Search Results for author: Karsten Müller

Found 4 papers, 0 papers with code

A Privacy Preserving System for Movie Recommendations Using Federated Learning

no code implementations7 Mar 2023 David Neumann, Andreas Lutz, Karsten Müller, Wojciech Samek

A recent distributed learning scheme called federated learning has made it possible to learn from personal user data without its central collection.

Federated Learning Privacy Preserving +2

FedAUXfdp: Differentially Private One-Shot Federated Distillation

no code implementations30 May 2022 Haley Hoech, Roman Rischke, Karsten Müller, Wojciech Samek

Federated learning suffers in the case of non-iid local datasets, i. e., when the distributions of the clients' data are heterogeneous.

Federated Learning

Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning

no code implementations9 Apr 2022 Daniel Becking, Heiner Kirchhoffer, Gerhard Tech, Paul Haase, Karsten Müller, Heiko Schwarz, Wojciech Samek

Federated learning (FL) scenarios inherently generate a large communication overhead by frequently transmitting neural network updates between clients and server.

Federated Learning

ECQ$^{\text{x}}$: Explainability-Driven Quantization for Low-Bit and Sparse DNNs

no code implementations9 Sep 2021 Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Müller, Sebastian Lapuschkin

The remarkable success of deep neural networks (DNNs) in various applications is accompanied by a significant increase in network parameters and arithmetic operations.

Explainable Artificial Intelligence (XAI) Quantization

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