DeepIoT: Compressing Deep Neural Network Structures for Sensing Systems
with a Compressor-Critic Framework

DeepIoT: Compressing Deep Neural Network Structures for Sensing Systems with a Compressor-Critic Framework

5 June 2017

Tarek F. Abdelzaher

Papers citing "DeepIoT: Compressing Deep Neural Network Structures for Sensing Systems with a Compressor-Critic Framework"

13 / 13 papers shown

Title
Designing and Training of Lightweight Neural Networks on Edge Devices using Early Halting in Knowledge Distillation Rahul Mishra Hari Prabhat Gupta 27 8 0 30 Sep 2022
Distributed Training for Deep Learning Models On An Edge Computing Network Using ShieldedReinforcement Learning Tanmoy Sen Haiying Shen OffRL 11 5 0 01 Jun 2022
Machine Learning for Microcontroller-Class Hardware: A Review Swapnil Sayan Saha S. Sandha Mani B. Srivastava 19 117 0 29 May 2022
SmartDet: Context-Aware Dynamic Control of Edge Task Offloading for Mobile Object Detection Davide Callegaro Francesco Restuccia Marco Levorato 14 3 0 11 Jan 2022
MOHAQ: Multi-Objective Hardware-Aware Quantization of Recurrent Neural Networks Nesma M. Rezk Tomas Nordstrom D. Stathis Z. Ul-Abdin E. Aksoy A. Hemani MQ 20 1 0 02 Aug 2021
Compacting Deep Neural Networks for Internet of Things: Methods and Applications Ke Zhang Hanbo Ying Hongning Dai Lin Li Yuangyuang Peng Keyi Guo Hongfang Yu 16 38 0 20 Mar 2021
On Lightweight Privacy-Preserving Collaborative Learning for Internet of Things by Independent Random Projections Linshan Jiang Rui Tan Xin Lou Guosheng Lin 14 12 0 11 Dec 2020
Robustness and Transferability of Universal Attacks on Compressed Models Alberto G. Matachana Kenneth T. Co Luis Muñoz-González David Martínez Emil C. Lupu AAML 16 10 0 10 Dec 2020
Bringing AI To Edge: From Deep Learning's Perspective Di Liu Hao Kong Xiangzhong Luo Weichen Liu Ravi Subramaniam 42 116 0 25 Nov 2020
Jointly Sparse Signal Recovery and Support Recovery via Deep Learning with Applications in MIMO-based Grant-Free Random Access Ying Cui Shuaichao Li Wanqing Zhang 13 61 0 05 Aug 2020
Model Pruning Enables Efficient Federated Learning on Edge Devices Yuang Jiang Shiqiang Wang Victor Valls Bongjun Ko Wei-Han Lee Kin K. Leung Leandros Tassiulas 30 443 0 26 Sep 2019
Machine Learning at the Network Edge: A Survey M. G. Sarwar Murshed Chris Murphy Daqing Hou Nazar Khan Ganesh Ananthanarayanan Faraz Hussain 30 378 0 31 Jul 2019
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 197 745 0 06 Jun 2015