Felix Sattler

Orcid: 0000-0001-8869-282X

According to our database1, Felix Sattler authored at least 18 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Embedded 3D reconstruction of dynamic objects in real time for maritime situational awareness pictures.
Vis. Comput., February, 2024

2023
FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning.
IEEE Trans. Neural Networks Learn. Syst., September, 2023

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024.
CoRR, 2023

Deep learning-based denoising streamed from mobile phones improves speech-in-noise understanding for hearing aid users.
CoRR, 2023

A Maritime Situational Awareness Framework Using Dynamic 3D Reconstruction in Real-Time.
Proceedings of the 27th International Conference Information Visualisation, 2023

2022
CFD: Communication-Efficient Federated Distillation via Soft-Label Quantization and Delta Coding.
IEEE Trans. Netw. Sci. Eng., 2022

2021
Concepts for efficient, adaptive and robust deep learning from distributed data.
PhD thesis, 2021

Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization Under Privacy Constraints.
IEEE Trans. Neural Networks Learn. Syst., 2021

Reward-Based 1-bit Compressed Federated Distillation on Blockchain.
CoRR, 2021

2020
Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data.
IEEE Trans. Neural Networks Learn. Syst., 2020

Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements.
npj Digit. Medicine, 2020

Communication-Efficient Federated Distillation.
CoRR, 2020

Trends and Advancements in Deep Neural Network Communication.
CoRR, 2020

Deepcabac: Plug & Play Compression of Neural Network Weights and Weight Updates.
Proceedings of the IEEE International Conference on Image Processing, 2020

On the Byzantine Robustness of Clustered Federated Learning.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints.
CoRR, 2019

Robust and Communication-Efficient Federated Learning from Non-IID Data.
CoRR, 2019

Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication.
Proceedings of the International Joint Conference on Neural Networks, 2019


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