The Ramifications of Making Deep Neural Networks Compact

26 June 2020

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

8 / 8 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 86 22 0 27 Sep 2023
Machine Learning for Microcontroller-Class Hardware: A Review Swapnil Sayan Saha S. Sandha Mani B. Srivastava 72 125 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 99 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 46 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 67 17 0 03 Dec 2020
Modeling Data Reuse in Deep Neural Networks by Taking Data-Types into Cognizance N. Jha Sparsh Mittal 48 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 61 13 0 30 Jul 2020
E2GC: Energy-efficient Group Convolution in Deep Neural Networks N. Jha Rajat Saini Subhrajit Nag Sparsh Mittal 37 4 0 26 Jun 2020