Magda Gregorová

Magda Gregorova Adjointe scientifique HES (postdoc)
magda.gregorova@hesge.ch

Bio

I am a member of the data mining and machine learning team of Mr. Kalousis in the Department of Business Informatics of the University of Applied Sciences-Western Switzerland, Geneva, as adjointe scientifique (postdoc). I graduated from a Master's program in statistics at the University of Economics in Prague in 2001. After gaining over 12 years of work experience as an applied statistician tackling real-life problems (including in the statistical departments of the Czech and the European Central Banks, and EUROCONTROL, the European Organisation for the Safety of Air Navigation), I have returned to academia and in 2018 defended a PhD in machine learning at the Department of Computer Science at the University of Geneva.

Research

During my PhD I focused primarily on structured sparsity and kernel methods. I'm now exploring the areas of life-long learning, Bayesian inference, and am interested in delving deeper into reinforcement learning.

Teaching

I teach data mining and machine learning courses at bachelor and masters level (course material).

Publications

2018

Gregorova, Magda

Sparse learning for variable selection with structures and nonlinearities PhD Thesis

2018, (PhD Thesis ID: unige:115678).

Abstract | Links | BibTeX

Lavda, Frantzeska; Ramapuram, Jason; Gregorova, Magda; Kalousis, Alexandros

Continual Classification Learning Using Generative Models Workshop

Continual learning Workshop NeurIPS 2018, 2018.

Links | BibTeX

Gregorová, Magda; Ramapuram, Jason; Kalousis, Alexandros; Marchand-Maillet, Stéphane

Large-Scale Nonlinear Variable Selection via Kernel Random Features Inproceedings

Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings, Part II, pp. 177–192, 2018.

Links | BibTeX

Gregorová, Magda; Kalousis, Alexandros; Marchand-Maillet, Stéphane

Structured nonlinear variable selection Inproceedings

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, UAI 2018, Monterey, California, USA, August 6-10, 2018, pp. 23–32, 2018.

Links | BibTeX

2017

Gregorová, Magda; Kalousis, Alexandros; Marchand-Maillet, Stéphane

Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks Inproceedings

Proceedings of The 9th Asian Conference on Machine Learning, ACML 2017, Seoul, Korea, November 15-17, 2017., pp. 161–176, 2017.

Abstract | Links | BibTeX

Gregorová, Magda; Kalousis, Alexandros; Marchand-Maillet, Stéphane

Forecasting and Granger Modelling with Non-linear Dynamical Dependencies Inproceedings

Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II, pp. 544–558, 2017.

Abstract | Links | BibTeX

Ramapuram, Jason; Gregorova, Magda; Kalousis, Alexandros

Lifelong Generative Modeling Journal Article

CoRR, abs/1705.09847 , 2017.

Links | BibTeX

2015

Gregorova, Magda; Kalousis, Alexandros; Dinuzzo, Francesco

Functional learning of time-series models preserving Granger-causality structures Inproceedings

Proceedings of the Time Series Workshop of the 29th Neural Information Processing Systems conference, NIPS-2015, 11th December 2015 2015.

Abstract | Links | BibTeX

Gregorova, Magda; Kalousis, Alexandros; Marchand-Maillet, Stéphane

Learning coherent Granger-causality in panel vector autoregressive models Inproceedings

Proceedings of the Demand Forecasting Workshop of the 32nd International Conference on Machine Learning, ICML 2015.

Abstract | Links | BibTeX