Smart at what cost? Characterising Mobile Deep Neural Networks in the
wild

Smart at what cost? Characterising Mobile Deep Neural Networks in the wild

28 September 2021

Stefanos Laskaridis

Abhinav Mehrotra

Ilias Leontiadis

Nicholas D. Lane

Papers citing "Smart at what cost? Characterising Mobile Deep Neural Networks in the wild"

17 / 17 papers shown

Title
Graft: Efficient Inference Serving for Hybrid Deep Learning with SLO Guarantees via DNN Re-alignment Jing Wu Lin Wang Qirui Jin Fangming Liu 23 11 0 17 Dec 2023
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition Samuel Horváth Stefanos Laskaridis Shashank Rajput Hongyi Wang BDL 32 4 0 28 Aug 2023
Mobile Foundation Model as Firmware Jinliang Yuan Chenchen Yang Dongqi Cai Shihe Wang Xin Yuan ... Di Zhang Hanzi Mei Xianqing Jia Shangguang Wang Mengwei Xu 37 19 0 28 Aug 2023
Green Federated Learning Ashkan Yousefpour Sheng Guo Ashish Shenoy Sayan Ghosh Pierre Stock Kiwan Maeng Schalk-Willem Kruger Michael G. Rabbat Carole-Jean Wu Ilya Mironov FedML AI4CE 36 10 0 26 Mar 2023
NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution Stylianos I. Venieris Mario Almeida Royson Lee Nicholas D. Lane SupR 10 4 0 15 Dec 2022
Taxonomic Classification of IoT Smart Home Voice Control M. Hewitt H. Cunningham 11 1 0 24 Oct 2022
The Future of Consumer Edge-AI Computing Stefanos Laskaridis Stylianos I. Venieris Alexandros Kouris Rui Li Nicholas D. Lane 39 8 0 19 Oct 2022
Edge Security: Challenges and Issues Xin Jin Charalampos Katsis Fan Sang Jiahao Sun A. Kundu Ramana Rao Kompella 39 8 0 14 Jun 2022
Automation Slicing and Testing for in-App Deep Learning Models Hao Wu Yuhang Gong Xiaopeng Ke Hanzhong Liang Minghao Li Fengyuan Xu Yunxin Liu Sheng Zhong 41 1 0 15 May 2022
EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers Junting Pan Adrian Bulat Fuwen Tan Xiatian Zhu L. Dudziak Hongsheng Li Georgios Tzimiropoulos Brais Martínez ViT 31 180 0 06 May 2022
Benchmarking of DL Libraries and Models on Mobile Devices Qiyang Zhang Xiang Li Xiangying Che Xiao Ma Ao Zhou Mengwei Xu Shangguang Wang Yun Ma Xuanzhe Liu 25 48 0 14 Feb 2022
DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device Mario Almeida Stefanos Laskaridis Stylianos I. Venieris Ilias Leontiadis Nicholas D. Lane 13 36 0 20 Apr 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 176 267 0 26 Feb 2021
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications Matthias Paulik M. Seigel Henry Mason Dominic Telaar Joris Kluivers ... Dominic Hughes O. Javidbakht Fei Dong Rehan Rishi Stanley Hung FedML 175 126 0 16 Feb 2021
It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation Ilias Leontiadis Stefanos Laskaridis Stylianos I. Venieris Nicholas D. Lane 63 29 0 02 Feb 2021
Scaling Up Online Speech Recognition Using ConvNets Vineel Pratap Qiantong Xu Jacob Kahn Gilad Avidov Tatiana Likhomanenko Awni Y. Hannun Vitaliy Liptchinsky Gabriel Synnaeve R. Collobert 149 38 0 27 Jan 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,561 0 17 Apr 2017