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ORCIDPatrick O. Glauner
- > Home > Persons > Patrick O. Glauner
Publications
- 2018
[c6]Patrick O. Glauner, Petko Valtchev, Radu State:
Impact of Biases in Big Data. ESANN 2018- [i14]Patrick O. Glauner, Radu State, Petko Valtchev, Diogo Duarte:
On the Reduction of Biases in Big Data Sets for the Detection of Irregular Power Usage. CoRR abs/1801.05627 (2018) - [i13]Patrick O. Glauner, Petko Valtchev, Radu State:
Impact of Biases in Big Data. CoRR abs/1803.00897 (2018) - 2017
- [j1]Patrick O. Glauner, Jorge Augusto Meira
, Petko Valtchev, Radu State, Franck Bettinger:
The Challenge of Non-Technical Loss Detection Using Artificial Intelligence: A Survey. Int. J. Comput. Intell. Syst. 10(1): 760-775 (2017) - [c5]Patrick O. Glauner, Manxing Du, Victor Paraschiv, Andrey Boytsov, Isabel Lopez Andrade, Jorge Augusto Meira, Petko Valtchev, Radu State:
The Top 10 Topics in Machine Learning Revisited: A Quantitative Meta-Study. ESANN 2017 - [c3]Patrick O. Glauner, Niklas Dahringer, Oleksandr Puhachov, Jorge Augusto Meira, Petko Valtchev, Radu State, Diogo Duarte:
Identifying Irregular Power Usage by Turning Predictions into Holographic Spatial Visualizations. ICDM Workshops 2017: 258-265 - [i12]Patrick O. Glauner, Angelo Migliosi, Jorge Augusto Meira, Eric Aislan Antonelo, Petko Valtchev, Radu State, Franck Bettinger:
Is Big Data Sufficient for a Reliable Detection of Non-Technical Losses? CoRR abs/1702.03767 (2017) - [i11]Patrick O. Glauner, Manxing Du, Victor Paraschiv, Andrey Boytsov, Isabel Lopez Andrade, Jorge Augusto Meira, Petko Valtchev, Radu State:
The Top 10 Topics in Machine Learning Revisited: A Quantitative Meta-Study. CoRR abs/1703.10121 (2017) - [i10]Patrick O. Glauner, Niklas Dahringer, Oleksandr Puhachov, Jorge Augusto Meira, Petko Valtchev, Radu State, Diogo Duarte:
Identifying Irregular Power Usage by Turning Predictions into Holographic Spatial Visualizations. CoRR abs/1709.03008 (2017) - 2016
- [c2]Patrick O. Glauner, Jorge Augusto Meira, Lautaro Dolberg, Radu State, Franck Bettinger, Yves Rangoni:
Neighborhood features help detecting non-technical losses in big data sets. BDCAT 2016: 253-261 - [c1]Patrick O. Glauner, Andre Boechat, Lautaro Dolberg, Radu State, Franck Bettinger, Yves Rangoni, Diogo Duarte:
Large-scale detection of non-technical losses in imbalanced data sets. ISGT 2016: 1-5 - [i8]Patrick O. Glauner, Andre Boechat, Lautaro Dolberg, Radu State, Franck Bettinger, Yves Rangoni, Diogo Duarte:
Large-Scale Detection of Non-Technical Losses in Imbalanced Data Sets. CoRR abs/1602.08350 (2016) - [i7]Patrick O. Glauner, Andre Boechat, Lautaro Dolberg, Jorge Augusto Meira, Radu State, Franck Bettinger, Yves Rangoni, Diogo Duarte:
The Challenge of Non-Technical Loss Detection using Artificial Intelligence: A Survey. CoRR abs/1606.00626 (2016) - [i6]Patrick O. Glauner, Jorge Augusto Meira, Lautaro Dolberg, Radu State, Franck Bettinger, Yves Rangoni, Diogo Duarte:
Neighborhood Features Help Detecting Electricity Theft in Big Data Sets. CoRR abs/1607.00872 (2016)
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