The Ramifications of Making Deep Neural Networks Compact

26 June 2020

Papers citing "The Ramifications of Making Deep Neural Networks Compact"

9 / 9 papers shown

Title
Enabling Resource-efficient AIoT System with Cross-level Optimization: A survey Sicong Liu Bin Guo Cheng Fang Ziqi Wang Shiyan Luo Zimu Zhou Zhiwen Yu AI4CE 31 22 0 27 Sep 2023
Machine Learning for Microcontroller-Class Hardware: A Review Swapnil Sayan Saha S. Sandha Mani B. Srivastava 21 118 0 29 May 2022
Deep neural networks with controlled variable selection for the identification of putative causal genetic variants P. H. Kassani Fred Lu Yann Le Guen Zihuai He 18 12 0 29 Sep 2021
AdaSpring: Context-adaptive and Runtime-evolutionary Deep Model Compression for Mobile Applications Sicong Liu Bin Guo Ke Ma Zhiwen Yu Junzhao Du 14 9 0 28 Jan 2021
Going Beyond Classification Accuracy Metrics in Model Compression Vinu Joseph Shoaib Ahmed Siddiqui Aditya Bhaskara Ganesh Gopalakrishnan Saurav Muralidharan M. Garland Sheraz Ahmed Andreas Dengel 42 17 0 03 Dec 2020
Modeling Data Reuse in Deep Neural Networks by Taking Data-Types into Cognizance N. Jha Sparsh Mittal 17 16 0 06 Aug 2020
DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs N. Jha Sparsh Mittal Binod Kumar Govardhan Mattela AAML 13 12 0 30 Jul 2020
E2GC: Energy-efficient Group Convolution in Deep Neural Networks N. Jha Rajat Saini Subhrajit Nag Sparsh Mittal 6 3 0 26 Jun 2020
NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications Tien-Ju Yang Andrew G. Howard Bo Chen Xiao Zhang Alec Go Mark Sandler Vivienne Sze Hartwig Adam 90 515 0 09 Apr 2018