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

2021

Brügge, Kai; Fischer, Asja; Igel, Christian

On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions Inproceedings

In: The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, pp. 469–477, PMLR, 2021.

Links | BibTeX

Laszkiewicz, Mike; Lederer, Johannes; Fischer, Asja

Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery Inproceedings

In: The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, pp. 1864–1872, PMLR, 2021.

Links | BibTeX

Esteves, Diego; Marcelino, José; Chawla, Piyush; Fischer, Asja; Lehmann, Jens

ŐRUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data Inproceedings

In: Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021, Proceedings, pp. 89–100, Springer, 2021.

Links | BibTeX

Chakraborty, Nilesh; Lukovnikov, Denis; Maheshwari, Gaurav; Trivedi, Priyansh; Lehmann, Jens; Fischer, Asja

Introduction to neural network-based question answering over knowledge graphs Journal Article

In: Wiley Interdiscip. Rev. Data Min. Knowl. Discov., 11 (3), 2021.

Links | BibTeX

2020

Krause, Oswin; Fischer, Asja; Igel, Christian

Algorithms for estimating the partition function of restricted Boltzmann machines Journal Article

In: Artif. Intell., 278 , 2020.

Links | BibTeX

Krause, Oswin; Fischer, Asja; Igel, Christian

Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract) Inproceedings

In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020, pp. 5045–5049, ijcai.org, 2020.

Links | BibTeX

Ali, Mehdi; Berrendorf, Max; Hoyt, Charles Tapley; Vermue, Laurent; Galkin, Mikhail; Sharifzadeh, Sahand; Fischer, Asja; Tresp, Volker; Lehmann, Jens

Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework Miscellaneous

2020.

Links | BibTeX

Koitka, Sven; Kim, Moon S.; Qu, Ming; Fischer, Asja; Friedrich, Christoph M.; Nensa, Felix

Mimicking the radiologists' workflow: Estimating pediatric hand bone age with stacked deep neural networks Journal Article

In: Medical Image Anal., 64 , pp. 101743, 2020.

Links | BibTeX

Frank, Joel; Eisenhofer, Thorsten; Schönherr, Lea; Fischer, Asja; Kolossa, Dorothea; Holz, Thorsten

Leveraging Frequency Analysis for Đeep Fake Image Recognition Inproceedings

In: Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, pp. 3247–3258, PMLR, 2020.

Links | BibTeX

Däubener, Sina; Schönherr, Lea; Fischer, Asja; Kolossa, Dorothea

Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification Inproceedings

In: Interspeech 2020, 21st Annual Conference of the International Speech Communication Association, Virtual Event, Shanghai, China, 25-29 October 2020, pp. 4661–4665, ISCA, 2020.

Links | BibTeX

Frank, Joel; Eisenhofer, Thorsten; Schönherr, Lea; Fischer, Asja; Kolossa, Dorothea; Holz, Thorsten

Leveraging Frequency Analysis for Deep Fake Image Recognition Inproceedings

In: Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, pp. 3247–3258, PMLR, 2020.

Links | BibTeX

2019

ebski, Stanisław Jastrzk; Kenton, Zachary; Ballas, Nicolas; Fischer, Asja; Bengio, Yoshua; Storkey, Amos J.

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length Inproceedings

In: 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, OpenReview.net, 2019.

Links | BibTeX

Kristiadi, Agustinus; Khan, Mohammad Asif; Lukovnikov, Denis; Lehmann, Jens; Fischer, Asja

Incorporating Literals into Knowledge Graph Embeddings Inproceedings

In: The Semantic Web - ISWC 2019 - 18th International Semantic Web Conference, Auckland, New Zealand, October 26-30, 2019, Proceedings, Part I, pp. 347–363, Springer, 2019.

Links | BibTeX

Maheshwari, Gaurav; Trivedi, Priyansh; Lukovnikov, Denis; Chakraborty, Nilesh; Fischer, Asja; Lehmann, Jens

Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs Inproceedings

In: The Semantic Web - ISWC 2019 - 18th International Semantic Web Conference, Auckland, New Zealand, October 26-30, 2019, Proceedings, Part I, pp. 487–504, Springer, 2019.

Links | BibTeX

Lukovnikov, Denis; Fischer, Asja; Lehmann, Jens

Pretrained Transformers for Simple Question Answering over Knowledge Graphs Inproceedings

In: The Semantic Web - ISWC 2019 - 18th International Semantic Web Conference, Auckland, New Zealand, October 26-30, 2019, Proceedings, Part I, pp. 470–486, Springer, 2019.

Links | BibTeX

2018

Chaudhuri, Debanjan; Kristiadi, Agustinus; Lehmann, Jens; Fischer, Asja

Improving Response Selection in Multi-Turn Dialogue Systems by Incorporating Domain Knowledge Inproceedings

In: Proceedings of the 22nd Conference on Computational Natural Language Learning, CoNLL 2018, Brussels, Belgium, October 31 - November 1, 2018, pp. 497–507, Association for Computational Linguistics, 2018.

