting static image datasets to spiking neuromorphic datasets using saccades. Frontiers in neuroscience 9","author":"Orchard Garrick","year":"2015","unstructured":"Garrick Orchard , Ajinkya Jayawant , Gregory K Cohen , and Nitish Thakor . 2015. Converting static image datasets to spiking neuromorphic datasets using saccades. Frontiers in neuroscience 9 ( 2015 ), 437. Garrick Orchard, Ajinkya Jayawant, Gregory K Cohen, and Nitish Thakor. 2015. Converting static image datasets to spiking neuromorphic datasets using saccades. Frontiers in neuroscience 9 (2015), 437."},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings, Part II 16","author":"Prabhu Ameya","year":"2020","unstructured":"Ameya Prabhu , Philip HS Torr , and Puneet K Dokania . 2020 . Gdumb: A simple approach that questions our progress in continual learning. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020 , Proceedings, Part II 16 . Springer, 524--540. Ameya Prabhu, Philip HS Torr, and Puneet K Dokania. 2020. Gdumb: A simple approach that questions our progress in continual learning. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part II 16. Springer, 524--540."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.587"},{"volume-title":"Algorithms for Synthetic Aperture Radar Imagery V","author":"Ross Timothy D","key":"e_1_3_2_1_16_1","unstructured":"Timothy D Ross , Steven W Worrell , Vincent J Velten , John C Mossing , and Michael Lee Bryant . 1998. Standard SAR ATR evaluation experiments using the MSTAR public release data set . In Algorithms for Synthetic Aperture Radar Imagery V , Vol. 3370 . SPIE , 566--573. Timothy D Ross, Steven W Worrell, Vincent J Velten, John C Mossing, and Michael Lee Bryant. 1998. Standard SAR ATR evaluation experiments using the MSTAR public release data set. In Algorithms for Synthetic Aperture Radar Imagery V, Vol. 3370. SPIE, 566--573."},{"key":"e_1_3_2_1_17_1","volume-title":"Progressive neural networks. arXiv preprint arXiv:1606.04671","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 preprint arXiv:1606.04671 ( 2016 ). Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell. 2016. Progressive neural networks. arXiv preprint arXiv:1606.04671 (2016)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18074.2021.9586323"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3354265.3354275"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01220"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSPEC.2021.9563954"},{"key":"e_1_3_2_1_22_1","volume-title":"Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms. arXiv preprint arXiv:1708.07747","author":"Xiao Han","year":"2017","unstructured":"Han Xiao , Kashif Rasul , and Roland Vollgraf . 2017. Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms. arXiv preprint arXiv:1708.07747 ( 2017 ). Han Xiao, Kashif Rasul, and Roland Vollgraf. 2017. Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms. arXiv preprint arXiv:1708.07747 (2017)."},{"key":"e_1_3_2_1_23_1","series-title":"Journal of physics: Conference series","volume-title":"An overview of overfitting and its solutions","author":"Ying Xue","year":"2022","unstructured":"Xue Ying . 2019. An overview of overfitting and its solutions . In Journal of physics: Conference series , Vol. 1168 . IOP Publishing , 02 2022 . Xue Ying. 2019. An overview of overfitting and its solutions. In Journal of physics: Conference series, Vol. 1168. IOP Publishing, 022022."},{"key":"e_1_3_2_1_24_1","volume-title":"Lifelong learning with dynamically expandable networks. arXiv preprint arXiv:1708.01547","author":"Yoon Jaehong","year":"2017","unstructured":"Jaehong Yoon , Eunho Yang , Jeongtae Lee , and Sung Ju Hwang . 2017. Lifelong learning with dynamically expandable networks. arXiv preprint arXiv:1708.01547 ( 2017 ). Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang. 2017. Lifelong learning with dynamically expandable networks. arXiv preprint arXiv:1708.01547 (2017)."},{"key":"e_1_3_2_1_25_1","volume-title":"International conference on machine learning. PMLR, 3987--3995","author":"Zenke Friedemann","year":"2017","unstructured":"Friedemann Zenke , Ben Poole , and Surya Ganguli . 2017 . Continual learning through synaptic intelligence . In International conference on machine learning. PMLR, 3987--3995 . Friedemann Zenke, Ben Poole, and Surya Ganguli. 2017. Continual learning through synaptic intelligence. In International conference on machine learning. PMLR, 3987--3995."}],"event":{"name":"ICONS '23: 2023 International Conference on Neuromorphic Systems","sponsor":["SIGDA ACM Special Interest Group on Design Automation"],"location":"Santa Fe NM USA","acronym":"ICONS '23"},"container-title":["Proceedings of the 2023 International Conference on Neuromorphic Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589737.3605974","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589737.3605974","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589737.3605974","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:21Z","timestamp":1750182561000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589737.3605974"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":25,"alternative-id":["10.1145\/3589737.3605974","10.1145\/3589737"],"URL":"https:\/\/doi.org\/10.1145\/3589737.3605974","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]},"assertion":[{"value":"2023-08-28","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}