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BottleFit: Learning Compressed Representations in Deep Neural Networks
  for Effective and Efficient Split Computing
v1v2 (latest)

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

IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2022
7 January 2022
Yoshitomo Matsubara
Davide Callegaro
Sameer Singh
Marco Levorato
Francesco Restuccia
ArXiv (abs)PDFHTML

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

19 / 19 papers shown
AVERY: Adaptive VLM Split Computing through Embodied Self-Awareness for Efficient Disaster Response Systems
AVERY: Adaptive VLM Split Computing through Embodied Self-Awareness for Efficient Disaster Response Systems
Rajat Bhattacharjya
Sing-Yao Wu
Hyunwoo Oh
Chaewon Nam
Suyeon Koo
Mohsen Imani
Elaheh Bozorgzadeh
N. Dutt
VLM
114
1
0
22 Nov 2025
Semantic Multiplexing
Semantic Multiplexing
Mohammad Abdi
Francesca Meneghello
Francesco Restuccia
93
0
0
16 Nov 2025
3D Point Cloud Object Detection on Edge Devices for Split Computing
3D Point Cloud Object Detection on Edge Devices for Split Computing
Taisuke Noguchi
Takuya Azumi
3DPC
166
5
0
04 Nov 2025
Why Should the Server Do It All?: A Scalable, Versatile, and Model-Agnostic Framework for Server-Light DNN Inference over Massively Distributed Clients via Training-Free Intermediate Feature Compression
Why Should the Server Do It All?: A Scalable, Versatile, and Model-Agnostic Framework for Server-Light DNN Inference over Massively Distributed Clients via Training-Free Intermediate Feature Compression
Mingyu Sung
Suhwan Im
Daeho Bang
Il-Min Kim
Sangseok Yun
Jae-Mo Kang
95
0
0
03 Nov 2025
An Efficient Semantic Segmentation Decoder for In-Car or Distributed Applications
An Efficient Semantic Segmentation Decoder for In-Car or Distributed Applications
Danish Nazir
Gowtham Sai Inti
Timo Bartels
Jan Piewek
Thorsten Bagdonat
Tim Fingscheidt
167
0
0
19 Oct 2025
On the Impact of White-box Deployment Strategies for Edge AI on Latency and Model Performance
On the Impact of White-box Deployment Strategies for Edge AI on Latency and Model Performance
Jaskirat Singh
Bram Adams
Ahmed E. Hassan
VLM
402
1
0
01 Nov 2024
EdgeRL: Reinforcement Learning-driven Deep Learning Model Inference
  Optimization at Edge
EdgeRL: Reinforcement Learning-driven Deep Learning Model Inference Optimization at EdgeConference on Network and Service Management (CNSM), 2024
Motahare Mounesan
Xiaojie Zhang
S. Debroy
178
5
0
16 Oct 2024
NaviSplit: Dynamic Multi-Branch Split DNNs for Efficient Distributed
  Autonomous Navigation
NaviSplit: Dynamic Multi-Branch Split DNNs for Efficient Distributed Autonomous NavigationIEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2024
Timothy K Johnsen
Ian Harshbarger
Zixia Xia
Marco Levorato
172
3
0
18 Jun 2024
Texture-guided Coding for Deep Features
Texture-guided Coding for Deep Features
Lei Xiong
Xin Luo
Zihao Wang
Chaofan He
Shuyuan Zhu
Bing Zeng
3DH
160
1
0
30 May 2024
On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance
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
393
5
0
25 Mar 2024
Resilience of Entropy Model in Distributed Neural Networks
Resilience of Entropy Model in Distributed Neural Networks
Milin Zhang
Mohammad Abdi
Shahriar Rifat
Francesco Restuccia
AAML
280
3
0
01 Mar 2024
SAWEC: Sensing-Assisted Wireless Edge Computing
SAWEC: Sensing-Assisted Wireless Edge Computing
Khandaker Foysal Haque
Francesca Meneghello
Md. Ebtidaul Karim
Francesco Restuccia
212
3
0
15 Feb 2024
Adaptive Compression-Aware Split Learning and Inference for Enhanced
  Network Efficiency
Adaptive Compression-Aware Split Learning and Inference for Enhanced Network Efficiency
Akrit Mudvari
Antero Vainio
Iason Ofeidis
Sasu Tarkoma
Leandros Tassiulas
361
11
0
09 Nov 2023
torchdistill Meets Hugging Face Libraries for Reproducible, Coding-Free
  Deep Learning Studies: A Case Study on NLP
torchdistill Meets Hugging Face Libraries for Reproducible, Coding-Free Deep Learning Studies: A Case Study on NLP
Yoshitomo Matsubara
VLM
251
1
0
26 Oct 2023
SplitEE: Early Exit in Deep Neural Networks with Split Computing
SplitEE: Early Exit in Deep Neural Networks with Split ComputingInternational Conference on AI-ML-Systems (ICA), 2023
Divya J. Bajpai
Vivek K. Trivedi
S. L. Yadav
M. Hanawal
254
16
0
17 Sep 2023
Split-Et-Impera: A Framework for the Design of Distributed Deep Learning
  Applications
Split-Et-Impera: A Framework for the Design of Distributed Deep Learning ApplicationsIEEE Workshop on Design and Diagnostics of Electronic Circuits and Systems (DDECS), 2023
Luigi Capogrosso
Federico Cunico
M. Lora
Marco Cristani
Franco Fummi
D. Quaglia
MoE
121
5
0
22 Mar 2023
Slimmable Quantum Federated Learning
Slimmable Quantum Federated Learning
Won Joon Yun
Jae Pyoung Kim
Soyi Jung
Jihong Park
M. Bennis
Joongheon Kim
364
43
0
20 Jul 2022
SC2 Benchmark: Supervised Compression for Split Computing
SC2 Benchmark: Supervised Compression for Split Computing
Yoshitomo Matsubara
Ruihan Yang
Marco Levorato
Stephan Mandt
329
24
0
16 Mar 2022
Split Computing and Early Exiting for Deep Learning Applications: Survey
  and Research Challenges
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research ChallengesACM Computing Surveys (CSUR), 2021
Yoshitomo Matsubara
Marco Levorato
Francesco Restuccia
404
276
0
08 Mar 2021
1
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