Links | BibTeX

ebski, Stanisław Jastrzk; Kenton, Zachary; Arpit, Devansh; Ballas, Nicolas; Fischer, Asja; Bengio, Yoshua; Storkey, Amos J.

Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio Inproceedings

In: Artificial Neural Networks and Machine Learning - ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III, pp. 392–402, Springer, 2018.

Links | BibTeX

ebski, Stanisław Jastrzk; Kenton, Zachary; Arpit, Devansh; Ballas, Nicolas; Fischer, Asja; Bengio, Yoshua; Storkey, Amos J.

Finding Flatter Minima with SGD Inproceedings

In: 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Workshop Track Proceedings, OpenReview.net, 2018.

Links | BibTeX

Petzka, Henning; Fischer, Asja; Lukovnikov, Denis

On the regularization of Wasserstein GANs Inproceedings

In: 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings, OpenReview.net, 2018.

Links | BibTeX

Krause, Oswin; Fischer, Asja; Igel, Christian

Population-Contrastive-Divergence: Does consistency help with RBM training? Journal Article

In: Pattern Recognit. Lett., 102 , pp. 1–7, 2018.

Links | BibTeX

2017

Krueger, David; Ballas, Nicolas; ebski, Stanisław Jastrzk; Arpit, Devansh; Kanwal, Maxinder S.; Maharaj, Tegan; Bengio, Emmanuel; Fischer, Asja; Courville, Aaron C.

Deep Nets Don't Learn via Memorization Inproceedings

In: 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Workshop Track Proceedings, OpenReview.net, 2017.

Links | BibTeX

Arpit, Devansh; ebski, Stanisław Jastrzk; Ballas, Nicolas; Krueger, David; Bengio, Emmanuel; Kanwal, Maxinder S.; Maharaj, Tegan; Fischer, Asja; Courville, Aaron C.; Bengio, Yoshua; Lacoste-Julien, Simon

A Closer Look at Memorization in Deep Networks Inproceedings

In: Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, pp. 233–242, PMLR, 2017.

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Lukovnikov, Denis; Fischer, Asja; Lehmann, Jens; Auer, Sören

Neural Network-based Question Answering over Knowledge Graphs on Word and Character Level Inproceedings

In: Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Perth, Australia, April 3-7, 2017, pp. 1211–1220, ACM, 2017.

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Weghenkel, Björn; Fischer, Asja; Wiskott, Laurenz

Graph-based predictable feature analysis Journal Article

In: Mach. Learn., 106 (9-10), pp. 1359–1380, 2017.

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Bengio, Yoshua; Mesnard, Thomas; Fischer, Asja; Zhang, Saizheng; Wu, Yuhuai

STDP-Compatible Approximation of Backpropagation in an Energy-Based Model Journal Article

In: Neural Computation, 29 (3), pp. 555–577, 2017.

Links | BibTeX

2016

Bornschein, Jörg; Shabanian, Samira; Fischer, Asja; Bengio, Yoshua

Bidirectional Helmholtz Machines Inproceedings

In: Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pp. 2511–2519, JMLR.org, 2016.

Links | BibTeX

Melchior, Jan; Fischer, Asja; Wiskott, Laurenz

How to Center Deep Boltzmann Machines Journal Article

In: J. Mach. Learn. Res., 17 , pp. 99:1–99:61, 2016.

Links | BibTeX

2015

Lee, Dong-Hyun; Zhang, Saizheng; Fischer, Asja; Bengio, Yoshua

Difference Target Propagation Inproceedings

In: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I, pp. 498–515, Springer, 2015.

Links | BibTeX

Fischer, Asja

Training Restricted Boltzmann Machines Journal Article

In: KI, 29 (4), pp. 441–444, 2015.

Links | BibTeX

Fischer, Asja; Igel, Christian

A bound for the convergence rate of parallel tempering for sampling restricted Boltzmann machines Journal Article

In: Theor. Comput. Sci., 598 , pp. 102–117, 2015.

Links | BibTeX

2014

Fischer, Asja; Igel, Christian

Training restricted Boltzmann machines: An introduction Journal Article

In: Pattern Recognit., 47 (1), pp. 25–39, 2014.

Links | BibTeX

2013

Krause, Oswin; Fischer, Asja; Glasmachers, Tobias; Igel, Christian

Approximation properties of DBNs with binary hidden units and real-valued visible units Inproceedings

In: Proceedings of the 30th International Conference on Machine Learning, ICML 2013, Atlanta, GA, USA, 16-21 June 2013, pp. 419–426, JMLR.org, 2013.

Links | BibTeX

Brügge, Kai; Fischer, Asja; Igel, Christian

The flip-the-state transition operator for restricted Boltzmann machines Journal Article

In: Mach. Learn., 93 (1), pp. 53–69, 2013.

Links | BibTeX

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.

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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