6 citations · 11 across the 9 of their papers we have counts for
4 papers · 1 filter
HW-Aware Initialization of DNN Auto-Tuning to Improve Exploration Time and Robustness
Dennis Rieber, Moritz Reiber, Oliver Bringmann +1
The process of optimizing the latency of DNN operators with ML models and hardware-in-the-loop, called auto-tuning, has established itself as a pervasive method for the deployment…
On Resource-Efficient Bayesian Network Classifiers and Deep Neural Networks
Wolfgang Roth, Günther Schindler, Holger Fröning +1
We present two methods to reduce the complexity of Bayesian network (BN) classifiers. First, we introduce quantization-aware training using the straight-through gradient estimator…
Parameterized Structured Pruning for Deep Neural Networks
Guenther Schindler, Wolfgang Roth, Franz Pernkopf +1
As a result of the growing size of Deep Neural Networks (DNNs), the gap to hardware capabilities in terms of memory and compute increases. To effectively compress DNNs, quantizatio…
Efficient and Robust Machine Learning for Real-World Systems
Franz Pernkopf, Wolfgang Roth, Matthias Zoehrer +7
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 ef…