Felix Sattler | DeepAI

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∙ 08/22/2023

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

The hearing loss of almost half a billion people is commonly treated wit...

0 Peter Udo Diehl, et al. ∙

∙ 06/27/2021

Reward-Based 1-bit Compressed Federated Distillation on Blockchain

The recent advent of various forms of Federated Knowledge Distillation (...

0 Leon Witt, et al. ∙

∙ 02/04/2021

FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning

Federated Distillation (FD) is a popular novel algorithmic paradigm for ...

13 Felix Sattler, et al. ∙

∙ 12/01/2020

Communication-Efficient Federated Distillation

Communication constraints are one of the major challenges preventing the...

0 Felix Sattler, et al. ∙

∙ 04/22/2020

Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements

Digital contact tracing approaches based on Bluetooth low energy (BLE) h...

13 Felix Sattler, et al. ∙

∙ 03/06/2020

Trends and Advancements in Deep Neural Network Communication

Due to their great performance and scalability properties neural network...

0 Felix Sattler, et al. ∙

∙ 10/04/2019

Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints

Federated Learning (FL) is currently the most widely adopted framework f...

42 Felix Sattler, et al. ∙

∙ 03/07/2019

Robust and Communication-Efficient Federated Learning from Non-IID Data

Federated Learning allows multiple parties to jointly train a deep learn...

12 Felix Sattler, et al. ∙

∙ 05/22/2018

Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication

Currently, progressively larger deep neural networks are trained on ever...

0 Felix Sattler, et al. ∙

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