{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:38:03Z","timestamp":1763192283761,"version":"3.45.0"},"reference-count":39,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"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":[[2025,6,30]]},"DOI":"10.1109\/ijcnn64981.2025.11227909","type":"proceedings-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T18:46:15Z","timestamp":1763145975000},"page":"1-8","source":"Crossref","is-referenced-by-count":0,"title":["MONAS: Efficient Zero-Shot Neural Architecture Search for MCUs"],"prefix":"10.1109","author":[{"given":"Ye","family":"Qiao","sequence":"first","affiliation":[{"name":"University of California, Irvine,Department of Electrical Engineering and Computer Science,Irvine,United States"}]},{"given":"Haocheng","family":"Xu","sequence":"additional","affiliation":[{"name":"University of California, Irvine,Department of Electrical Engineering and Computer Science,Irvine,United States"}]},{"given":"Yifan","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of California, Irvine,Department of Electrical Engineering and Computer Science,Irvine,United States"}]},{"given":"Sitao","family":"Huang","sequence":"additional","affiliation":[{"name":"University of California, Irvine,Department of Electrical Engineering and Computer Science,Irvine,United States"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","year":"2017","author":"Howard","key":"ref2"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICIT48603.2022.10002796"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.20472\/EFC.2023.018.004"},{"article-title":"MCUNet: Tiny deep learning on iot devices","volume-title":"Annual Conference on Neural Information Processing Systems (NeurIPS)","author":"Lin","key":"ref5"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3437984.3458836"},{"article-title":"Neural architecture search: Insights from 1000 papers","year":"2023","author":"White","key":"ref7"},{"article-title":"Nas-bench-suite-zero: Accelerating research on zero cost proxies","year":"2022","author":"Krishnakumar","key":"ref8"},{"article-title":"Neural architecture search without training","year":"2021","author":"Mellor","key":"ref9"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.23919\/DATE58400.2024.10546710"},{"article-title":"Tg-nas: Leveraging zero-cost proxies with transformer and graph convolution networks for efficient neural architecture search","year":"2024","author":"Qiao","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00293"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014780"},{"article-title":"Proxylessnas: Direct neural architecture search on target task and hardware","year":"2019","author":"Cai","key":"ref14"},{"article-title":"Once-for-all: Train one network and specialize it for efficient deployment","year":"2020","author":"Cai","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2018.00474"},{"article-title":"Darts: Differentiable architecture search","year":"2018","author":"Liu","key":"ref17"},{"article-title":"Nas-bench-201: Extending the scope of re-producible neural architecture search","volume-title":"International Conference on Learning Representations (ICLR)","author":"Dong","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00293"},{"article-title":"Neural architecture search on ImageNet in four GPU hours: A theoretically inspired perspective","year":"2021","author":"Chen","key":"ref20"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00040"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1088\/1742-5468\/abc62b"},{"article-title":"Scaling limits of wide neural networks with weight sharing: Gaussian process behavior, gradient independence, and neural tangent kernel derivation","year":"2020","author":"Yang","key":"ref23"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3406325.3465355"},{"key":"ref25","first-page":"10462","article-title":"Disentangling trainability and generalization in deep neural networks","volume-title":"International Conference on Machine Learning","author":"Xiao"},{"article-title":"Zico: Zero-shot nas via inverse coefficient of variation on gradients","year":"2023","author":"Li","key":"ref26"},{"article-title":"Snip: Single-shot network pruning based on connection sensitivity","year":"2019","author":"Lee","key":"ref27"},{"article-title":"Picking winning tickets before training by preserving gradient flow","year":"2020","author":"Wang","key":"ref28"},{"article-title":"Zero-cost proxies for lightweight nas","year":"2021","author":"Abdelfattah","key":"ref29"},{"article-title":"Nas-bench-101: Towards reproducible neural architecture search","year":"2019","author":"Ying","key":"ref30"},{"article-title":"Surrogate nas benchmarks: Going beyond the limited search spaces of tabular nas benchmarks","year":"2022","author":"Zela","key":"ref31"},{"article-title":"Hw-nas-bench: hardware-aware neural architecture search benchmark","year":"2021","author":"Li","key":"ref32"},{"article-title":"Atomnas: Fine-grained end-to-end neural architecture search","year":"2020","author":"Mei","key":"ref33"},{"article-title":"On latency predictors for neural architecture search","year":"2024","author":"Akhauri","key":"ref34"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.2307\/2332226"},{"article-title":"On the number of linear regions of convolutional neural networks","year":"2020","author":"Xiong","key":"ref36"},{"article-title":"Snip: Single-shot network pruning based on connection sensitivity","year":"2018","author":"Lee","key":"ref37"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00186"},{"article-title":"KNAS: Green neural architecture search","volume-title":"Proceedings of ICML 2021","author":"Xu","key":"ref39"}],"event":{"name":"2025 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2025,6,30]]},"location":"Rome, Italy","end":{"date-parts":[[2025,7,5]]}},"container-title":["2025 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11227166\/11227148\/11227909.pdf?arnumber=11227909","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:33:47Z","timestamp":1763192027000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11227909\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/ijcnn64981.2025.11227909","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}