129 citations · 718 across the 31 of their papers we have counts for
5 papers · 1 filter
Technical Report: Combining knowledge from Transfer Learning during training and Wide Resnets
Wolfgang Fuhl
In this report, we combine the idea of Wide ResNets and transfer learning to optimize the architecture of deep neural networks. The first improvement of the architecture is the use…
Maximum and Leaky Maximum Propagation
Wolfgang Fuhl
In this work, we present an alternative to conventional residual connections, which is inspired by maxout nets. This means that instead of the addition in residual connections, our…
Explainable Online Validation of Machine Learning Models for Practical Applications
Wolfgang Fuhl, Yao Rong, Thomas Motz +4
We present a reformulation of the regression and classification, which aims to validate the result of a machine learning algorithm. Our reformulation simplifies the original proble…
Reinforcement learning for the privacy preservation and manipulation of eye tracking data
Wolfgang Fuhl, Efe Bozkir, Enkelejda Kasneci
In this paper, we present an approach based on reinforcement learning for eye tracking data manipulation. It is based on two opposing agents, where one tries to classify the data c…
Training Decision Trees as Replacement for Convolution Layers
Wolfgang Fuhl, Gjergji Kasneci, Wolfgang Rosenstiel +1
We present an alternative layer to convolution layers in convolutional neural networks (CNNs). Our approach reduces the complexity of convolutions by replacing it with binary decis…