Prof. Dr. Asja Fischer

Full Professor
Faculty of Mathematics
Ruhr-Universität Bochum

Profiles: LinkedIn, Google Scholar, DBLP

Office: IB 3/153
Universitätsstraße 150
44801 Bochum, Germany

Short CV


Note: I recently moved to Ruhr-University Bochum where I am Assistant Professor for Machine Learning now! I am still looking for a PhD student 🙂


Dr. Asja Fischer is a Assistant Professor at the Computer Science Department III of the University of Bonn. Before, she was a post-doctoral researcher at the Montreal Institute for Machine Learning (MILA). Between 2010 and end of 2014, Asja was employed both at the Institute for Neural Computation at the Ruhr-University Bochum and the Department of Computer Science at the University of Copenhagen working on her PhD in Machine Learning, which she defended in Copenhagen in 2014. Before, she studied Biology. Bioinformatics, Mathematics and Cognitive Science at the Ruhr-University Bochum, the Universidade de Lisboa and the University of Osnabrück.

Research Interests


  • Machine Learning
  • Deep Learning
  • Probabilistic Models
  • Sampling Techniques
  • Big Data

Teaching


Winter 2017

  • Lecture “Knowledge Graph Analysis”
  • Exercise “Knowledge Graph Analysis”
  • Seminar “Knowledge Graph Analysis”

Summer 2017

  • Lab “Deep Learning”
  • Seminar “Deep Learning”

Winter 2016

  • Lecture “Knowledge Graph Analysis”
  • Exercise “Knowledge Graph Analysis”
  • Seminar “Knowledge Graph Analysis”

Publications

54 entries « 2 of 2 »

2012

Fischer, Asja; Igel, Christian

An Introduction to Restricted Boltzmann Machines Inproceedings

In: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Buenos Aires, Argentina, September 3-6, 2012. Proceedings, pp. 14–36, Springer, 2012.

Links | BibTeX

2011

Fischer, Asja; Igel, Christian

Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives Inproceedings

In: ESANN 2011, 19th European Symposium on Artificial Neural Networks, Bruges, Belgium, April 27-29, 2011, Proceedings, 2011.

Links | BibTeX

Fischer, Asja; Igel, Christian

Bounding the Bias of Contrastive Divergence Learning Journal Article

In: Neural Computation, 23 (3), pp. 664–673, 2011.

Links | BibTeX

2010

Fischer, Asja; Igel, Christian

Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines Inproceedings

In: Artificial Neural Networks - ICANN 2010 - 20th International Conference, Thessaloniki, Greece, September 15-18, 2010, Proceedings, Part III, pp. 208–217, Springer, 2010.

Links | BibTeX

54 entries « 2 of 2 »