34 citations · 113 across the 17 of their papers we have counts for
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cs.LG2023★ 34 cited
Hardware-Aware DNN Compression via Diverse Pruning and Mixed-Precision Quantization
Konstantinos Balaskas, Andreas Karatzas, Christos Sad +4
Deep Neural Networks (DNNs) have shown significant advantages in a wide variety of domains. However, DNNs are becoming computationally intensive and energy hungry at an exponential…
cs.LG2023
OmniBoost: Boosting Throughput of Heterogeneous Embedded Devices under Multi-DNN Workload
Andreas Karatzas, Iraklis Anagnostopoulos
Modern Deep Neural Networks (DNNs) exhibit profound efficiency and accuracy properties. This has introduced application workloads that comprise of multiple DNN applications, raisin…