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cs.LG2025
Optimizing Learned Image Compression on Scalar and Entropy-Constraint Quantization
Florian Borzechowski, Michael Schäfer, Heiko Schwarz +3
The continuous improvements on image compression with variational autoencoders have lead to learned codecs competitive with conventional approaches in terms of rate-distortion effi…
cs.LG2025
Efficient Federated Learning Tiny Language Models for Mobile Network Feature Prediction
Daniel Becking, Ingo Friese, Karsten Müller +4
In telecommunications, Autonomous Networks (ANs) automatically adjust configurations based on specific requirements (e.g., bandwidth) and available resources. These networks rely o…