Memory- and Communication-Aware Model Compression for Distributed Deep
Learning Inference on IoT

Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT

26 July 2019

Kartikeya Bhardwaj

Papers citing "Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT"

17 / 17 papers shown

Title
Knowledge Distillation: Enhancing Neural Network Compression with Integrated Gradients David E. Hernandez J. Chang Torbjörn E. M. Nordling 58 0 0 17 Mar 2025
DistrEE: Distributed Early Exit of Deep Neural Network Inference on Edge Devices Xian Peng Xin Wu Lianming Xu Li Wang Aiguo Fei 36 0 0 06 Feb 2025
Failure-Resilient Distributed Inference with Model Compression over Heterogeneous Edge Devices Li Wang Liang Li Lianming Xu Xian Peng Aiguo Fei 20 2 0 20 Jun 2024
Chrion: Optimizing Recurrent Neural Network Inference by Collaboratively Utilizing CPUs and GPUs Zinuo Cai Hao Wang Tao Song Yang Hua Ruhui Ma Haibing Guan GNN 11 0 0 21 Jul 2023
A Theory of I/O-Efficient Sparse Neural Network Inference Niels Gleinig Tal Ben-Nun Torsten Hoefler 27 0 0 03 Jan 2023
Bandwidth-efficient distributed neural network architectures with application to body sensor networks Thomas Strypsteen Alexander Bertrand 17 1 0 14 Oct 2022
Jack and Masters of all Trades: One-Pass Learning Sets of Model Sets From Large Pre-Trained Models Han Xiang Choong Yew-Soon Ong Abhishek Gupta Caishun Chen Ray Lim 27 4 0 02 May 2022
DistrEdge: Speeding up Convolutional Neural Network Inference on Distributed Edge Devices Xueyu Hou Yongjie Guan Tao Han Ning Zhang 24 41 0 03 Feb 2022
ParaDiS: Parallelly Distributable Slimmable Neural Networks A. Ozerov Anne Lambert S. Kumaraswamy UQCV MoE 37 1 0 06 Oct 2021
An improved LogNNet classifier for IoT application Hanif Heidari Andrei Velichko 17 10 0 30 May 2021
Packet-Loss-Tolerant Split Inference for Delay-Sensitive Deep Learning in Lossy Wireless Networks Sohei Itahara Takayuki Nishio Koji Yamamoto 25 15 0 28 Apr 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 21 38 0 20 Mar 2021
Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning Hongseok Namkoong Sam Daulton E. Bakshy OffRL 16 6 0 29 Nov 2020
New Directions in Distributed Deep Learning: Bringing the Network at Forefront of IoT Design Kartikeya Bhardwaj Wei Chen R. Marculescu GNN 11 7 0 25 Aug 2020
Communication-Efficient Edge AI: Algorithms and Systems Yuanming Shi Kai Yang Tao Jiang Jun Zhang Khaled B. Letaief GNN 29 327 0 22 Feb 2020
EdgeAI: A Vision for Deep Learning in IoT Era Kartikeya Bhardwaj Naveen Suda R. Marculescu 14 12 0 23 Oct 2019
Distributed Deep Convolutional Neural Networks for the Internet-of-Things Simone Disabato M. Roveri Cesare Alippi 24 47 0 02 Aug 2019