BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing

7 January 2022

Papers citing "BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing"

9 / 9 papers shown

Title
On the Impact of White-box Deployment Strategies for Edge AI on Latency and Model Performance Jaskirat Singh Bram Adams Ahmed E. Hassan VLM 43 0 0 01 Nov 2024
On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance Jaskirat Singh Emad Fallahzadeh Bram Adams Ahmed E. Hassan MQ 40 3 0 25 Mar 2024
SAWEC: Sensing-Assisted Wireless Edge Computing Khandaker Foysal Haque Francesca Meneghello Md. Ebtidaul Karim Francesco Restuccia 38 1 0 15 Feb 2024
Adaptive Compression-Aware Split Learning and Inference for Enhanced Network Efficiency Akrit Mudvari Antero Vainio Iason Ofeidis Sasu Tarkoma Leandros Tassiulas 29 3 0 09 Nov 2023
torchdistill Meets Hugging Face Libraries for Reproducible, Coding-Free Deep Learning Studies: A Case Study on NLP Yoshitomo Matsubara VLM 34 1 0 26 Oct 2023
SplitEE: Early Exit in Deep Neural Networks with Split Computing Divya J. Bajpai Vivek K. Trivedi S. L. Yadav M. Hanawal 28 5 0 17 Sep 2023
Slimmable Quantum Federated Learning Won Joon Yun Jae Pyoung Kim Soyi Jung Jihong Park M. Bennis Joongheon Kim 15 27 0 20 Jul 2022
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges Yoshitomo Matsubara Marco Levorato Francesco Restuccia 33 199 0 08 Mar 2021
Split Computing for Complex Object Detectors: Challenges and Preliminary Results Yoshitomo Matsubara Marco Levorato 46 24 0 27 Jul 2020