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Thomas Dittrich 0001

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affiliation: TU Vienna, Institute of Telecommunications, Austria
affiliation: Alpen-Adria University, Klagenfurt, Austria

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2020 – today

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2023
[c10]
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  - conf/icassp/MatzVD23
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Gerald Matz, Claudio Verardo, Thomas Dittrich:
Efficient Learning of Balanced Signature Graphs. ICASSP 2023: 1-5
2022
[c9]
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Gerald Matz, Thomas Dittrich:
Signature Graphs - Fundamentals, Learning, and Clustering. IEEECONF 2022: 235-239
2021
[c8]
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Thomas Dittrich, Gerald Matz:
Non-Convex Total Variation Minimization for Signed Graph Cut Clustering. ACSCC 2021: 1307-1311
[c7]
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Thomas Dittrich, Gerald Matz:
A Maximum A Posteriori Relaxation For Clustering The Labeled Stochastic Block Model. EUSIPCO 2021: 2194-2198
2020
[j2]
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Thomas Dittrich, Gerald Matz:
Signal Processing on Signed Graphs: Fundamentals and Potentials. IEEE Signal Process. Mag. 37(6): 86-98 (2020)
[c6]
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Thomas Dittrich, Gerald Matz:
Unsupervised Clustering on Signed Graphs with Unknown Number of Clusters. EUSIPCO 2020: 1060-1064
[c5]
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Gerald Matz, Thomas Dittrich:
Learning Signed Graphs from Data. ICASSP 2020: 5570-5574

2010 – 2019

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2019
[c4]
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Peter Berger, Thomas Dittrich, Gabor Hannak, Gerald Matz:
Semi-supervised Multiclass Clustering Based on Signed Total Variation. ICASSP 2019: 4953-4957
2018
[j1]
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Martin Klaus Müller, Fjolla Ademaj, Thomas Dittrich, Agnes Fastenbauer, Blanca Ramos Elbal, Armand Nabavi, Lukas Nagel, Stefan Schwarz, Markus Rupp:
Flexible multi-node simulation of cellular mobile communications: the Vienna 5G System Level Simulator. EURASIP J. Wirel. Commun. Netw. 2018: 227 (2018)
[c3]
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Thomas Dittrich, Peter Berger, Gerald Matz:
Semi-Supervised Spectral Clustering Using the Signed Laplacian. ACSSC 2018: 1413-1417
[c2]
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Peter Berger, Thomas Dittrich, Gerald Matz:
Semi-Supervised Clustering Based on Signed Total Variation. GlobalSIP 2018: 793-797
2017
[c1]
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Thomas Dittrich, Martin Taranetz, Markus Rupp:
An Efficient Method for Avoiding Shadow Fading Maps in System Level Simulations. WSA 2017: 1-8

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