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Machine Learning Group

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Department of Computer Science

University of Copenhagen

 

Sigurdsgade 41

2200 København N

Denmark

 

Office: 1.08

 

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Fabian Gieseke

I am an assistant professor for Large-Scale Data Science at the Department of Computer Science of the University of Copenhagen. I have received my Diploma degrees in Mathematics and Computer Science from the Westfälische Wilhelms-Universität Münster (Germany) and my PhD in Computer Science from the Carl von Ossietzky Universität Oldenburg (Germany).

 

My research interests include various topics in the field of data analysis (data mining, machine learning, algorithm engineering, ...) with applications for challenging large-scale scenarios in astronomy, text mining, energy systems, and others.

 

For an overview of past and current research projects, see here.

 

 

Selected Publications

  1. Fabian Gieseke, Steven Bloemen, Cas Bogaard, Tom Heskes, Jonas Kindler, Richard A Scalzo, Valerio A R M Ribeiro, Jan Roestel, Paul J Groot, Fang Yuan, Anais Möller, and Brad E Tucker. Convolutional Neural Networks for Transient Candidate Vetting in Large-Scale Surveys. Monthly Notices of the Royal Astronomical Society (MNRAS), 2017.  Accepted 

  2. Fabian Gieseke, Cosmin Oancea, and Christian Igel. bufferkdtree: A Python library for massive nearest neighbor queries on multi-many-core devices. Knowledge-Based Systems, 2017.  In press, online first  

  3. Fabian Gieseke, Tapio Pahikkala, and Tom Heskes. Batch Steepest-Descent-Mildest-Ascent for Interactive Maximum Margin Clustering. In Proceedings of the 14th International Symposium on Intelligent Data Analysis. Advances in Intelligent Data Analysis XIV 9385. 2015, 95–107.   

  4. Fabian Gieseke, Justin Heinermann, Cosmin Oancea, and Christian Igel. Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs. In Proceedings of the 31st International Conference on Machine Learning (ICML) 32(1). 2014, 172-180.   

  5. Fabian Gieseke, Tapio Pahikkala, and Christian Igel. Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification. In Proceedings of the 5th Asian Conference on Machine Learning (ACML). 2013, 62-71.   

  6. Kai Lars Polsterer, Peter Zinn, and Fabian Gieseke. Finding New High-Redshift Quasars by Asking the Neighbours. Monthly Notices of the Royal Astronomical Society (MNRAS) 428(1):226-235, 2013.   

  7. Tapio Pahikkala, Antti Airola, Fabian Gieseke, and Oliver Kramer. Unsupervised Multi-Class Regularized Least-Squares Classification. In Proceedings of the 12th IEEE International Conference on Data Mining (ICDM). 2012, 585-594.   

  8. Fabian Gieseke, Gabriel Moruz, and Jan Vahrenhold. Resilient K-d Trees: K-Means in Space Revisited. In Proceedings of the 10th IEEE International Conference on Data Mining (ICDM). 2010, 815-820.   

  9. Fabian Gieseke, Joachim Gudmundsson, and Jan Vahrenhold. Pruning Spanners and Constructing Well-Separated Pair Decompositions in the Presence of Memory Hierarchies. Journal of Discrete Algorithms (JDA) 8(3):259-272, 2010.   

  10. Fabian Gieseke, Tapio Pahikkala, and Oliver Kramer. Fast Evolutionary Maximum Margin Clustering. In Proceedings of the 26th International Conference on Machine Learning (ICML). 2009, 361-368.   

 

A complete list of my publications can be found here.

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