no code implementations • 22 Jan 2024 • Yao Lu, Hiram Rayo Torres Rodriguez, Sebastian Vogel, Nick van de Waterlaat, Pavol Jancura
Since models are typically quantized for edge deployment, recent work has investigated quantization-aware NAS (QA-NAS) to search for highly accurate and efficient quantized models.
no code implementations • 27 Jan 2023 • David van Son, Floran de Putter, Sebastian Vogel, Henk Corporaal
Bayesian Optimization Mixed-Precision Neural Architecture Search (BOMP-NAS) is an approach to quantization-aware neural architecture search (QA-NAS) that leverages both Bayesian optimization (BO) and mixed-precision quantization (MP) to efficiently search for compact, high performance deep neural networks.
no code implementations • 25 Oct 2019 • Michael J. Klaiber, Sebastian Vogel, Axel Acosta, Robert Korn, Leonardo Ecco, Kristine Back, Andre Guntoro, Ingo Feldner
End-to-end performance estimation and measurement of deep neural network (DNN) systems become more important with increasing complexity of DNN systems consisting of hardware and software components.
no code implementations • 30 Sep 2019 • Christoph Schorn, Thomas Elsken, Sebastian Vogel, Armin Runge, Andre Guntoro, Gerd Ascheid
It is thus desirable to exploit optimization potential for error resilience and efficiency also at the algorithmic side, e. g., by optimizing the architecture of the DNN.
no code implementations • 20 Nov 2016 • Sebastian Vogel, Christoph Schorn, Andre Guntoro, Gerd Ascheid
Recently published methods enable training of bitwise neural networks which allow reduced representation of down to a single bit per weight.