9 citations · 9 across the 2 of their papers we have counts for
3 papers
cs.LG2018
Impact of Biases in Big Data
Patrick Glauner, Petko Valtchev, Radu State
The underlying paradigm of big data-driven machine learning reflects the desire of deriving better conclusions from simply analyzing more data, without the necessity of looking at…
cs.LG2017
Identifying Irregular Power Usage by Turning Predictions into Holographic Spatial Visualizations
Patrick Glauner, Niklas Dahringer, Oleksandr Puhachov +4
Power grids are critical infrastructure assets that face non-technical losses (NTL) such as electricity theft or faulty meters. NTL may range up to 40% of the total electricity dis…
cs.LG2015★ 9 cited
Comparison of Training Methods for Deep Neural Networks
Patrick O. Glauner
This report describes the difficulties of training neural networks and in particular deep neural networks. It then provides a literature review of training methods for deep neural…