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20212024
most citedUniversal Approximation Theorems of Fully Connected Binarized Neural Networks

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.DC2024

Eliminating Timing Anomalies in Scheduling Periodic Segmented Self-Suspending Tasks with Release Jitter

Ching-Chi Lin, Mario Günzel, Junjie Shi +3

Ensuring timing guarantees for every individual tasks is critical in real-time systems. Even for periodic tasks, providing timing guarantees for tasks with segmented self-suspendin…

cs.RO2024

Bridging the Gap between ROS~2 and Classical Real-Time Scheduling for Periodic Tasks

Harun Teper, Oren Bell, Mario Günzel +2

The Robot Operating System 2 (ROS~2) is a widely used middleware that provides software libraries and tools for developing robotic systems. In these systems, tasks are scheduled by…

cs.PF2024

Dawn of the Dead(line Misses): Impact of Job Dismiss on the Deadline Miss Rate

Jian-Jia Chen, Mario Günzel, Peter Bella +2

Occasional deadline misses are acceptable for soft real-time systems. Quantifying probabilistic and deterministic characteristics of deadline misses is therefore essential to ensur…

cs.DC2022

Parallel Path Progression DAG Scheduling

Niklas Ueter, Mario Günzel, Georg von der Brüggen +1

To satisfy the increasing performance needs of modern cyber-physical systems, multiprocessor architectures are increasingly utilized. To efficiently exploit their potential paralle…

cs.LG20211 cited

Universal Approximation Theorems of Fully Connected Binarized Neural Networks

Mikail Yayla, Mario Günzel, Burim Ramosaj +1

Neural networks (NNs) are known for their high predictive accuracy in complex learning problems. Beside practical advantages, NNs also indicate favourable theoretical properties su…