no code implementations • 25 Jan 2022 • Johanna Rock, Wolfgang Roth, Mate Toth, Paul Meissner, Franz Pernkopf
We analyze the quantization of (i) weights and (ii) activations of different CNN-based model architectures.
no code implementations • 14 Apr 2021 • David Peter, Wolfgang Roth, Franz Pernkopf
This paper introduces neural architecture search (NAS) for the automatic discovery of end-to-end keyword spotting (KWS) models in limited resource environments.
Ranked #15 on Keyword Spotting on Google Speech Commands (Google Speech Commands V2 12 metric)
2 code implementations • 18 Dec 2020 • David Peter, Wolfgang Roth, Franz Pernkopf
This paper introduces neural architecture search (NAS) for the automatic discovery of small models for keyword spotting (KWS) in limited resource environments.
no code implementations • 25 Nov 2020 • Johanna Rock, Wolfgang Roth, Paul Meissner, Franz Pernkopf
Radar sensors are crucial for environment perception of driver assistance systems as well as autonomous vehicles.
1 code implementation • 22 Oct 2020 • Wolfgang Roth, Günther Schindler, Holger Fröning, Franz Pernkopf
We present two methods to reduce the complexity of Bayesian network (BN) classifiers.
1 code implementation • 21 Aug 2020 • Wolfgang Roth, Franz Pernkopf
Learning the structure of Bayesian networks is a difficult combinatorial optimization problem.
no code implementations • 22 Jul 2020 • Lukas Pfeifenberger, Matthias Zöhrer, Günther Schindler, Wolfgang Roth, Holger Fröning, Franz Pernkopf
While machine learning techniques are traditionally resource intensive, we are currently witnessing an increased interest in hardware and energy efficient approaches.
no code implementations • 7 Jan 2020 • Wolfgang Roth, Günther Schindler, Bernhard Klein, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani
While machine learning is traditionally a resource intensive task, embedded systems, autonomous navigation, and the vision of the Internet of Things fuel the interest in resource-efficient approaches.
no code implementations • 10 Jul 2019 • Bernhard K. Aichernig, Roderick Bloem, Masoud Ebrahimi, Martin Horn, Franz Pernkopf, Wolfgang Roth, Astrid Rupp, Martin Tappler, Markus Tranninger
Therefore, there is considerable interest in learning such hybrid behavior by means of machine learning which requires sufficient and representative training data covering the behavior of the physical system adequately.
no code implementations • 12 Jun 2019 • Guenther Schindler, Wolfgang Roth, Franz Pernkopf, Holger Froening
As a result, PSP maintains prediction performance, creates a substantial amount of sparsity that is structured and, thus, easy and efficient to map to a variety of massively parallel processors, which are mandatory for utmost compute power and energy efficiency.
no code implementations • ICLR 2019 • Günther Schindler, Wolfgang Roth, Franz Pernkopf, Holger Fröning
In this work we propose a method for weight and activation quantization that is scalable in terms of quantization levels (n-ary representations) and easy to compute while maintaining the performance close to full-precision CNNs.
no code implementations • 5 Dec 2018 • Franz Pernkopf, Wolfgang Roth, Matthias Zoehrer, Lukas Pfeifenberger, Guenther Schindler, Holger Froening, Sebastian Tschiatschek, Robert Peharz, Matthew Mattina, Zoubin Ghahramani
In that way, we provide an extensive overview of the current state-of-the-art of robust and efficient machine learning for real-world systems.
no code implementations • ICLR 2018 • Wolfgang Roth, Franz Pernkopf
The increasing demand for neural networks (NNs) being employed on embedded devices has led to plenty of research investigating methods for training low precision NNs.